About
The course teaches students comprehensive and specialised subjects in entrepreneurial leadership and management for various business situations; it develops skills in critical thinking and strategic planning for changing and fast-paced environments, including financial and operational analysis; and it develops competences in leadership, including autonomous decision-making, and communication with employees, stakeholders, and other members of a business. These generalized MBA insights are firmly rooted in a curriculum focused on innovation, social entrepreneurship, finance, and technology. Specialised MBA programmes aims to refine the expertise in the specific field.
Target Audience
Ages 19-30, 31-65, 65+
Target Group
The course is suited for executives and general business managers in organisations of all sizes and types, or for those who will soon move into such management positions. It is designed for those that will have responsibility for planning, organising, and directing business operations. Some of the specific pathways will have associated audiences.
For example the MBA in International Business is suited for executives and general business managers, or aspirants to these roles, who work in organisations with global reach and need to enhance their understandings of internationalisation and cross-cultural aspects of work and business.
Similarly, the MBA in Technology Leadership is suited for business leaders at the forefront of digital and technological transformation in their organisations.
In all cases, the target group should be prepared to pursue substantial academic studies fitting to the MQF level.
Mode of attendance
Full-Time and Part-Time
Structure of the programme
Please note that this structure may be subject to change based on faculty expertise and evolving academic best practices. This flexibility ensures we can provide the most up-to-date and effective learning experience for our students.
Full-Time: 50 Weeks, 1 Year, or 3 Semesters (2250 hrs at ~45 hrs/week)
Semester I (~17 weeks): Tier One Foundational modules (30 ECTS, 750 hrs) result in 1 semester of coursework (~45 hrs/week)
Semester II (~17 weeks): Tier Two Specialisation modules (30 ECTS, 750 hrs) result in 1 semester of coursework (~45 hrs/week)
Semester III (~17 weeks): Tier Three Capstone module (30 ECTS, 750 hours) results in 1 semester of coursework (~45 hrs/week)
Part-Time: Up to 250 Weeks, 5 Years, or 15 Semesters (2250 hrs at <9 hrs/week)
Semester I (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester II (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester III (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester IV (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester V (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester VI (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester VII (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester VIII (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester IX (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester X (~17 weeks): Tier One Foundational module (3 ECTS, 75 hrs) at ~4.5 hrs/week
Semester XII (~17 weeks): Tier Two Specialisation module (10 ECTS, 250 hrs) at ~15 hrs/week
Semester XIII (~17 weeks): Tier Two Specialisation module (10 ECTS, 250 hrs) at ~15 hrs/week
Semester XIV (~17 weeks): Tier Two Specialisation module (10 ECTS, 250 hrs) at ~15 hrs/week
Semester XV (~17 weeks): Tier Three Capstone module (30 ECTS, 750 hours) at ~45 hrs/week
Grading System - Scale: 0-100 points - Components: 60% of the mark derives from the average of the assignments, and 40% of the mark derives from the cumulative examination - Passing requirement: minimum of 60% overall
Dates of Next Intake - Rolling admission
Pass rates - 2023 pass rates will be publicised in the next cycle, contingent upon ensuring sufficient student data for anonymization.
Identity Malta’s VISA requirement for third country nationals: https://www.identitymalta.com/unit/central-visa-unit/
How students have found success through Woolf
Course Structure
About
This module will approach leadership by identifying practices that researchers and practitioners have shown to be the most effective. Through these processes, students will gain a broad range of skills.
This module examines how leaders can most effectively use the resources of their team members to achieve business outcomes. The module develops managerial and leadership competencies, focusing on how key improvements in the general strategy and techniques of managing people can produce outcomes more significant than isolated improvements to employee performance. The module provides students with concepts to support them across their careers as they continue to develop effective delegation, management strategy, and engagement with people inside of an organisation.
Specific topics covered include managing a diverse workforce; self-leadership; perception pitfalls; decision making; conflict resolution; emotional intelligence; improving performance; team structure.
Teachers



Intended learning outcomes
- Specialised knowledge of key strategies for effective delegation.
- Critical knowledge of business leadership strategy.
- Analyse and assess theories of management and concepts of delegation and performance tracking.
- Strategies for improving general strategy and techniques of managing people to produce outcomes more significant than isolated improvements to employee performance.
- Select topics for the advanced management of human resources.
- Communicate an in-depth domain-specific knowledge and understanding of business leadership and strategy.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of business leadership and strategy including: Assessing the resources of a team to show how those resources could be used to achieve business outcomes; Assessing the performance of a team to show whether they are on track to meet business goals.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Autonomously gather material and organise it into a coherent, comprehensive presentation.
- d) Demonstrate self-direction in research and originality in solutions for management and leadership problems.
- a) Create critical and contextualised understandings and discussions of key issues related to leadership and management.
- c) Efficiently manage interdisciplinary issues that arise when assessing human resources and delegating effectively to achieve business goals.
- f) Solve problems and be prepared to take leadership decisions related to business leadership and strategy.
- e) Identifying research problems and solutions related to business leadership and strategy.
- b) Apply a professional and scholarly approach to research problems pertaining to the effective use of team resources and delegation of personnel.
About
In general terms, financial accounting is the measurement of economic activity for decision-making. Financial statements are a key product of this measurement process and an important component of firms’ financial reporting activities.
The objective of this module is to help students become intelligent readers of the financial reports of most publicly traded companies. Students will learn the development, analysis, and use of these reports by focusing on what these reports contain, what assumptions and concepts accountants use to prepare them, and why they use those assumptions and concepts. A solid understanding of the fundamentals covered in this module should enable students to do well in more advanced finance and accounting courses and to interview intelligently for jobs in finance, consulting, and general management.
The module begins with the basic concepts of accounting. Students will analyse the main financial statements: balance sheet, income statement, statement of cash flows, and statement of stockholders’ equity. Particular attention is paid to how these four statements relate to each other and how they provide information about the operating performance and financial health of a company. The module also covers specific items from the financial statements and applies tools of analysis whenever possible.
Teachers



Intended learning outcomes
- Varying scholarly views on when to set an allowance using a balance sheet or income statement approach.
- Specialised knowledge of factors determining when to capitalise or expense.
- Select topics related to assets, liabilities, and equities.
- Critical knowledge of the relationship between cash and accrual accounting.
- Apply ratio analysis to companies in different industries and perform a critical assessment of their performance based on limited or incomplete information.
- Interpret Balance sheets, income statements, and statement cash flows.
- Prepare simple journal entries, ledgers, trial balances, and end-of period adjusting entries.
- Prepare simple financial statements and explain their significance to internal and external audiences.
- c) Identify issues related to revenue recognition.
- d) Makes judgments in assessing how a given financial statement analysis is tied to valuation.
- a) Understand, interpret, and describe how business activities are captured by financial statements.
- b) Explain how components of financial statements are linked together.
- e) Assess and analyse companies’ strategic engagement in earnings management activities.
About
This module will approach leadership by identifying practices that researchers and practitioners have shown to be the most effective. Through these processes, students will gain a broad range of skills.
This module examines how leaders can most effectively use the resources of their team members to achieve business outcomes. The module develops managerial and leadership competencies, focusing on how key improvements in the general strategy and techniques of managing people can produce outcomes more significant than isolated improvements to employee performance. The module provides students with concepts to support them across their careers as they continue to develop effective delegation, management strategy, and engagement with people inside of an organisation.
Specific topics covered include managing a diverse workforce; self-leadership; perception pitfalls; decision making; conflict resolution; emotional intelligence; improving performance; team structure.
Teachers



Intended learning outcomes
- b) Develop a specialised knowledge of key strategies related to the accounting cycle.
- d) Critically understand the diverse scholarly views on revenue recognition and cost measurement.
- e) Critically assess the relevance of theories for business applications in the domain of accounting, finance, and economics.
- c) Acquire knowledge of select topics for the advanced management of financial-statement preparation, use, and analysis.
- a) Develop a critical understanding of business accounting, finance, and economics.
- h) Communicate clearly about business finance, accounting, and microeconomics in the context of managerial decisions.
- e) Assess, analyse, and criticise the various strategies for handling matters arising in the context of entrepreneurial finance and accounting.
- b) Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- a) Autonomously gather material and organise it into a coherent financial statement, and be able to interpret financial statements
- d) Apply an in-depth domain-specific knowledge and understanding to business accounting, finance, and economics.
- g) Propose appropriate solutions to complex and changing problems pertaining to business accounting, finance, and economics.
- f) Compare and evaluate the different methodologies recommended in scholarly sources pertaining to how managers should handle business accounting, finance, and economics.
- c) Creatively apply microeconomic theory to develop critical and original solutions for the challenges of business economics.
- c) Efficiently manage interdisciplinary issues that arise in connection to the trade-off between risk and return.
- d) Demonstrate self-direction in research and originality in solutions for entrepreneurial finance and accounting.
- f) Solve problems and be prepared to take leadership decisions related to the methods and principles of capital budgeting.
- b) Apply a professional and scholarly approach to research problems pertaining to the trade-off between risk and return.
- a) Create synthetic contextualised discussions of key issues related to revenue recognition and cost measurement.
- e) Act autonomously in identifying research problems and solutions related to business accounting, finance, and economics.
About
This module explores basic economic principles (theories and applications) that are relevant to a variety of businesses. The module emphasises an economist's mindset and amassing the tools necessary to do so, including the study of microeconomics and macroeconomics.
Throughout the module, students will examine the underlying economics of successful business strategy: the strategic imperatives of competitive markets, the sources and dynamics of competitive advantage, managing competitive interactions, and the organisational implementation of business strategy.
Additionally, the module focuses on case discussion and analysis and provides a foundation for consultants, managers, and corporate finance generalists.
Teachers



Intended learning outcomes
- c) Has a comprehensive knowledge of the business cycle beyond that associated with general studies.
- a) Has specialised knowledge of techniques for production and cost analysis.
- b) Have the autonomy to recognise and describe the different strategic goals for firms managing in competitive and monopolistic environments.
- a) Research the determinants of market demand and supply in a given industry.
- c) Demonstrates the ability to respond to fast-changing market conditions with actionable proposals for strategic firm behaviour including game theory, entry and deterrence, collusion and cooperation, and bargaining.
- b) Select topics in the strategic deployment of Information, auctions, and incentives.
- c) Analyse and take leadership decisions in a fast-changing environment about monetary policy and the supply and demand for money.
- b) Analyse and communicate the relevance of gross domestic product and its components for a given market.
- a) Performs critical evaluations of business environments in order to model relevant markets.
About
The role of marketing management in organisations is to identify and measure the needs and wants of consumers, to determine which targets the business can serve, to decide on the appropriate offerings to serve these markets, and to determine the optimal methods of pricing, promoting, and distributing the firm’s offerings. Successful organisations are those that integrate the objectives and resources of the organisation with the needs and opportunities of the marketplace. The goal of this module is to facilitate student achievement of these goals regardless of career path.
This module addresses how to design and implement the best combination of marketing efforts to carry out a firm's strategy in its target markets. Specifically, this module helps to develop the student's understanding of how the firm can benefit by creating and delivering value to its customers, and stakeholders, and develop skills in applying the analytical concepts and tools of marketing to such decisions as segmentation and targeting, branding, pricing, distribution, and promotion.
Teachers



Intended learning outcomes
- a) Factors determining selection of which businesses and segments to compete in.
- c) The role of channels, channel partners, and other intermediaries in delivering products, services, and information to customers.
- b) Strategic issues facing today's managers in a dynamic competitive environment.
- b) Formulate and implement marketing strategies for brands and businesses.
- e) Make cross-functional connections between marketing and other business areas.
- a) Apply marketing concepts to real-life marketing situations.
- d) Make and defend marketing decisions in the context of real-world problem situations with incomplete information.
- c) Allocate resources across businesses, segments, and elements of the marketing mix.
- a) Critically analyse the tasks of marketing and examine the major functions that comprise the marketing task in organisations.
- b) Assess market potential.
- c) Classify and analyse customer segments, to develop effective marketing strategy.
About
In this module, students will gain the capacity to appropriately apply a broad repertoire of communication skills in business, professional, and social contexts.
Throughout the module, students will critically analyse managerial communication skills required for leadership in a wide variety of industries. It considers the varied means of communication including writing, speaking, and calling, and generally appearing professional. The communication requirements of different contexts are studied, including informational, persuasive, and relational forms of communication.
Teachers



Intended learning outcomes
- Theories for business applications in the domain of effective managerial communication.
- Effective managerial communication techniques, guidelines, and strategies.
- Topics for the advanced management of effective managerial communication-including writing, speaking, calling –and generally appearing professional.
- Diverse scholarly views on effective managerial communication.
- Key strategies for applying effective managerial communication to improve the connection between management and frontline employees.
- Autonomously gather material and organise it into a coherent, comprehensive presentation of effective managerial communication techniques and strategies.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing in discussions of effective managerial communication.
- Apply in-depth domain-specific knowledge and understanding to effective managerial communication.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of effective managerial communication.
- Act autonomously in identifying research problems and solutions related to effective managerial communication.
- Efficiently manage interdisciplinary aspects of effective managerial communication.
- Apply a professional and scholarly approach to defining appropriate and effective managerial communication.
- Solve problems and be prepared to take leadership decisions related to effective managerial communication
- Create synthetic contextualised discussions of key issues related to effective managerial communication.
- Demonstrate self-direction in originality in developing an appropriately broad repertoire of communication skills.
About
This module is designed to achieve an understanding of fundamental notions of data presentation and analysis and to use statistical thinking in the context of business problems.
The module addresses modern methods of data exploration (designed to reveal unusual or problematic aspects of databases), the uses and abuses of the basic techniques of inference, and the use of regression as a tool for management and for financial analysis. The potential ethical issues related to each topic will be reviewed. Socially and environmentally relevant data will be utilised throughout the module.
The goal of the module is not to turn students into statisticians but to enable them to appreciate the use of probability in assessing evidence and making decisions, and to be statistically literate consumers of quantitative information generated by economists, biomedical researchers, psychologists, statisticians, survey researchers, and other experts.
Teachers



Intended learning outcomes
- Critical awareness of the fundamental methods of statistics (sampling, correlation, and regression) and the essential concepts of statistical thought (probability distributions, estimation, hypothesis testing, and decision theory), at a level beyond undergraduate studies and responsive to managerial contexts.
- A specialised understanding of the limitations of statistical inference and of the ethics of data analysis and statistics, especially in business situations.
- Test for consistency of data with particular values of parameters.
- Construct and use descriptive statistics, graphs, charts, and tables to analyse data sets.
- Interpret computer output and use it to solve problems.
- Determine sample size for given levels of confidence and margins of error.
- Apply correctly a variety of statistical techniques, both descriptive and inferential.
- Integrate statistical analysis in a decision-making process.
- Interpret linear association and conduct simple linear regression data analysis.
About
In this module students will strengthen their capacity to lead individuals, teams, and organisations in processes that generate data-driven solutions to problems, data-driven insights into customer behaviour, and data-driven decision-making.
This module provides the foundations of probability and statistics required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty, with incomplete information, and in both structured and unstructured settings. Theoretical topics include decision trees, hypothesis testing, multiple regression, and sampling.
Teachers



Intended learning outcomes
- Key theoretical topics pertaining to evidence-based decision-making such as decision trees, hypothesis testing, multiple regression, and sampling.
- The foundations of probability and statistics to the extent required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty.
- The relevance of theories for business applications in the domain of evidence-based decision-making.
- Select topics for the advanced management of data- driven insights into customer behaviour.
- Diverse scholarly views on evidence-based decision-making in a business context.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Apply an in-depth domain-specific knowledge and understanding to evidence-based decision-making in a business context.
- Autonomously gather evidence and organise it into a coherent, comprehensive presentation advocating an evidence-based decision.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of evidence-based decision-making in a business context.
- Solve problems and be prepared to take leadership decisions related to evidence-based decision-making in a business context.
- Act autonomously in identifying research problems and solutions related to evidence-based decision-making in a business context.
- Create synthetic contextualised discussions of key issues related to evidence-based decision-making.
- Apply a professional and scholarly approach to data and evidence as factors in decision-making.
- Demonstrate self-direction in gathering and using evidence and data for decision-making.
- Efficiently manage interdisciplinary and diverse kinds of evidence that inform decision-making.
About
This module examines how leaders can most effectively use the resources of their team members to achieve business outcomes. The module develops managerial and leadership competences, focussing on how key improvements in the general strategy and techniques of managing people can produce outcomes more significant than isolated improvements to employee performance.
The module provides students with concepts to support them across their careers as they continue to develop effective delegation, management strategy, and engagement with people inside of an organisation.
Teachers



Intended learning outcomes
- The relevance of theories of management and concepts of delegation and performance tracking.
- Critical knowledge of business leadership strategy.
- Key strategies for effective delegation.
- Select topics for the advanced management of human resources.
- Why improvements in the general strategy and techniques of managing people can produce outcomes more significant than isolated improvements to employee performance.
- a) Autonomously gather material and organise it into a coherent, comprehensive presentation.
- b) Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- c) Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of business leadership and strategy including: • Assessing the resources of a team to show how those resources could be used to achieve business outcomes. • Assessing the performance of a team to show whether they are on track to meet business goals.
- d) Communicate an in-depth domain-specific knowledge and understanding to business leadership and strategy.
- Apply a professional and scholarly approach to research problems pertaining to the effective use of team resources and delegation of personnel.
- Create synthetic contextualised discussions of key issues related to leadership and management strategy.
- Efficiently manage interdisciplinary issues that arise when assessing human resources and delegating effectively to achieve business goals.
- Solve problems and be prepared to take leadership decisions related to business leadership and strategy.
- Demonstrate self-direction in research and originality in solutions for management and leadership.
- Act autonomously in identifying research problems and solutions related to business leadership and strategy.
About
Increases in product variety and customization in the past few years have posed challenges to firms in terms of delivering products to customers faster and more efficiently. With the prevalence of the usage of the Internet for business, electronic business transformations are occurring in every business. One of the fundamental enablers of electronic commerce is effective supply chain management. Thus, supply chain management has become the focus of attention of senior management in the industry today.
This module considers management of a supply chain in a global environment from a managerial perspective. The focus is on analysis, management, and improvement of supply chain processes and their adaptation to the electronic business environment. The module focuses on six topics: Inventory and Information Management; Distribution and Transportation; Global Operations; Supplier Management; Management of Product Variety; and Electronic Supply Chains. Several new concepts including Prognostic Supply Chains, Build-to-Order, Collaborative Forecasting, Delayed Differentiation, Cross Docking, Global Outsourcing, and Efficient Consumer Response will also be discussed. At the end of the module, a student will have the necessary tools and metrics to evaluate a current supply chain and recommend design changes to supply chain processes
Teachers



Intended learning outcomes
- A specialised knowledge of the global outlook that reflects changes experienced and anticipated by firms and industries and the requirements for effective change management in operations and supply chains.
- A critical knowledge of the increasing importance of supply chain management in today’s business environment.
- Define and assess the significance of logistics as it relates to transportation and warehousing.
- Design management plans for global supply chains that are lawful, ethical, and environmentally and socially responsible.
- Utilise management skills such as negotiating, working effectively within a diverse business environment, ethical decision-making, and use of information technology.
- Demonstrate the use of effective written and oral communications, critical thinking, team building, and presentation skills as applied to business problems.
- Analyse and improve supply chain processes.
- Use concepts of operations and supply chain management and qualitative and quantitative methods to make decisions in business contexts that include new and unfamiliar situations.
- Align the management to supply chains with corporate goals and strategies.
- Apply current supply chain theories, practices, and concepts utilising case problems and problem-based learning situations.
- Analysing current supply chain management trends and their relevance for specific markets, industries, or organisations.
- Use and apply computer-based supply chain optimization tools including the use of selected state-of-the-art supply chain software suites currently used in business.
About
In this module, students learn about the complex responsibilities facing business leaders today. Through cases about difficult managerial decisions, the course examines the legal, ethical, and economic responsibilities of corporate leaders. It also teaches students about management and governance systems leaders can use to promote responsible conduct by companies and their employees, and shows how personal values can play a critical role in effective leadership. Additionally, this module is designed to deepen and extend students' conceptual and practical understanding of leadership in organisations, extending beyond the application of knowledge in practical judgements that achieve business outcomes, to embrace wider social and ethical considerations. The course is experiential and multidisciplinary, requiring participants to reflect on the social and ethical responsibilities of leaders in relation to their own experiences. It is designed to help students discover insights about themselves as leaders, fostering the development of self-awareness, including strengths and opportunities for personal growth.
Teachers



Intended learning outcomes
- Select topics for advanced cultivation and management skills related to one’s own experiences.
- Critical knowledge of ways in which one’s behaviours and decision-making can impact others and affect goals of leading with integrity.
- Theories of corporate responsibility in relation to ethical considerations.
- Specialised knowledge of key strategies for cultivating reflective leadership.
- Diverse scholarly views on self-awareness.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on the social and ethical responsibilities of leaders in relation to their own experiences.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of responsible leadership.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing, when communicating about the cultivation of social and ethical responsibilities faced by leaders.
- Efficiently manage interdisciplinary issues that arise when assessing the conditions for corporate accountability.
- Demonstrate self-direction in cultivating habits that improve accountability while in leadership positions.
- Create synthetic contextualised discussions of key issues related to leadership and corporate accountability.
- Solve problems and be prepared to take leadership decisions related to social and ethical considerations.
About
This module is designed to provide students with the skills and knowledge to influence and lead social impact in business and impact contexts. By the conclusion of this module, students should have a strong foundation in social impact and social change, including approaches to funding impact, scaling programmes, and interventions, public-private partnerships, corporate engagement, impact investment decision-making, blended capital, and approaches to intentional impact.
The module will pivot around multiple case studies addressing social issues through which students learn and test social impact frameworks and concepts. Once students have gained a mastery of perspectives and methodologies necessary to consider and address a social issue from the ground up, they will next learn to identify and utilise effective measures of outputs and progress and explore the core levers and potentials to change outcomes for people, communities and market systems.
Teachers



Intended learning outcomes
- Critical knowledge of public-private partnerships and corporate engagement in relation to social change.
- Impact investment decision-making and its impact on global business.
- The impact of diversity, equity, and inclusion in organisations on approaches to intentional impact.
- Strategic approaches that organisations use to foster social change.
- Autonomously gather material and organise it into coherent, comprehensive presentations identifying and utilising effective measures of outputs and progress that explore the core levers and potentials to change outcomes for people, communities, and market systems
- Creatively apply the theories learned in the module to test social impact frameworks and concepts
- Ability to critically discuss social change programmes and interventions in terms of organisations and society.
- Efficiently manage interdisciplinary issues related to funding impact in a corporate setting.
- Understand and assess the historical evolution of social impact and social change globally.
About
The objective of this module is to provide students the basic data analysis and modelling concepts and methodologies using probability theory. Basic statistics concepts and probability concepts will be covered. Fundamental data analysis and hypothesis techniques will be covered. Further data modelling methodologies such as Hidden Markov Models and Bayesian networks will be introduced. Students successfully completing this module will have gained a solid understanding of probabilistic data modelling, interpretation, and analysis and thus have formed an important basis to solve practical statistics and data analysis-related problems arising in real-world business situations. The techniques discussed are applied in all functional areas within business organisations including accounting, finance, human resource management, marketing, operations, and strategic planning.
Teachers



Intended learning outcomes
- Select topics in acquiring and cleaning data.
- Researching, evaluating, and selecting appropriate mathematical and statistical tools for data analytics problems.
- A specialised knowledge of various data warehousing architectures, processes, and operations.
- A critical understanding of varying scholarly perspectives on measuring fit and performance of models appropriately.
- Execute statistical analyses with professional statistical software.
- Construct complex statistical models.
- Integrate data from disparate sources.
- Build and assess data-based models.
- Describe the business intelligence methodology and concepts and relate them to decision support.
- Identify and interpret the data relevance, reliability, and validity from multiple sources.
- Proficient in solving business problems by identifying data gaps and synthesising data to deliver quality output.
- Research and utilise validated data to logically construct reports based on needs.
- Apply data science concepts and methods to solve problems in real-world business contexts and communicate these solutions effectively.
- Use data visualisation tools to analyse data and produce reports.
- Demonstrate proficiency with statistical analysis of data.
About
This module introduces students to one of the world’s most widely used and in-demand programming languages and its specific applications to business analytics. Python is used in a wide range of fields, including web development, data science, fin-tech, health care, and more. With Python, business leaders can scrape online sources to determine consumer sentiment, automate tasks, run advanced models, and export code across different applications. Throughout the module will develop the following skills: Apply programmatic logic to complex business problems in areas such as finance, operations, and marketing; Use technical knowledge to lead and manage teams in today’s evolving digital economy; Leverage state-of-the-art tools and powerful, open-source Python libraries to clean, analyse and visualise data.
Teachers



Intended learning outcomes
- Specialised knowledge of data processing with Python language.
- Analyse and assess various scholarly views on the practical applications of machine learning models in data analytics.
- A critical understanding of various Python libraries and their applicability to real-world business situations.
- Predict the results of various Python codes.
- Analyse and read Python data using datasets.
- Write Python code to read, write, filter, merge, summarise, and graph a given dataset.
- Independently build data models.
- Describe and perform Python data acquisition and analysis techniques.
- Communicate effectively the purpose, methodology, and results of an analysis involving Python to a non-technical business audience.
- Derive hidden information from voluminous and complex data.
- Analyse data from a variety of industries and uncover business insights.
About
The focus of this module is to introduce concepts, skills, and strategies for performing competitively in the business market where organisations rather than households are the customers. This module provides a managerial introduction to the strategic and tactical aspects of business marketing decisions and marketing channel strategy. Students examine the strategic concepts and tools that guide market selection, successful differentiation in business markets, and supply chain management. Students will examine how product and service decisions are designed to deliver the B2B value proposition, how pricing captures customer value, how value is communicated to and among customers, and how marketing channels are used to make this value accessible to target customers. Additionally, students will compare and contrast how the strategic and tactical processes of developing and managing value-generating relationships differ between B2B and B2C markets. Moreover, students will also gain an understanding of how to manage channel power, conflict, and relationships.
Teachers



Intended learning outcomes
- A critical understanding of the process by which strategic market analysis guides the development of B2B marketing programmes that integrate product pricing, communications, and channel decisions
- The ability to assess differing systematic approaches to problem solving and decision-making in business marketing organisations through the use of case studies.
- Design strategies and structures to effectively serve the B2B market.
- Analyse market opportunities and company capabilities as the basis for market selection, developing competitive differentiation, and formulating marketing channel strategy in contemporary business markets.
- Develop a business marketing plan for real-life applications.
- Develop managerial orientation to implementing and controlling B2B marketing programmes and managing channel relationships.
- Develop a managerial perspective on the marketing function in firms that target business and government customers in both domestic and global contexts.
- Critically discuss the applications, challenges, and environment of B2B marketing, including the unique nature of organisational buying behaviour.
About
The role of marketing management in organisations is to identify and measure the needs and wants of consumers, to determine which targets the business can serve, to decide on the appropriate offerings to serve these markets, and to determine the optimal methods of pricing, promoting, and distributing the firm’s offerings. Successful organisations are those that integrate the objectives and resources of the organisation with the needs and opportunities of the marketplace. The goal of this module is to facilitate student achievement of these goals regardless of career path.
Throughout the module, students will study various tools for generating marketing insights from data in such areas as segmentation, targeting and positioning, satisfaction management, customer lifetime analysis, customer choice, product and price decisions using conjoint analysis, and text analysis, and search analytics.
Teachers



Intended learning outcomes
- A specialised knowledge of real-world applications of conjoint analysis.
- Select topics in marketing data collection, analysis, and interpretation.
- Various scholarly approaches to cluster analysis methods for marketing segmentation, analysis, and positioning.
- A critical understanding of selected marketing concepts within the context of specific business problems and their applications.
- Conduct customer lifetime analysis.
- Apply marketing concepts to real-life marketing situations.
- Use various data visualisation tools to communicate clearly about customer behavior, preferences, or other insights.
- Set up regressions, interpret outputs, analyse confounding effects and biases, and distinguish between economic and statistical significance.
- Critically analyse different methods for data-driven decision making in a marketing context..
- Assess the major functions that comprise the marketing task in organisations, and create data-informed approaches to these functions..
- Measure customer lifetime value and use that information to evaluate strategic marketing alternatives.
About
Throughout this module, students will learn the basic concepts of needs analysis, investment policy, asset allocation, product selection, portfolio monitoring and rebalancing. Students will assess the various types of institutional investors, including pension funds and insurance companies and develop skills related to the client management life cycle and portfolio management as a process. The module will address the basic concepts, principles, and the major styles of investing in alternative assets. Additionally, students will learn about the impact of digitization on investment strategies and the issues related to performance measurement, transaction costs and liquidity risk, margin requirements, risk management, and portfolio construction. Other topics addressed in the module include quantitative investment strategies used by active traders and methodologies to analyse them. Through the use of case studies, students will learn to use real data to back-test or evaluate several of the most successful trading strategies used by active investment managers. As a result, students will learn to read and analyse academic research articles in search of profitable and implementable trading ideas.
Teachers



Intended learning outcomes
- A critical knowledge of common strategies in quantitative investing.
- Principles of bond market and yield used to critically assess forecasting.
- The ability to identify, assess, and analyse common investment pitfalls through overleveraging and underappreciating.
- Evaluate the different theoretical foundations of active investment management.
- Use statistical packages and other programming tools to make investments, measure performance, and change strategic direction in response to rapidly changing market conditions.
- Make informed stock selections by measuring risk and applying risk management and analytical theory to choices.
- Utilise financial and economic databases for real-world applications.
- Make informed market decisions with a deep understanding of capital markets and major investable asset classes.
- Analyse the performance of investment products over time by using large data sets and statistical packages for measuring performance.
- Communicate effectively to technical and nontechnical audiences about underlying empirical evidence that informs investment decisions.
- Critically assess challenges of leveraging and shorting.
- Apply modern risk management and analytical theory to stock selection.
- Perform the functions of a quantitative research analyst at an investment firm with autonomy.
About
Throughout this module, students will develop the analytical tools necessary to understand crisis prevention and management, and risk management. The properties and characteristics of risk management techniques will be analysed and related to corporate and sovereign default risk, hedging and trading strategies, regulation, and assessing financial stability and systemic risk. Emphasis will be put on applying these techniques to problems emerging in the marketplace.
Additionally, this module addresses the ability of different risk management approaches to account for large market shocks. Students will study the effect of leverage, through borrowing or through the structuring of assets, in amplifying shocks and increasing risk, and the role of capital in mitigating them. The information learned in this module will help business leaders understand their role in regulatory compliance and participate constructively in these interactions.
Teachers



Intended learning outcomes
- e) Evaluate legal risk and reputational risk as factors in risk management.
- d) Select topics in corporate governance, accounting, and disclosure that prioritize the health of financial markets
- b) Implementation of M&A-related risk management with respect to capital structure and interest rate risk.
- a) A critical understanding of key funding issues including how much debt a company should have, how different types of debt compare, and liability management techniques.
- c) Commodity risk management, including derivatives available and hedging techniques.
- c) Perform currency risk management, including assessing the different types of currency risk for a given organization, evaluating different hedging techniques, and managing emerging market currency risk.
- a) Identify and measure risk exposures using factor models, Monte Carlo simulations, and Value at Risk.
- d) Assess interest rate risk management, including the risks of different types of liabilities, how liabilities are optimised with respect to cost versus risk, derivatives available, hedging, and pre hedging techniques.
- b) Develop effective risk management policies which address key roles and responsibilities, different approaches, advisable policy limits, and performance assessments.
- e) Critically assess counterparty risk management, including derivatives available, and hedging techniques.
- c) Perform critical evaluations of risk factors and evaluate risk management approaches on the basis of incomplete information in a fastchanging business context.
- a) Communicate the importance of risk management, key objectives, concerns, and challenges to technical and nontechnical audiences.
- b) Research solutions to real-world risk management problems across a variety of risk factors (currency risk, commodity risk, etc.).
About
This module explores the international business environment in which organisations operate. Throughout the module, students will examine the structure and features of international markets, how organisations engage with these markets, and how they respond to their complexities. Students are introduced to useful theoretical and analytical frameworks that are crucial to understanding the opportunities and risks derived from the political, economic, social, technological, and institutional environment of countries.
The module also addresses aspects of global institutions, such as the World Trade organisation (WTO) and the International Monetary Fund (IMF), which set global rules that affect business strategy and human welfare.
Teachers



Intended learning outcomes
- A critical understanding of the principal theories of international trade and investment, including those related to exchange rate regimes and global stock and bond markets.
- Specialised knowledge of factors driving an organisation’s entrance into international business environments.
- Select topics in the impact of regional treaties on international trade as well as the monetary and financial environment for international business.
- Critically assess and communicate effectively on the role played by multinational economic and social aid organisations such as the UN, EU, IMF, WTO, and World Bank in facilitating international trade and business.
- Autonomously assess and advise on business operations and relationships in complex international business environments.
- Act ethically, diplomatically, and with emotional sensitivity in international business environments.
- Simulate cross-cultural business negotiations by recalling the steps in global strategic planning and the models available to direct the analysis and decision-making involved.
- Assess the nature and impact of globalisation on the world’s economy.
- Effectively communicate how economic and political systems interact to form a political economy.
- Identify how cultural differences restrict and create opportunities for management action, international trade, and its forms and theories.
About
Teachers



Intended learning outcomes
About
This module examines specific issues involved in building and managing global brands in such a way that they contribute to shareholder value. A global brand uses the same name and logo and has awareness, availability, and acceptance in multiple regions of the world. It shares the same strategic principles, values, positioning, and marketing throughout the world. Although the marketing mix can vary, it is managed in an internationally coordinated manner. Throughout this module, students will develop skills related to building strong global brands; developing marketing mix strategies that are an effective combination of global standardisation, local adaptation, and worldwide learning; and managing global brands.
Teachers



Intended learning outcomes
- e) Relevance of theories for business applications in the domain of global brand management.
- d) Diverse scholarly views on evidence-based brand management in a business context.
- b) Key theoretical topics pertaining to brand management such as multichannel and multicultural strategies, global standardisation, local adaptation, and worldwide learning.
- c) Selected topics for the advanced management of brands considering customer perceptions and expectations.
- a) A critical understanding of the factors driving global brand recognition and engagement at a level required for managerial decisionmaking.
- b) Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- a) Autonomously gather evidence and organise it into a coherent, comprehensive presentation advocating specific approaches to brand management.
- c) Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of global brand management in a business context.
- d) Apply in-depth domain-specific knowledge and understanding to branding strategies in a business context.
- a) Participate in and analyse discussions of key issues related to international branding.
- d) Demonstrate self-direction in gathering and using evidence and data for developing marketing strategies related to brand.
- b) Apply a professional and scholarly approach to data and evidence as factors in developing a global brand.
- f) Solve problems and be prepared to take leadership decisions related to evidence-based decision-making in a business context.
- c) Efficiently manage interdisciplinary and diverse kinds of evidence that inform branding.
- e) Act autonomously in identifying research problems and solutions related to global branding in a business context.
About
Teachers



Intended learning outcomes
About
This module focuses on multiple aspects of team dynamics and structure, with a focus on the organisational intelligence needed to lead and manage diverse organisations in a varied marketplace. Theories of organisational behaviour, social psychology, and anthropology are critically discussed in relation to real-world scenarios.
Additionally, this module introduces students to the challenges and opportunities faced in multifaceted workplaces and provides evidence-based insights and practical strategies for how to accelerate team engagement and belonging as a pathway to sustainability and competitive advantage. Ultimately, this module enables students to successfully build and lead organisations that are multifaceted, equitable, and engaging.
Teachers
Intended learning outcomes
- The impact of employing persons with varying backgrounds on firm strategy, organisational performance, and market leadership.
- Strategic approaches that organisations use to foster cross-team and cross-cultural collaboration.
- The impact of cross-cultural competence and incompetence on global business practices.
- Frameworks for comparing and contrasting workers’ values and diagnosing potential complications.
- Employ the standard modern conventions for practising conscious inclusion in teams and organisations.
- Creatively apply the theories learned in the module to develop strategic approaches that organisations can use to foster workforce collaboration and leverage difference as a source of sustainable competitive advantage.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on the social and ethical responsibilities of leaders in relation to their own experiences through the use of fieldwork.
- Understand and assess the historical evolution of workplace sustainability and equity globally.
- Critically discuss diverse workplaces and inclusion in terms of organisations and society.
- Efficiently manage interdisciplinary issues related to the relationship between culture and self-presentation in a workplace setting.
About
This module encompasses statistics, decision analysis, and simulation modelling.
Throughout the module, students will strengthen their capacity to lead individuals, teams, and organisations in processes that generate data-driven solutions to problems, data-driven insights into customer behaviour, and data-driven decision-making. This module provides the foundations of probability and statistics required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty, with incomplete information, and in both structured and unstructured settings. Theoretical topics include decision trees, hypothesis testing, multiple regression, Monte Carlo simulation, and sampling and estimation.
Teachers



Intended learning outcomes
- Theories for business applications in the domain of evidence based decision-making.
- A critical understanding of the foundations of probability and statistics to the extent required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty.
- Key theoretical topics pertaining to evidence-based decisionmaking such as decision trees, hypothesis testing, multiple regression, and sampling.
- Relevant topics for the advanced management of data-driven insights into customer segments.
- Diverse scholarly views on evidence-based decision-making in a business context.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of evidence-based decision-making in a business context.
- Autonomously gather evidence and organise it into a coherent, comprehensive presentation advocating an evidence-based decision.
- Apply in-depth domain-specific knowledge and understanding to evidence-based decision-making in a business context.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Efficiently manage interdisciplinary and diverse kinds of evidence that inform decision-making.
- Apply a professional and scholarly approach to data and evidence as factors in decision-making.
- Solve problems and be prepared to take leadership decisions related to evidence-based decision-making in a business context.
- Act autonomously in identifying research problems and solutions related to evidence-based decision-making in a business context.
- Create synthetic contextualised discussions of key issues related to evidence-based decision-making.
- Demonstrate self-direction in gathering and using evidence and data for decision-making.
About
Financial reports contain important information about a company's past, present, and future. The ability to read these reports provides valuable insights into an organisation's strengths and shortcomings.
This module is designed to prepare students to interpret and analyse financial statements for tasks such as credit and security analyses, lending and investment decisions, and other decisions that rely on financial data. Throughout the module, students will explore in greater depth financial reporting from the perspective of financial statement users. Students will develop a sufficient understanding of the concepts and recording procedures and therefore will be able to interpret various disclosures in an informed manner. Additionally, students will learn how to compare companies financially, understand cash flow, and grasp basic profitability issues and risk analysis concepts.
Teachers



Intended learning outcomes
- A critical knowledge of ratios used to compare a firm to its competitors and to evaluate changes in ratios over time.
- Select topics in forecasting future earnings and anticipating market reactions.
- Specialised knowledge of tactics for recognizing accounting errors, either intentional or unintentional, and their impact on reported income and the book value of equity
- Research and develop an analysis of an organisation’s performance and risk.
- Use ratios to help forecast and make financial predictions.
- Read and critically evaluate financial analyst reports on publicly listed companies.
- Make predictions related to the stock market’s response to quarterly earnings.
- Apply analytical tools and concepts in competitor analysis, credit and investment decisions, and business valuation.
- Interpret various disclosures in an informed manner.
- Critically analyse a business’s finances.
- Develop a sufficient understanding of the concepts and recording procedures.
- Understand and evaluate major valuation models.
- Critically compare companies financially, understand cash flow, and grasp basic profitability issues and risk analysis concepts.
- Understand and interpret assets and liabilities reported on a balance sheet.
About
This course explores the dynamic world of entrepreneurship with It offers a blend of theoretical frameworks and practical strategies essential for launching and scaling businesses in today’s competitive market.
Key topics include ideation, business model development, market analysis, and funding strategies. Students will learn how to create robust business plans, attract investors, and build scalable operations. The course also covers leadership skills, team building, and the challenges of scaling, providing a comprehensive toolkit for entrepreneurial success.
Through case studies of high-growth startups and interactive sessions with seasoned experts, students will gain real-world insights and actionable strategies. Hands-on projects and pitch presentations will further enhance their ability to turn innovative ideas into thriving businesses. By the end of this course, students will be prepared to launch new ventures and scale existing ones, driving innovation and growth in the entrepreneurial landscape.
Teachers



Intended learning outcomes
- Identify key factors and variables influencing business success and failure, such as market trends, competitive dynamics, and financial metrics.
- Define scalability in the context of business operations and leadership, emphasizing the ability to grow and expand operations without proportional increases in resources or costs.
- Explain negotiation techniques and principles for securing favorable terms and agreements in funding deals and strategic partnerships.
- Cultivate effective communication and persuasion skills to pitch business ideas, negotiate funding deals, and establish strategic partnerships.
- Demonstrate proficiency in conducting market analysis, competitor research, and customer segmentation to inform strategic decision-making and business planning.
- Implement scalable operational processes and systems to support business growth and expansion while maintaining operational efficiency and quality standards.
- Implement scalable operations and leadership practices to manage growth effectively and sustain long-term success in dynamic market environments.
- Demonstrate proficiency in financial modeling and valuation techniques to attract investors and secure financing for venture launches and scaling initiatives.
- Develop comprehensive business plans that integrate thorough market analysis, financial projections, and growth strategies to ensure successful venture launches.
About
Excel in entrepreneurship with "Finding the Product-Market Fit," a specialized MBA course designed to equip aspiring business leaders with the skills to align products with market demands. This course delves into the critical process of ensuring that a product meets the needs of its target market, a key determinant of startup success. The course highlights strategies for achieving sustainable product-market fit and scaling businesses effectively. Through case studies of high-growth companies, students will gain practical insights into successful product-market fit strategies. Hands-on projects and guidance from seasoned entrepreneurs will provide real-world experience in testing and validating product concepts. By the end of this course, students will be prepared to develop and refine products that truly meet market needs, ensuring a solid foundation for entrepreneurial success and growth.
Teachers



Intended learning outcomes
- Describe segmentation strategies and frameworks to effectively identify and prioritize target customer segments.
- Understand the role of feedback in validating product-market fit and driving iterative product development.
- Define the key components of a value proposition, including customer benefits, unique selling points, and competitive differentiation.
- Apply iterative design and prototyping techniques to refine product features and enhance value proposition effectiveness.
- Interpret and analyze market data to extract actionable insights relevant to product-market fit and value proposition development.
- Apply critical thinking skills to assess market research needs and select appropriate methodologies for targeting customer segments.
- Evaluate market data to discern customer needs and preferences, guiding strategic decision-making.
- Implement feedback mechanisms to systematically collect and analyze insights from customers and stakeholders.
- Construct clear and compelling value propositions tailored to specific customer segments.
About
This course is designed to help aspiring entrepreneurs identify and address market needs effectively. It focuses on developing a deep understanding of customer problems and creating solutions that resonate with the target audience. Through case studies of successful startups, students will gain practical insights into the process of refining their business ideas. Hands-on projects and mentorship from experienced entrepreneurs will further enhance their ability to create viable and impactful solutions. By the end of this course, students will be equipped with the tools and strategies to find and validate problem-solution fit, setting the foundation for successful and sustainable ventures.
Teachers



Intended learning outcomes
- Describe analytical techniques for assessing market demand, such as market sizing, trend analysis, and customer segmentation.
- Recognize the limitations and biases associated with different validation techniques and strategies.
- Explain the role of customer feedback and market insights in driving iterative refinement processes to achieve a strong problem-solution fit.
- Analyze qualitative and quantitative data to identify patterns and insights relevant to market needs and preferences.
- Utilize analytical skills to assess market demand, competition, and scalability factors to evaluate solution viability.
- Adapt and pivot business ideas based on evolving market conditions and feedback, demonstrating resilience and flexibility in decision-making.
- Demonstrate creativity and adaptability in exploring alternative solutions to address identified market problems effectively.
- Synthesise insights from customer discovery to develop innovative solutions that address validated market need
- Demonstrate proficiency in analysing customer feedback to uncover underlying pain points and unmet needs.
About
This course delves into the critical aspects of acquiring talent and managing performance and rewards effectively. Explore recruitment strategies, selection processes, and talent sourcing techniques to attract and retain top talent. Dive into performance management frameworks, including goal setting, feedback mechanisms, and performance appraisal systems. Discover the principles of designing competitive compensation and rewards programs that align with organizational objectives and employee motivation. Through case studies and practical exercises, develop skills in talent acquisition planning, performance evaluation, and designing reward structures.This course equips you to drive organizational success through effective talent management and reward strategies.
Teachers



Intended learning outcomes
- Discuss the theories and practices of rewards management, including compensation structures, benefits administration, and incentive programs.
- Describe the principles and methods of talent acquisition, including recruitment channels, selection techniques, and legal considerations.
- Explain the components of performance management systems, including goal setting, performance appraisal methods, and feedback mechanisms.
- Design competitive and equitable rewards and recognition programs that align with organizational goals and enhance employee motivation.
- Implement effective talent acquisition strategies, including sourcing, screening, and selecting candidates.
- Facilitate performance management processes, including goal setting, performance reviews, and feedback sessions.
- Develop comprehensive talent acquisition strategies that address workforce planning needs and attract top talent.
- Execute performance management practices that align individual goals with organizational objectives, fostering a culture of continuous improvement.
- Evaluate the effectiveness of rewards and recognition programs through analysis of employee engagement, retention rates, and performance outcomes.
About
This course delves into the strategic processes and methodologies essential for effectively managing and optimizing workforce capabilities within organizations. Explore workforce planning methodologies, including forecasting future workforce needs and aligning them with business goals. Learn strategies for recruitment, selection, and onboarding to build a skilled and motivated workforce. Discover the importance of talent retention, performance management, and succession planning in maintaining organizational stability and growth. Through practical applications and case studies, develop skills in workforce analytics, strategic staffing, and workforce development. This course prepares you to strategically manage human capital to drive organizational success and sustainability.
Teachers



Intended learning outcomes
- Explain the role of workforce management in organizational strategy, including talent acquisition, development, and retention strategies.
- Discuss the legal and ethical considerations in workforce planning and management practices.
- Describe the principles and methodologies of workforce planning, including demand forecasting and supply analysis.
- Implement strategic workforce planning initiatives aligned with organizational goals and objectives.
- Conduct workforce analysis and forecasting to anticipate future talent needs and gaps.
- Utilize HR metrics and analytics to assess workforce performance, productivity, and effectiveness.
- Execute effective workforce management practices, including recruitment, selection, and development initiatives, to optimize organizational performance.
- Develop comprehensive workforce planning strategies that align with organizational objectives and support long-term sustainability.
- Evaluate the impact of workforce planning and management strategies on organizational success, using data-driven insights and metrics.
About
This course explores the principles and practices essential for enhancing organizational learning and employee development. Delve into learning theories, instructional design methodologies, and training evaluation techniques. Discover strategies for identifying training needs, designing effective learning programs, and delivering engaging training sessions. Explore the role of technology in learning delivery and the importance of continuous professional development. Through case studies and practical applications, develop skills in designing learning interventions, facilitating learning experiences, and assessing training effectiveness. This course prepares you to foster a culture of learning within organizations and equip employees with the knowledge and skills for continuous growth and success.
Teachers



Intended learning outcomes
- Explain instructional design principles and methodologies for developing effective training programs.
- Describe theories of adult learning and their application in organizational settings.
- Discuss the role of learning technologies and tools in facilitating employee development and organizational learning.
- Evaluate the effectiveness of learning and development initiatives through assessment and feedback mechanisms.
- Design effective learning interventions and training programs tailored to organizational needs and learning objectives.
- Facilitate engaging learning experiences using a variety of instructional methods and technologies.
- Assess the impact of learning interventions on organizational performance and employee growth, recommending improvements and adjustments as needed.
- Develop comprehensive learning and development strategies aligned with organizational goals and employee development needs.
- Implement effective training and development programs that enhance employee knowledge, skills, and performance.
About
This course explores the diverse landscape of digital marketing strategies that leverage paid channels for optimal reach and engagement. Dive into platforms like Google Ads, social media advertising, and display advertising. Learn to create targeted campaigns, optimize ad performance, and measure ROI effectively. Discover advanced techniques for audience segmentation, ad copywriting, and budget allocation to maximize campaign success. Through practical simulations and real-world case studies, develop skills in planning, executing, and analyzing paid digital marketing campaigns. This course equips you to harness the power of paid channels to drive traffic, conversions, and business growth in the digital age.
Teachers



Intended learning outcomes
- Explain the key principles and best practices for creating effective paid digital marketing campaigns, such as targeting, ad formats, and bidding strategies.
- Discuss the metrics and analytics used to measure the success of paid digital marketing campaigns, including CTR, CPC, conversion rates, and ROI.
- Describe the various paid digital marketing channels available, including Google Ads, social media advertising platforms, and display networks.
- Create targeted paid digital marketing campaigns across platforms such as Google Ads and social media, tailored to specific audience segments.
- Analyze campaign metrics and KPIs to evaluate effectiveness, make data-driven decisions, and optimize future digital marketing efforts.
- Optimize ad performance through A/B testing, keyword optimization, and bid management strategies to maximize ROI.
- Develop comprehensive paid digital marketing strategies aligned with business goals, integrating platforms and tactics to maximize reach and conversions.
- Evaluate the impact of paid digital marketing campaigns on business outcomes, leveraging analytics to optimize strategies and enhance.
- Execute effective campaign management practices, including budget allocation, scheduling, and performance monitoring, to achieve targeted marketing objectives.
About
This course explores effective strategies for leveraging organic channels to enhance online visibility and drive sustainable growth. Dive into search engine optimization (SEO), content marketing, and social media strategies tailored to organic growth. Learn to optimize websites for search engines, create compelling content, and engage audiences organically. Discover techniques for building brand authority, fostering community engagement, and generating leads without paid promotion. Through hands-on exercises and case studies, develop skills in planning, implementing, and measuring success through organic digital marketing channels. This course equips you to harness the power of organic strategies to achieve long-term digital marketing success.
Teachers



Intended learning outcomes
- Discuss the role of social media platforms in organic digital marketing, including best practices for engagement, content promotion, and community management.
- Explain the principles and strategies of content marketing, including content creation, distribution channels, and the role of SEO in content strategy.
- Describe the fundamentals of search engine optimization (SEO), including key concepts such as keywords, on-page optimization, and off-page factors.
- Create engaging and relevant content strategies for organic digital marketing channels, including blogs, videos, and social media posts.
- Utilize social media platforms to cultivate organic engagement, build brand awareness, and foster community interaction.
- Implement effective search engine optimization (SEO) techniques to improve website visibility and organic traffic.
- Evaluate the effectiveness of organic digital marketing efforts through analytics and metrics, adjusting strategies to optimize engagement, traffic, and conversion rates.
- Develop comprehensive organic digital marketing strategies aligned with business objectives, integrating SEO, content marketing, and social media tactics.
- Execute effective implementation of SEO strategies, including keyword research, on-page optimization, and backlink building, to improve search engine rankings.
About
This course explores the landscape of digital marketing channels and the metrics used to measure their effectiveness. Dive into various channels such as search engine marketing (SEM), social media marketing, email marketing, and display advertising. Learn to create integrated digital marketing strategies that align with business goals. Discover how to analyze and interpret key metrics including click-through rates (CTR), conversion rates, return on investment (ROI), and customer acquisition cost (CAC). Through hands-on projects and case studies, develop skills in optimizing campaigns, tracking performance, and making data-driven decisions to maximize marketing effectiveness.
Teachers



Intended learning outcomes
- Describe the various digital marketing channels available, including their features, advantages, and target audiences.
- Explain the key metrics used in digital marketing, such as CTR, conversion rate, ROI, and customer acquisition cost (CAC).
- Discuss the principles and best practices of digital marketing campaign management, including budgeting, targeting strategies, and ad creative optimization.
- Utilize digital marketing tools and platforms to create, manage, and optimize campaigns effectively.
- Implement digital marketing strategies across various channels such as SEM, social media, email, and display advertising.
- Analyze key digital marketing metrics to evaluate campaign performance, identify trends, and make data-driven decisions for optimization.
- Develop integrated digital marketing strategies that align with organizational goals and target audience preferences.
- Execute digital marketing campaigns across multiple channels, demonstrating proficiency in campaign setup, management, and optimization.
- Evaluate the effectiveness of digital marketing efforts through comprehensive analysis of metrics, providing insights and recommendations for continuous improvement.
About
This course explores the strategies and processes involved in bringing new products to market and optimizing their growth. Learn to identify market opportunities, conduct market research, and develop innovative products that meet customer needs. Delve into stages of product lifecycle management, from concept development to commercialization. Gain insights into pricing strategies, distribution channels, and marketing tactics to maximize product adoption and profitability. Through case studies and hands-on projects, acquire skills in product innovation, strategic planning, and fostering sustainable growth. This course prepares you to drive product success in dynamic market environments, ensuring sustainable business growth.
Teachers



Intended learning outcomes
- Explain the importance of market research, consumer behavior analysis, and competitive analysis in product development.
- Discuss various strategies for pricing, distribution, and promotion to drive product growth and market penetration.
- Describe the stages of product development lifecycle, from ideation and concept development to commercialization and launch.
- Evaluate product performance metrics and make data-driven decisions to optimize product positioning and growth strategies.
- Implement effective product development strategies, including market research, concept testing, and product iteration.
- Create innovative product concepts and prototypes that address market needs and opportunities.
- Develop comprehensive product development plans that integrate market insights, innovation strategies, and commercialization tactics.
- Evaluate product performance and iterate strategies based on market feedback and competitive analysis to sustain growth and profitability.
- Execute effective product launch strategies, including marketing campaigns and distribution plans, to maximize market adoption and growth.
About
This course immerses you in the creative and technical aspects of product design from concept to realization. Explore the principles of design thinking, prototype development, and user-centered design methodologies. Learn to identify user needs, conduct market research, and integrate feedback into iterative design processes. Delve into CAD tools, materials selection, and manufacturing considerations to create functional and innovative products. Through hands-on projects and collaborative exercises, develop skills in ideation, prototyping, and refining designs based on usability and market viability. This course prepares you to envision and bring to life products that meet both user expectations and business objectives.
Teachers



Intended learning outcomes
- Explain the importance of user research, market analysis, and feasibility studies in the product design process.
- Describe the principles and stages of product design, including ideation, concept development, and prototyping.
- Discuss various design methodologies and tools used in product development, such as CAD software, rapid prototyping techniques, and materials selection.
- Generate creative product concepts and prototypes that address user needs and market demands.
- Utilize design thinking methodologies and user-centered design principles to develop innovative and user-friendly product designs.
- Demonstrate proficiency in using CAD software and other design tools to create detailed product specifications and prototypes.
- Develop innovative product designs that integrate user feedback, market research, and functional requirements.
- Evaluate and refine product designs based on usability testing, feedback from stakeholders, and market viability assessments.
- Apply design principles and technical knowledge to prototype and iterate product designs effectively.
About
This course delves into essential methodologies for understanding user preferences and competitive landscapes in business contexts. Explore techniques for conducting qualitative and quantitative research to uncover user needs, behaviors, and preferences. Analyze competitive analysis frameworks to identify market trends, strengths, and weaknesses of competitors. Learn to leverage insights from user and competition research to inform strategic decision-making and product development. Through practical exercises and case studies, gain skills in data interpretation, market segmentation, and developing actionable insights. This course equips you to effectively navigate market dynamics, innovate products, and enhance competitive positioning.
Teachers



Intended learning outcomes
- Explain the importance of user research in understanding customer needs, behaviours, and preferences.
- Discuss competitive analysis frameworks and tools for evaluating market competition, including SWOT analysis, Porter's Five Forces, and market segmentation.
- Describe various qualitative and quantitative research methods used to gather user data and preferences.
- Utilize competitive analysis frameworks to assess market dynamics, identify competitors' strategies, and evaluate competitive strengths and weaknesses.
- Generate actionable recommendations based on user and competition research to inform strategic decision-making and product development.
- Conduct qualitative and quantitative research methods to gather user insights and preferences.
- Apply advanced research techniques to gather and analyze user data effectively, providing actionable insights for business decisions.
- Develop comprehensive competitive intelligence reports that identify market trends, assess competitors' strategies, and recommend strategic responses.
- Evaluate the impact of user and competition research on business strategy and propose adjustments to enhance competitive positioning.
About
This course provides a thorough exploration of techniques to enhance healthcare quality and performance. Learn the principles of benchmarking, including identifying best practices and setting performance standards. Delve into quality management frameworks and tools, such as Six Sigma and Lean, tailored for healthcare settings. Through practical exercises and real-world case studies, gain skills in measuring, analyzing, and improving healthcare processes. This course equips you with the knowledge to drive continuous improvement, ensure patient safety, and achieve excellence in healthcare delivery, ultimately leading to better patient outcomes and organizational efficiency.
Teachers



Intended learning outcomes
- Explain different quality management frameworks and their application in healthcare settings, such as Six Sigma and Lean methodologies.
- Describe the principles and importance of benchmarking in healthcare quality improvement.
- Discuss the role of quality indicators and metrics in monitoring and improving healthcare outcomes.
- Evaluate healthcare quality indicators and benchmarks to assess performance against industry standards.
- Develop strategies for implementing best practices identified through benchmarking to enhance patient care and safety.
- Apply quality management tools and techniques, such as Six Sigma and Lean methodologies, to streamline healthcare processes and improve efficiency.
- Implement effective benchmarking processes to identify and adopt best practices in healthcare delivery.
- Evaluate the impact of quality management strategies on healthcare outcomes and patient satisfaction.
- Lead quality improvement initiatives by applying advanced quality management tools and methodologies in healthcare settings.
About
This course explores the essential principles and practices for efficient management of materials and supplies in healthcare settings. Learn about inventory control, procurement strategies, and supply chain logistics tailored to healthcare needs. Delve into techniques for optimizing inventory levels, reducing waste, and ensuring timely availability of medical supplies. Through case studies and practical applications, gain skills in managing healthcare materials to support patient care, enhance operational efficiency, and minimize costs. This course equips you with the knowledge to effectively navigate the complexities of material management in healthcare, ensuring quality service delivery and patient satisfaction.
Teachers



Intended learning outcomes
- Describe the principles and concepts of material management in healthcare, including inventory control and supply chain logistics.
- Discuss regulatory requirements and guidelines related to inventory management and material handling in healthcare settings.
- Explain the importance of effective procurement strategies and vendor relationships in healthcare material management.
- Implement supply chain logistics strategies to improve the efficiency and reliability of material flow within healthcare facilities.
- Apply inventory management techniques specific to healthcare settings to optimize stock levels and reduce costs.
- Utilize procurement strategies and vendor management skills to ensure timely and cost-effective acquisition of medical supplies.
- Evaluate and optimize inventory systems and supply chain processes to enhance healthcare material availability and reduce waste.
- Design and implement comprehensive material management strategies that meet healthcare facility needs while ensuring cost-effectiveness and efficiency.
- Lead initiatives to improve material management practices within healthcare organizations, demonstrating effective decision-making and resource allocation.
About
This course delves into the critical intersection of ethics and law within healthcare practice. Explore ethical dilemmas, patient rights, and professional responsibilities in medical decision-making. Discuss legal frameworks, regulations, and healthcare policies that govern patient care and organizational practices. Through case studies and discussions, examine issues of confidentiality, informed consent, and end-of-life care. Gain insights into navigating ethical challenges and legal complexities to ensure patient welfare and uphold healthcare standards. This course equips you with the knowledge to navigate ethical dilemmas, legal requirements, and uphold ethical standards in healthcare delivery and decision-making.
Teachers



Intended learning outcomes
- Explain the legal frameworks and regulations governing healthcare practice, including patient rights, confidentiality, and informed consent.
- Discuss the ethical considerations in end-of-life care, patient-provider relationships, and healthcare decision-making.
- Describe the ethical principles and theories relevant to healthcare practice, such as autonomy, beneficence, non-maleficence, and justice.
- Evaluate healthcare policies and legal frameworks to ensure compliance and ethical practice in patient care and organizational policies.
- Demonstrate effective communication skills to facilitate informed consent and ethical decision-making processes with patients and their families.
- Apply ethical principles and theories to analyze and resolve complex ethical dilemmas in healthcare settings.
- Evaluate ethical dilemmas and propose solutions that uphold ethical standards, legal requirements, and patient rights in healthcare settings.
- Develop policies and procedures that promote ethical practice and compliance with legal standards in healthcare organizations.
- Apply ethical reasoning and legal principles to make informed decisions in complex healthcare scenarios, ensuring patient welfare and ethical integrity.
About
This course delves into the critical role of data analytics in optimizing supply chain operations. Explore methodologies and tools for collecting, analyzing, and interpreting supply chain data to enhance efficiency and decision-making. Learn to leverage analytics to forecast demand, manage inventory, and improve logistics. Discover how data-driven insights can mitigate risks, reduce costs, and enhance overall supply chain performance. Through practical applications and case studies, develop skills in using statistical models, optimization techniques, and data visualization tools to solve real-world supply chain challenges. This course equips you with the knowledge to drive strategic improvements and innovation within supply chain management.
Teachers



Intended learning outcomes
- Explain the fundamental principles and concepts of supply chain management and logistics.
- Describe different analytical techniques and tools used in supply chain analytics, such as optimization models, simulation, and predictive analytics.
- Discuss the role of data analytics in supply chain decision-making, including forecasting, inventory management, and risk mitigation.
- Utilize data analytics tools and software to analyze and interpret supply chain data effectively.
- Apply statistical techniques and optimization models to improve supply chain processes and decision-making.
- Create visualizations and reports to communicate supply chain insights and recommendations to stakeholders.
- Evaluate supply chain performance using analytics-based metrics and KPIs, recommending continuous improvement initiatives.
- Develop and implement data-driven supply chain strategies that optimize efficiency and reduce costs.
- Apply supply chain analytics techniques to identify and solve complex supply chain problems and challenges.
About
This course offers a comprehensive exploration of creating and overseeing effective distribution networks. Learn the principles of channel design, including selecting and managing intermediaries, logistics coordination, and performance evaluation. Delve into strategies for optimizing distribution efficiency and ensuring seamless product flow from producers to consumers. Through practical exercises and case studies, gain insights into managing relationships with channel partners, resolving conflicts, and adapting to market changes. This course equips you with the skills and knowledge to design robust distribution channels that enhance customer satisfaction and drive business success.
Teachers



Intended learning outcomes
- Identify key components and functions of distribution channels and their roles in the supply chain.
- Explain the principles of channel design and the factors influencing channel selection and management.
- Compare different distribution channel strategies and their impacts on market reach and customer satisfaction.
- Analyze distribution channel structures and evaluate their effectiveness in various market contexts.
- Design optimal distribution networks by applying principles of channel design and logistics coordination to real-world scenarios.
- Manage relationships with channel partners, using conflict resolution and performance evaluation techniques to ensure seamless product flow and customer satisfaction.
- Assess the performance of distribution channels and make data-driven adjustments to enhance operational effectiveness and customer satisfaction.
- Implement effective logistics and coordination practices to optimize product flow and distribution efficiency.
- Develop comprehensive distribution channel strategies that align with business objectives and market demands.
About
This course is designed to explore how Artificial Intelligence (AI) and Machine Learning (ML) can revolutionize business practices. This course provides a comprehensive overview of leveraging AI and ML to drive innovation and efficiency in various business functions.Key topics include AI and ML fundamentals, data analytics, automation, and predictive modeling. Students will learn how to implement AI/ML solutions in areas such as marketing, finance, operations, and customer service. Through case studies of leading organizations and interactive sessions, students will gain insights into successful AI/ML strategies and applications. Hands-on projects and collaboration with industry experts will further enhance their ability to design and deploy AI/ML solutions.By the end of this course, MBA students will be equipped with the knowledge and skills to integrate AI and ML into their business strategies, driving growth, efficiency, and innovation in their organizations.
Teachers



Intended learning outcomes
- Explore emerging trends and technologies in AI/ML, such as edge computing, federated learning, and AI-driven automation, and their potential applications and implications for business innovation and efficiency.
- Explain the concepts and techniques of advanced data analytics, including predictive modeling, pattern recognition, and anomaly detection, in the context of business intelligence and insights generation.
- Identify common business problems and use cases where AI/ML technologies have demonstrated significant value and impact, such as customer segmentation, fraud detection, demand forecasting, and personalized recommendations.
- Design and implement end-to-end AI/ML solutions, including data ingestion, preprocessing, model training, evaluation, and deployment, within business environments and infrastructures.
- Evaluate model performance and optimize parameters through techniques such as cross-validation, hyper parameter tuning, and ensemble learning to achieve desired business outcomes and objectives.
- Apply statistical methods and hypothesis testing to validate findings and conclusions drawn from data analysis and modeling exercises.
- Communicate data-driven insights effectively to stakeholders through reports, presentations, and visualization tools to facilitate informed decision-making and drive organizational growth.
- Foster a culture of innovation and continuous improvement by championing the adoption of AI/ML solutions, fostering cross-functional collaboration, and promoting knowledge sharing and best practices.
- Utilize domain knowledge and data-driven insights to identify suitable AI/ML approaches and algorithms for solving diverse business problems effectively.
About
This course offers a practical and theoretical foundation of machine learning, enabling future business leaders to leverage machine learning for data-driven insights and competitive advantage. Key topics include supervised and unsupervised learning, predictive analytics, and model evaluation. Students will explore how machine learning algorithms can be applied to solve complex business problems across various domains such as marketing, finance, and operations. Through case studies and hands-on projects, students will gain practical experience in building and implementing machine learning models. Interactive sessions with industry experts provide additional insights into best practices and real-world applications. By the end of this course, students will be equipped with the skills and knowledge to integrate machine learning into business strategies, enhancing their ability to make informed, data-driven decisions.
Teachers



Intended learning outcomes
- Recognize the importance of data quality, data preprocessing, and feature engineering in preparing datasets for machine learning analysis.
- Identify common evaluation metrics and techniques used to assess the performance and generalization ability of machine learning models, such as confusion matrices, ROC curves, and cross-validation.
- Understand the theoretical foundations and working principles of popular machine learning algorithms, including linear regression, logistic regression, decision trees, k-nearest neighbors, and neural networks.
- Tune model hyperparameters, select appropriate features, and optimize model performance through iterative experimentation and validation.
- Implement machine learning algorithms using programming languages and libraries such as Python, scikit-learn, and TensorFlow to develop predictive models for decision support systems.
- Continuously monitor model performance and iterate on model improvements to adapt to changing business requirements and data dynamics.
- Conduct exploratory data analysis (EDA) and data preprocessing techniques to understand the characteristics and patterns within complex datasets.
- Implement a variety of machine learning algorithms, including regression, classification, clustering, and ensemble methods, to develop predictive models that enhance strategic decision-making.
- Evaluate the effectiveness and performance of machine learning models in solving real-world business problems and improving decision processes.
About
This course explores the transformative world of Artificial Intelligence (AI) and Machine Learning (ML) in this comprehensive MBA specialization course. It provides an in-depth understanding of how AI and ML are reshaping industries and driving innovation. Key topics include the fundamentals of AI and ML, data-driven decision-making, and the integration of AI/ML in business functions such as marketing, finance, and operations. Students will examine case studies of leading organizations, gaining insights into best practices and common pitfalls. The course also covers emerging trends and ethical considerations, preparing students to navigate AI-driven business environments. Hands-on projects and interactive sessions with industry experts offer practical experience, enhancing students’ ability to apply AI and ML concepts in a business context. By the end of this course, students will be equipped to harness AI and ML for innovation, efficiency, and sustainable growth in their organizations.
Teachers



Intended learning outcomes
- Define reinforcement learning and its components, including agents, environments, states, actions, and rewards.
- Describe the architecture and workings of artificial neural networks (ANNs) and deep neural networks (DNNs), including feedforward and convolutional neural networks.
- Understand the principles and objectives of semi-supervised learning and its distinction from supervised and unsupervised learning.
- Evaluate and fine-tune reinforcement learning models through simulation, experimentation, and performance analysis in diverse application domains.
- Fine-tune pre-trained deep learning models and architectures to achieve better performance and adaptability to specific datasets and tasks.
- Interpret and communicate the results of semi-supervised learning experiments, including model performance metrics and insights gained from unlabeled data.
- Identify the core concepts and components of reinforcement learning, including agents, environments, actions, and rewards.
- Explore the fundamental principles and architectures of deep learning models, including artificial neural networks and deep neural networks.
- Analyze the principles and techniques of semi-supervised learning to recognize its potential applications and advantages.
About
This module provides students with advanced methods and frameworks for
understanding customer needs, and for translating those needs into a
program of research and product development that can be used to create a successful new product or service. It equips students with skills to generate new product hypotheses, to research the potential of a new product or entrepreneurial venture, and to adjust the product offering to fit the needs of customers. This module instills the all-important distinction between a ‘bright idea’ and a ‘business opportunity’ in new product creation.
Using disciplined methods of customer and market analysis, students will gain advanced abilities in defining the core customers for a new product or entrepreneurial venture.
Students will study the complex combination of factors that influence customers to adopt a new product or service. They will gain a comprehensive understanding of what makes entrepreneurial selling unique, and why it is valuable to integrate key aspects of selling and marketing activities in a new venture. Students will learn how to select potential customers through data collection, including customer interviews, and students will learn how to analyse that data to refine a product offering.
Teachers
Intended learning outcomes
- Theories of product creation for business applications.
- Business new product inspiration and creation.
- Key strategies for hypothesis-driven product creation and revision.
- Diverse scholarly views on how new products should be developed and introduced to the market.
- Select topics for the advanced management of product inspiration, market testing, and product revision.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing in discussions about product inspiration and creation.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on a new product.
- Apply an in-depth domain-specific knowledge and understanding to business creativity and innovation.
- Creatively apply the theories learned in the module to develop critical and original solutions for a new product.
- Apply a professional and scholarly approach to research problems related to new product formulation and introduction.
- Create synthetic contextualised discussions of key issues related to new product creation.
- Demonstrate self-direction in research and originality in solutions developed.
- Efficiently manage interdisciplinary issues that arise in the creation and definition of new products.
- Act autonomously in identifying research problems and solutions related to business product innovation and creation.
- Solve problems and be prepared to take leadership decisions related to business creativity and innovation.
About
This module provides students with advanced methods needed to understand how a product will fit into a competitive market, and how to introduce the product into that market. This includes advanced research on the receptiveness of a market to the new product, as well as strategies for defining and finding the market that will be most receptive to the product. Students consider product introductions with the goal of what Marc Andreesen called ‘product/market fit’ - a ‘good market with a product that can satisfy that market.’
The module trains students to reflect upon and analyse a company’s go-to- market strategy, and it provides students with sophisticated methods of calculating customer acquisition cost, determining customer break-even, and calculating customer lifetime value.
Teachers
Intended learning outcomes
- Diverse scholarly views on product launches in relation to product/market fit.
- Topics for the advanced management of product introductions.
- Key implementation strategies for introducing a product to a market.
- Product/market fit theories to product launches and implementation strategies.
- Business strategies for product introductions.
- Apply an in-depth domain-specific knowledge and understanding to product/market fit.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of calibrating the relationship between a product and a market.
- Employ the standard modern conventions for the presentation of scholarly work on product launches.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on product/market fit.
- Act autonomously in identifying research problems and solutions related for product introductions.
- Create synthetic contextualised discussions of key issues related to product launches and post-launch market fit.
- Apply a professional and scholarly approach to research problems pertaining to product/market fit.
- Demonstrate self-direction in research and originality in solutions developed.
- Solve problems and be prepared to take leadership decisions related to new product introductions.
- Efficiently manage interdisciplinary issues that arise in determining how to assess new product implementations.
About
This module examines iterative product development as a method for improving customer adoption and retention. Students will gain a mastery of iterative product development as a strategy for (a) transforming market research into potential solutions, (b) testing hypotheses about product improvements, and (c) gaining validation for product adjustments.
Students will gain a comprehensive understanding of the concept of a minimum viable product, how to test the market in the early stages of product adoption, and the benefits and weaknesses of incremental product improvements. Students will gain an advanced understanding of concepts related to customer segmentation, cohort analysis, and churn in order to learn from market responses to product changes, increase customer retention, and expand customer adoption.
Teachers
Intended learning outcomes
- Theories for product measurement and adoption.
- Diverse scholarly views on the role of measurement in product adoption.
- Select topics for the advanced management of product adoption and post-adoption optimisation.
- Customer segmentation and cohort analysis.
- Key strategies for reducing churn and increasing user adoption.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on measurement and product adoption.
- Apply an in-depth domain-specific knowledge and understanding to customer segmentation and cohort retention analysis.
- Creatively apply the theories learned in the module to develop critical and original solutions for product measurement in order to drive adoption outcomes.
- Demonstrate self-direction in research and originality in solutions related to increasing and maintaining product adoption while avoiding churn.
- Apply a professional and scholarly approach to research problems of measurement and data-driven decision-making pertaining to product adoption.
- Efficiently manage interdisciplinary issues that arise in connection product improvements and product adoption.
- Create synthetic contextualised discussions of key issues related to product adoption.
- Act autonomously in identifying research problems and solutions related to product adoption.
- Solve problems and be prepared to take leadership decisions related to measuring product adoption.
About
This module has been designed to foster a strong safety culture by disseminating safe behaviours throughout the organisation, with a strong focus on leadership development at all levels.
Teachers
Intended learning outcomes
- Diverse scholarly views on the role of leadership in health and safety.
- Select topics for the advanced management of health and safety
- Key strategies for promoting health and safety in a work environment.
- Apply an in-depth domain-specific knowledge and understanding to health and safety leadership.
- Understand and demonstrate the importance of leadership for improving health and safety performance.
- Create synthetic contextualised discussions of key issues related to health and safety.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on health and safety.
- Critically assess the relevance of quality management and various quality management models.
- Creatively apply the theories learned in the module to develop critical and original solutions for health and safety leadership
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Understand and demonstrate the impact of leadership on team cohesion and functioning in the health and safety sector.
About
The purpose of this module is to give learners an opportunity to integrate all the knowledge from their programme of learning by developing a project in which they plan and implement a new product, service or process. Learners need to take a full and active role in all aspects of the project, and the selection of an appropriate management issue is crucial to success. Learners will cover a full range of management activities and roles, including resource and people management and implementation of change. The result needs to be a substantial report in a style appropriate for consideration by senior management
Teachers
Intended learning outcomes
- Diverse scholarly views on the role of software in product management.
- Communication planning and management within a project context.
- Select topics in advanced product management.
- Project Management strategies and practices in a global context.
- Creatively apply the theories learned in the module to develop critical and original solutions for product management in order to drive adoption outcomes.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on product management.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Develop project specifications, schedule, controls, and evaluation of project work, using various project management tools.
- Act autonomously in identifying research problems and solutions related to product management.
- Create synthetic contextualised discussions of key issues related to product management.
- Implement and evaluate the outcomes of a project.
- Apply an in-depth domain-specific knowledge and understanding to product management.
- Efficiently manage interdisciplinary issues that arise in connection product management.
About
This module provides an introduction to the main areas of Enterprise Risk Management. This module also covers Risk Management processes and strategies. Numerous case studies from various business sectors will illustrate the increasing importance of Enterprise Risk Management.
Teachers
Intended learning outcomes
- Diverse scholarly views on the role of risk management
- Key methods to manage and organisation’s risk, including risk optimisation, and management of market risk, credit risk, operational and other risks.
- Select topics for the advanced management of various risks in a business setting.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on risk management.
- Demonstrate an understanding of the relevance of ERM to stakeholders.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Apply a professional and scholarly approach to research problems of measurement and data-driven decision-making pertaining to risk management.
- Create synthetic contextualised discussions of key issues related to risk management.
- Act autonomously in identifying research problems and solutions related to risk management
- Describe and show an understanding of different risk categories.
- Demonstrate an understanding of risk management frameworks for financial organisations in different regulatory environments.
About
This course synthesises the multifaceted skills, knowledge, and strategic
thinking acquired throughout the program, challenging participants to
apply their expertise to real-world business challenges. Under the
guidance of seasoned mentors and industry professionals, students will
undertake a comprehensive, hands-on project that requires them to
integrate concepts from various disciplines within the curriculum. From
strategic planning and financial analysis to organisational leadership and
ethical decision-making, the Capstone Project serves as a comprehensive
test of the holistic business acumen developed during the program.
Participants will not only hone their problem-solving abilities but will also
demonstrate their ability to develop actionable solutions that align with
contemporary business challenges. As a capstone experience, this course
not only underscores the depth of knowledge gained during the program
but also empowers participants to showcase their readiness to contribute
meaningfully to the complex landscape of modern business. Elevate your
strategic thinking, analytical prowess, and leadership skills as you embark
on this transformative journey toward earning your degree
Teachers



Intended learning outcomes
- Topics for the advanced management of a contemporary business problem.
- Key strategies for applying creativity and leadership to a contemporary business problem.
- Diverse scholarly views on a contemporary business problem.
- Theories for business applications in the pursuit of a solution to a contemporary business problem.
- Critical knowledge of a contemporary business problem.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of a contemporary business problem.
- Autonomously gather material and organise it into a coherent, comprehensive presentation.
- Apply an in-depth domain-specific knowledge and understanding to a contemporary business problem
- f) Solve problems and be prepared to take leadership decisions related to a contemporary business problem.
- a) Create synthetic contextualised discussions of key issues related to a contemporary business problem.
- d)Demonstrate self-direction in research and originality in solutions developed.
- b)Apply a professional and scholarly approach to research problems pertaining to a contemporary business problem.
- c) Efficiently manage interdisciplinary issues that arise in connection with analysing and proposing a solution to a contemporary business problem.
- e)Act autonomously in identifying research problems and solutions related to a contemporary business problem; act as a professional team member where appropriate.
About
In this dynamic and interactive course, participants will embark on a transformative journey to enhance their soft skills, crucial for personal and professional success in today's dynamic work environment. The course delves into the multifaceted realm of interpersonal skills, communication, teamwork, and adaptability. Through a combination of theoretical insights, practical exercises, and real-world scenarios, participants will develop a profound understanding of the significance of soft skills in fostering effective collaboration and navigating the complexities of the modern workplace.
Moreover, the Soft Skills course goes beyond traditional instruction, providing a comprehensive framework for self-discovery and improvement. Participants will engage in activities that not only refine their communication style but also empower them to cultivate emotional intelligence, resilience, and leadership acumen. By the end of the course, participants will have honed the essential soft skills needed to thrive in diverse professional settings, empowering them to build lasting relationships, contribute meaningfully to team dynamics, and stand out as adaptable and emotionally intelligent leaders in their respective fields
Teachers



Intended learning outcomes
- Analyse different communication styles and their impact on team dynamics and organisational performance.
- Recognise the fundamental components of soft skills, including communication, teamwork, and emotional intelligence.
- Explain the role of interpersonal skills in leadership, conflict resolution, and collaboration within a business setting.
- Communicate complex business ideas clearly and persuasively, tailoring the message for different stakeholders and organisational levels.
- Exercise judgement in adapting communication styles to diverse business contexts, such as team meetings, presentations, and negotiations.
- Understand how to apply active listening techniques in professional interactions, ensuring effective communication and empathy.
- Foster an environment of continuous personal and professional growth, promoting adaptability and resilience within the organisation.
- Ensure consistent application of emotional intelligence in decision-making, enhancing team performance and conflict resolution.
- Demonstrate effective leadership through fostering collaboration and positive work culture, ensuring team cohesion and shared goals.
About
This comprehensive course is designed to equip participants with the knowledge, strategies, and confidence needed to navigate the intricacies of job interviews successfully. Participants will gain a deep understanding of the interview process, learning how to effectively communicate their strengths, experiences, and accomplishments to make a lasting impression on prospective employers.
Throughout the course, participants will engage in mock interviews, receive personalised feedback, and learn proven techniques for handling common interview questions. From mastering body language and crafting compelling narratives to addressing potential challenges, the course provides a holistic approach to interview success. Whether you are a recent graduate entering the job market or a seasoned professional looking to advance in your career, this course will empower you with the tools to stand out in interviews and secure the job opportunities you aspire to. It will elevate the interview performance and unlock career potential with this invaluable skill-building experience.
Teachers



Intended learning outcomes
- Analyse employer expectations during the interview process, focusing on industry-specific competencies and soft skills.
- Identify key elements of successful interviews, including research, communication, and presentation techniques.
- Explain common interview formats and strategies, such as behavioural, situational, and panel interviews.
- Use judgement in tailoring interview strategies by analysing job descriptions and organisational culture to prepare targeted responses that showcase relevant skills and experience.
- Understand how to structure responses to common interview questions, demonstrating clarity, relevance, and alignment with the role's requirements.
- Communicate effectively in simulated interview settings, applying advanced techniques such as non-verbal cues, confident speech, and professional demeanour to leave a positive impression on interviewers.
- Demonstrate confidence and adaptability during interviews, showcasing an ability to handle complex questions and unpredictable scenarios.
- Ensure a professional and polished presentation throughout the interview process, from preparation to follow-up, enhancing personal branding.
- Foster self-awareness and continuous improvement, using feedback and reflection to refine interview techniques and career growth strategies.
About
The Digital Action Programme for Business Administration provides a capstone course in which students deepen and apply their learning through a 'Digital Action Programme' (DAP). In the DAP, students are grouped into cohorts (typically five students) and must work both individually and together on a specific, real, contemporary business consultancy problem related to their specialisation (Data Analytics; Marketing; Finance; International Business; DEI), normally proposed by a cooperating organisation (corporation or non-profit), which results in a comprehensive solution proposal.
This provides students with a real-world business consultancy engagement, and the opportunity to produce, both individually and as a team, a substantial piece of relevant, scholarly, and actionable research, to be presented directly to stakeholders in the cooperating organisation.
Over the course of the DAP, students fulfil the learning objectives: each student demonstrates their comprehensive knowledge and understanding of key business processes; each student uses multidisciplinary approaches to perform critical analyses of real business issues in situations of uncertainty and incomplete information in order to develop an actionable solution; each student practises teamwork, exercises their leadership skills, and reflects on their own performance and the performance of their cohort; and each student communicates to members of their cohort, the cooperating organisation, and faculty members from Woolf. Students are required to demonstrate autonomy, individual scholarly acumen, self-reflection in their engagement with peers, role adaptability within their cohort, and teamwork while engaged in the DAP. The goal of the DAP is (1) to fulfil the learning objectives and (2) to produce a project portfolio containing an analysis of the business problem and the proposed solution.
DAP Roles and Responsibilities
(a)Individual students
Students are required to take responsibility for their own work, they must act autonomously on the basis of their prior learning and experience, and they must individually generate key research results that contribute to the DAP.
Each student must individually contribute through assignment submissions, which are marked on their individual merits. The final mark on the course (as described below) consists of 50% for the individual research submissions, and 50% for the cohort's final project taken as a whole. The final project contains individual contributions, but requires teamwork, and is graded as a whole in terms of its fulfilment of the learning objectives.
Thus 15 ECTS worth of the course is based on individual work, and 15 ECTS is based on the collaborative work of the Cohort.
(b)Cohorts
Cohorts are groups of about 5 students that are assigned to address a single business problem, on which they commit to working both individually and as a team. All cohorts must agree to a cohort charter, which outlines the roles and responsibilities of the team. The cohort charter must include the following topics: timeliness; comprehensive designation of areas of responsibility, including gathering meeting agenda items, chairing meetings, meeting note-taking, and being the point of contact for the cooperating organisation; a schedule of rotating leadership positions across the modules units, and a commitment to professional teamwork that prioritises the goal of the DAP.
(c)Tutors
All cohorts are assigned a Woolf tutor to facilitate three cohort tutorials for each unit, and all cohorts are assigned a designated contact person from a cooperating organisation.
The role of the tutor in cohort tutorials is to ensure that students are achieving the learning objectives and that the cohort is on course with their program roadmap. As the DAP progresses, students are expected to increase their management over the tutorial meetings, including setting the meeting agenda.
(d)Cooperating organisations
Cooperating organisations must register and be verified with Woolf, provide an initial portfolio of basic information on the company, provide a designated contact person, and agree to the standard 'cooperating organisation framework' –which commits them to attend a minimum number of meetings with a cohort, and they are encouraged to provide students with access to the executive members of their organisation.
In cases where relations with a cooperating organisation become untenable for any reason, and the cohort is unable to continue with the relationship, then cohorts will be provided with the choice of (a) continuing their DAP without further input from the cooperating organisation, (b) switching to a new cooperating organisation, or (c) selecting a contemporary business problem on the basis of publicly available information and in agreement with their tutor.
DAP Timeline of Assignments
Each unit of the module normally requires about 75 hours of work from each member of the cohort. Individuals must complete their projects on schedule –neither early nor late –and in response to the requirements of their project; cohorts have the opportunity to adjust the amount of time dedicated to each unit.
The cohort meetings are an opportunity for the instructor to check in on the team's progress; they are a key checkpoint for individual submissions, and they provide milestones in the progress of the DAP. Before every cohort meeting, each student is required to submit a status report on individual and team performance.
At the end of the DAP, every cohort submits a Final Report, Final Presentation, and Final Reflection on their experience.
The Final Report consists of the following components:
Title, abstract, and table of contents
Industry and competition report
Report on the cooperating organisation
Report on the business problem
Report on the potential solutions analysing their merits and weakness
Recommended solution with an implementation plan
Full financial model
Bibliography
Items 2-7 (which may be adjusted in coordination with the cohort tutor), each have a Directly Responsible Individual (the DRI), who undertakes all the research for the section of the Final Report. Each DRI must elicit feedback and review from other members of the cohort, who must contribute feedback to every other section of the report.
The Final Presentation is typically a slide deck between 20 and 40 slides, and it is a fully collaborative project.
The Final Reflection is a reflective analysis on the DAP experience, and it must contain an individual report from each member and a joint concluding statement.
The course concludes with each member providing a peer review of their cohort peers, including strengths and areas of improvement.
The timeline of the course assignments is set by the cohort at the start, and adjusted in consultation with the tutor as the DAP progresses. The outline of assignment submissions is as follows:
Unit 1
●Standard cohort charter discussed, revised, and agreed
●Project timeline with designated areas of responsibility
Unit 2-3
●Draft title and abstract for the final report
●Industry information gathering
●Draft report on the cooperating organisation
●Draft report on the industry landscape
Unit 4-5
●Problem and opportunity diagnose
●Creative generation of varied potential solutions
Unit 6
●Evaluation of potential solutions
●Preliminary financial models of potential solutions
Unit 7-8
●Recommended solution
●Implementation plan
Unit 9-10
●Final Report
●Final Presentation
●Final Reflection and cohort debrief
●Peer evaluation
Teachers



Intended learning outcomes
About
This module encompasses statistics, decision analysis, and simulation modelling.
Throughout the module, students will strengthen their capacity to lead individuals, teams, and organisations in processes that generate data-driven solutions to problems, data-driven insights into customer behaviour, and data-driven decision-making. This module provides the foundations of probability and statistics required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty, with incomplete information, and in both structured and unstructured settings. Theoretical topics include decision trees, hypothesis testing, multiple regression, Monte Carlo simulation, and sampling and estimation.
Teachers



Intended learning outcomes
- Theories for business applications in the domain of evidence based decision-making.
- A critical understanding of the foundations of probability and statistics to the extent required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty.
- Key theoretical topics pertaining to evidence-based decisionmaking such as decision trees, hypothesis testing, multiple regression, and sampling.
- Relevant topics for the advanced management of data-driven insights into customer segments.
- Diverse scholarly views on evidence-based decision-making in a business context.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of evidence-based decision-making in a business context.
- Autonomously gather evidence and organise it into a coherent, comprehensive presentation advocating an evidence-based decision.
- Apply in-depth domain-specific knowledge and understanding to evidence-based decision-making in a business context.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Efficiently manage interdisciplinary and diverse kinds of evidence that inform decision-making.
- Apply a professional and scholarly approach to data and evidence as factors in decision-making.
- Solve problems and be prepared to take leadership decisions related to evidence-based decision-making in a business context.
- Act autonomously in identifying research problems and solutions related to evidence-based decision-making in a business context.
- Create synthetic contextualised discussions of key issues related to evidence-based decision-making.
- Demonstrate self-direction in gathering and using evidence and data for decision-making.
About
This module introduces students to one of the world’s most widely used and in-demand programming languages and its specific applications to business analytics. Python is used in a wide range of fields, including web development, data science, fin-tech, health care, and more. With Python, business leaders can scrape online sources to determine consumer sentiment, automate tasks, run advanced models, and export code across different applications. Throughout the module will develop the following skills: Apply programmatic logic to complex business problems in areas such as finance, operations, and marketing; Use technical knowledge to lead and manage teams in today’s evolving digital economy; Leverage state-of-the-art tools and powerful, open-source Python libraries to clean, analyse and visualise data.
Teachers



Intended learning outcomes
- Specialised knowledge of data processing with Python language.
- Analyse and assess various scholarly views on the practical applications of machine learning models in data analytics.
- A critical understanding of various Python libraries and their applicability to real-world business situations.
- Predict the results of various Python codes.
- Analyse and read Python data using datasets.
- Write Python code to read, write, filter, merge, summarise, and graph a given dataset.
- Independently build data models.
- Describe and perform Python data acquisition and analysis techniques.
- Communicate effectively the purpose, methodology, and results of an analysis involving Python to a non-technical business audience.
- Derive hidden information from voluminous and complex data.
- Analyse data from a variety of industries and uncover business insights.
About
The objective of this module is to provide students the basic data analysis and modelling concepts and methodologies using probability theory. Basic statistics concepts and probability concepts will be covered. Fundamental data analysis and hypothesis techniques will be covered. Further data modelling methodologies such as Hidden Markov Models and Bayesian networks will be introduced. Students successfully completing this module will have gained a solid understanding of probabilistic data modelling, interpretation, and analysis and thus have formed an important basis to solve practical statistics and data analysis-related problems arising in real-world business situations. The techniques discussed are applied in all functional areas within business organisations including accounting, finance, human resource management, marketing, operations, and strategic planning.
Teachers



Intended learning outcomes
- Select topics in acquiring and cleaning data.
- Researching, evaluating, and selecting appropriate mathematical and statistical tools for data analytics problems.
- A specialised knowledge of various data warehousing architectures, processes, and operations.
- A critical understanding of varying scholarly perspectives on measuring fit and performance of models appropriately.
- Execute statistical analyses with professional statistical software.
- Construct complex statistical models.
- Integrate data from disparate sources.
- Build and assess data-based models.
- Describe the business intelligence methodology and concepts and relate them to decision support.
- Identify and interpret the data relevance, reliability, and validity from multiple sources.
- Proficient in solving business problems by identifying data gaps and synthesising data to deliver quality output.
- Research and utilise validated data to logically construct reports based on needs.
- Apply data science concepts and methods to solve problems in real-world business contexts and communicate these solutions effectively.
- Use data visualisation tools to analyse data and produce reports.
- Demonstrate proficiency with statistical analysis of data.
About
Financial reports contain important information about a company's past, present, and future. The ability to read these reports provides valuable insights into an organisation's strengths and shortcomings.
This module is designed to prepare students to interpret and analyse financial statements for tasks such as credit and security analyses, lending and investment decisions, and other decisions that rely on financial data. Throughout the module, students will explore in greater depth financial reporting from the perspective of financial statement users. Students will develop a sufficient understanding of the concepts and recording procedures and therefore will be able to interpret various disclosures in an informed manner. Additionally, students will learn how to compare companies financially, understand cash flow, and grasp basic profitability issues and risk analysis concepts.
Teachers



Intended learning outcomes
- A critical knowledge of ratios used to compare a firm to its competitors and to evaluate changes in ratios over time.
- Select topics in forecasting future earnings and anticipating market reactions.
- Specialised knowledge of tactics for recognizing accounting errors, either intentional or unintentional, and their impact on reported income and the book value of equity
- Research and develop an analysis of an organisation’s performance and risk.
- Use ratios to help forecast and make financial predictions.
- Read and critically evaluate financial analyst reports on publicly listed companies.
- Make predictions related to the stock market’s response to quarterly earnings.
- Apply analytical tools and concepts in competitor analysis, credit and investment decisions, and business valuation.
- Interpret various disclosures in an informed manner.
- Critically analyse a business’s finances.
- Develop a sufficient understanding of the concepts and recording procedures.
- Understand and evaluate major valuation models.
- Critically compare companies financially, understand cash flow, and grasp basic profitability issues and risk analysis concepts.
- Understand and interpret assets and liabilities reported on a balance sheet.
About
Throughout this module, students will develop the analytical tools necessary to understand crisis prevention and management, and risk management. The properties and characteristics of risk management techniques will be analysed and related to corporate and sovereign default risk, hedging and trading strategies, regulation, and assessing financial stability and systemic risk. Emphasis will be put on applying these techniques to problems emerging in the marketplace.
Additionally, this module addresses the ability of different risk management approaches to account for large market shocks. Students will study the effect of leverage, through borrowing or through the structuring of assets, in amplifying shocks and increasing risk, and the role of capital in mitigating them. The information learned in this module will help business leaders understand their role in regulatory compliance and participate constructively in these interactions.
Teachers



Intended learning outcomes
- e) Evaluate legal risk and reputational risk as factors in risk management.
- d) Select topics in corporate governance, accounting, and disclosure that prioritize the health of financial markets
- b) Implementation of M&A-related risk management with respect to capital structure and interest rate risk.
- a) A critical understanding of key funding issues including how much debt a company should have, how different types of debt compare, and liability management techniques.
- c) Commodity risk management, including derivatives available and hedging techniques.
- c) Perform currency risk management, including assessing the different types of currency risk for a given organization, evaluating different hedging techniques, and managing emerging market currency risk.
- a) Identify and measure risk exposures using factor models, Monte Carlo simulations, and Value at Risk.
- d) Assess interest rate risk management, including the risks of different types of liabilities, how liabilities are optimised with respect to cost versus risk, derivatives available, hedging, and pre hedging techniques.
- b) Develop effective risk management policies which address key roles and responsibilities, different approaches, advisable policy limits, and performance assessments.
- e) Critically assess counterparty risk management, including derivatives available, and hedging techniques.
- c) Perform critical evaluations of risk factors and evaluate risk management approaches on the basis of incomplete information in a fastchanging business context.
- a) Communicate the importance of risk management, key objectives, concerns, and challenges to technical and nontechnical audiences.
- b) Research solutions to real-world risk management problems across a variety of risk factors (currency risk, commodity risk, etc.).
About
Throughout this module, students will learn the basic concepts of needs analysis, investment policy, asset allocation, product selection, portfolio monitoring and rebalancing. Students will assess the various types of institutional investors, including pension funds and insurance companies and develop skills related to the client management life cycle and portfolio management as a process. The module will address the basic concepts, principles, and the major styles of investing in alternative assets. Additionally, students will learn about the impact of digitization on investment strategies and the issues related to performance measurement, transaction costs and liquidity risk, margin requirements, risk management, and portfolio construction. Other topics addressed in the module include quantitative investment strategies used by active traders and methodologies to analyse them. Through the use of case studies, students will learn to use real data to back-test or evaluate several of the most successful trading strategies used by active investment managers. As a result, students will learn to read and analyse academic research articles in search of profitable and implementable trading ideas.
Teachers



Intended learning outcomes
- A critical knowledge of common strategies in quantitative investing.
- Principles of bond market and yield used to critically assess forecasting.
- The ability to identify, assess, and analyse common investment pitfalls through overleveraging and underappreciating.
- Evaluate the different theoretical foundations of active investment management.
- Use statistical packages and other programming tools to make investments, measure performance, and change strategic direction in response to rapidly changing market conditions.
- Make informed stock selections by measuring risk and applying risk management and analytical theory to choices.
- Utilise financial and economic databases for real-world applications.
- Make informed market decisions with a deep understanding of capital markets and major investable asset classes.
- Analyse the performance of investment products over time by using large data sets and statistical packages for measuring performance.
- Communicate effectively to technical and nontechnical audiences about underlying empirical evidence that informs investment decisions.
- Critically assess challenges of leveraging and shorting.
- Apply modern risk management and analytical theory to stock selection.
- Perform the functions of a quantitative research analyst at an investment firm with autonomy.
About
This module explores the international business environment in which organisations operate. Throughout the module, students will examine the structure and features of international markets, how organisations engage with these markets, and how they respond to their complexities. Students are introduced to useful theoretical and analytical frameworks that are crucial to understanding the opportunities and risks derived from the political, economic, social, technological, and institutional environment of countries.
The module also addresses aspects of global institutions, such as the World Trade organisation (WTO) and the International Monetary Fund (IMF), which set global rules that affect business strategy and human welfare.
Teachers



Intended learning outcomes
- A critical understanding of the principal theories of international trade and investment, including those related to exchange rate regimes and global stock and bond markets.
- Specialised knowledge of factors driving an organisation’s entrance into international business environments.
- Select topics in the impact of regional treaties on international trade as well as the monetary and financial environment for international business.
- Critically assess and communicate effectively on the role played by multinational economic and social aid organisations such as the UN, EU, IMF, WTO, and World Bank in facilitating international trade and business.
- Autonomously assess and advise on business operations and relationships in complex international business environments.
- Act ethically, diplomatically, and with emotional sensitivity in international business environments.
- Simulate cross-cultural business negotiations by recalling the steps in global strategic planning and the models available to direct the analysis and decision-making involved.
- Assess the nature and impact of globalisation on the world’s economy.
- Effectively communicate how economic and political systems interact to form a political economy.
- Identify how cultural differences restrict and create opportunities for management action, international trade, and its forms and theories.
About
This module encompasses statistics, decision analysis, and simulation modelling.
Throughout the module, students will strengthen their capacity to lead individuals, teams, and organisations in processes that generate data-driven solutions to problems, data-driven insights into customer behaviour, and data-driven decision-making. This module provides the foundations of probability and statistics required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty, with incomplete information, and in both structured and unstructured settings. Theoretical topics include decision trees, hypothesis testing, multiple regression, Monte Carlo simulation, and sampling and estimation.
Teachers



Intended learning outcomes
- Theories for business applications in the domain of evidence based decision-making.
- A critical understanding of the foundations of probability and statistics to the extent required for a manager to interpret large quantities of data and to make informed decisions under conditions of uncertainty.
- Key theoretical topics pertaining to evidence-based decisionmaking such as decision trees, hypothesis testing, multiple regression, and sampling.
- Relevant topics for the advanced management of data-driven insights into customer segments.
- Diverse scholarly views on evidence-based decision-making in a business context.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of evidence-based decision-making in a business context.
- Autonomously gather evidence and organise it into a coherent, comprehensive presentation advocating an evidence-based decision.
- Apply in-depth domain-specific knowledge and understanding to evidence-based decision-making in a business context.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Efficiently manage interdisciplinary and diverse kinds of evidence that inform decision-making.
- Apply a professional and scholarly approach to data and evidence as factors in decision-making.
- Solve problems and be prepared to take leadership decisions related to evidence-based decision-making in a business context.
- Act autonomously in identifying research problems and solutions related to evidence-based decision-making in a business context.
- Create synthetic contextualised discussions of key issues related to evidence-based decision-making.
- Demonstrate self-direction in gathering and using evidence and data for decision-making.
About
This module examines specific issues involved in building and managing global brands in such a way that they contribute to shareholder value. A global brand uses the same name and logo and has awareness, availability, and acceptance in multiple regions of the world. It shares the same strategic principles, values, positioning, and marketing throughout the world. Although the marketing mix can vary, it is managed in an internationally coordinated manner. Throughout this module, students will develop skills related to building strong global brands; developing marketing mix strategies that are an effective combination of global standardisation, local adaptation, and worldwide learning; and managing global brands.
Teachers



Intended learning outcomes
- e) Relevance of theories for business applications in the domain of global brand management.
- d) Diverse scholarly views on evidence-based brand management in a business context.
- b) Key theoretical topics pertaining to brand management such as multichannel and multicultural strategies, global standardisation, local adaptation, and worldwide learning.
- c) Selected topics for the advanced management of brands considering customer perceptions and expectations.
- a) A critical understanding of the factors driving global brand recognition and engagement at a level required for managerial decisionmaking.
- b) Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- a) Autonomously gather evidence and organise it into a coherent, comprehensive presentation advocating specific approaches to brand management.
- c) Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of global brand management in a business context.
- d) Apply in-depth domain-specific knowledge and understanding to branding strategies in a business context.
- a) Participate in and analyse discussions of key issues related to international branding.
- d) Demonstrate self-direction in gathering and using evidence and data for developing marketing strategies related to brand.
- b) Apply a professional and scholarly approach to data and evidence as factors in developing a global brand.
- f) Solve problems and be prepared to take leadership decisions related to evidence-based decision-making in a business context.
- c) Efficiently manage interdisciplinary and diverse kinds of evidence that inform branding.
- e) Act autonomously in identifying research problems and solutions related to global branding in a business context.
About
Excel in entrepreneurship with "Finding the Product-Market Fit," a specialized MBA course designed to equip aspiring business leaders with the skills to align products with market demands. This course delves into the critical process of ensuring that a product meets the needs of its target market, a key determinant of startup success. The course highlights strategies for achieving sustainable product-market fit and scaling businesses effectively. Through case studies of high-growth companies, students will gain practical insights into successful product-market fit strategies. Hands-on projects and guidance from seasoned entrepreneurs will provide real-world experience in testing and validating product concepts. By the end of this course, students will be prepared to develop and refine products that truly meet market needs, ensuring a solid foundation for entrepreneurial success and growth.
Teachers



Intended learning outcomes
- Describe segmentation strategies and frameworks to effectively identify and prioritize target customer segments.
- Understand the role of feedback in validating product-market fit and driving iterative product development.
- Define the key components of a value proposition, including customer benefits, unique selling points, and competitive differentiation.
- Apply iterative design and prototyping techniques to refine product features and enhance value proposition effectiveness.
- Interpret and analyze market data to extract actionable insights relevant to product-market fit and value proposition development.
- Apply critical thinking skills to assess market research needs and select appropriate methodologies for targeting customer segments.
- Evaluate market data to discern customer needs and preferences, guiding strategic decision-making.
- Implement feedback mechanisms to systematically collect and analyze insights from customers and stakeholders.
- Construct clear and compelling value propositions tailored to specific customer segments.
About
This course is designed to help aspiring entrepreneurs identify and address market needs effectively. It focuses on developing a deep understanding of customer problems and creating solutions that resonate with the target audience. Through case studies of successful startups, students will gain practical insights into the process of refining their business ideas. Hands-on projects and mentorship from experienced entrepreneurs will further enhance their ability to create viable and impactful solutions. By the end of this course, students will be equipped with the tools and strategies to find and validate problem-solution fit, setting the foundation for successful and sustainable ventures.
Teachers



Intended learning outcomes
- Describe analytical techniques for assessing market demand, such as market sizing, trend analysis, and customer segmentation.
- Recognize the limitations and biases associated with different validation techniques and strategies.
- Explain the role of customer feedback and market insights in driving iterative refinement processes to achieve a strong problem-solution fit.
- Analyze qualitative and quantitative data to identify patterns and insights relevant to market needs and preferences.
- Utilize analytical skills to assess market demand, competition, and scalability factors to evaluate solution viability.
- Adapt and pivot business ideas based on evolving market conditions and feedback, demonstrating resilience and flexibility in decision-making.
- Demonstrate creativity and adaptability in exploring alternative solutions to address identified market problems effectively.
- Synthesise insights from customer discovery to develop innovative solutions that address validated market need
- Demonstrate proficiency in analysing customer feedback to uncover underlying pain points and unmet needs.
About
This course explores the dynamic world of entrepreneurship with It offers a blend of theoretical frameworks and practical strategies essential for launching and scaling businesses in today’s competitive market.
Key topics include ideation, business model development, market analysis, and funding strategies. Students will learn how to create robust business plans, attract investors, and build scalable operations. The course also covers leadership skills, team building, and the challenges of scaling, providing a comprehensive toolkit for entrepreneurial success.
Through case studies of high-growth startups and interactive sessions with seasoned experts, students will gain real-world insights and actionable strategies. Hands-on projects and pitch presentations will further enhance their ability to turn innovative ideas into thriving businesses. By the end of this course, students will be prepared to launch new ventures and scale existing ones, driving innovation and growth in the entrepreneurial landscape.
Teachers



Intended learning outcomes
- Identify key factors and variables influencing business success and failure, such as market trends, competitive dynamics, and financial metrics.
- Define scalability in the context of business operations and leadership, emphasizing the ability to grow and expand operations without proportional increases in resources or costs.
- Explain negotiation techniques and principles for securing favorable terms and agreements in funding deals and strategic partnerships.
- Cultivate effective communication and persuasion skills to pitch business ideas, negotiate funding deals, and establish strategic partnerships.
- Demonstrate proficiency in conducting market analysis, competitor research, and customer segmentation to inform strategic decision-making and business planning.
- Implement scalable operational processes and systems to support business growth and expansion while maintaining operational efficiency and quality standards.
- Implement scalable operations and leadership practices to manage growth effectively and sustain long-term success in dynamic market environments.
- Demonstrate proficiency in financial modeling and valuation techniques to attract investors and secure financing for venture launches and scaling initiatives.
- Develop comprehensive business plans that integrate thorough market analysis, financial projections, and growth strategies to ensure successful venture launches.
About
This course delves into the critical aspects of acquiring talent and managing performance and rewards effectively. Explore recruitment strategies, selection processes, and talent sourcing techniques to attract and retain top talent. Dive into performance management frameworks, including goal setting, feedback mechanisms, and performance appraisal systems. Discover the principles of designing competitive compensation and rewards programs that align with organizational objectives and employee motivation. Through case studies and practical exercises, develop skills in talent acquisition planning, performance evaluation, and designing reward structures.This course equips you to drive organizational success through effective talent management and reward strategies.
Teachers



Intended learning outcomes
- Discuss the theories and practices of rewards management, including compensation structures, benefits administration, and incentive programs.
- Describe the principles and methods of talent acquisition, including recruitment channels, selection techniques, and legal considerations.
- Explain the components of performance management systems, including goal setting, performance appraisal methods, and feedback mechanisms.
- Design competitive and equitable rewards and recognition programs that align with organizational goals and enhance employee motivation.
- Implement effective talent acquisition strategies, including sourcing, screening, and selecting candidates.
- Facilitate performance management processes, including goal setting, performance reviews, and feedback sessions.
- Develop comprehensive talent acquisition strategies that address workforce planning needs and attract top talent.
- Execute performance management practices that align individual goals with organizational objectives, fostering a culture of continuous improvement.
- Evaluate the effectiveness of rewards and recognition programs through analysis of employee engagement, retention rates, and performance outcomes.
About
This course delves into the strategic processes and methodologies essential for effectively managing and optimizing workforce capabilities within organizations. Explore workforce planning methodologies, including forecasting future workforce needs and aligning them with business goals. Learn strategies for recruitment, selection, and onboarding to build a skilled and motivated workforce. Discover the importance of talent retention, performance management, and succession planning in maintaining organizational stability and growth. Through practical applications and case studies, develop skills in workforce analytics, strategic staffing, and workforce development. This course prepares you to strategically manage human capital to drive organizational success and sustainability.
Teachers



Intended learning outcomes
- Explain the role of workforce management in organizational strategy, including talent acquisition, development, and retention strategies.
- Discuss the legal and ethical considerations in workforce planning and management practices.
- Describe the principles and methodologies of workforce planning, including demand forecasting and supply analysis.
- Implement strategic workforce planning initiatives aligned with organizational goals and objectives.
- Conduct workforce analysis and forecasting to anticipate future talent needs and gaps.
- Utilize HR metrics and analytics to assess workforce performance, productivity, and effectiveness.
- Execute effective workforce management practices, including recruitment, selection, and development initiatives, to optimize organizational performance.
- Develop comprehensive workforce planning strategies that align with organizational objectives and support long-term sustainability.
- Evaluate the impact of workforce planning and management strategies on organizational success, using data-driven insights and metrics.
About
This course explores the principles and practices essential for enhancing organizational learning and employee development. Delve into learning theories, instructional design methodologies, and training evaluation techniques. Discover strategies for identifying training needs, designing effective learning programs, and delivering engaging training sessions. Explore the role of technology in learning delivery and the importance of continuous professional development. Through case studies and practical applications, develop skills in designing learning interventions, facilitating learning experiences, and assessing training effectiveness. This course prepares you to foster a culture of learning within organizations and equip employees with the knowledge and skills for continuous growth and success.
Teachers



Intended learning outcomes
- Explain instructional design principles and methodologies for developing effective training programs.
- Describe theories of adult learning and their application in organizational settings.
- Discuss the role of learning technologies and tools in facilitating employee development and organizational learning.
- Evaluate the effectiveness of learning and development initiatives through assessment and feedback mechanisms.
- Design effective learning interventions and training programs tailored to organizational needs and learning objectives.
- Facilitate engaging learning experiences using a variety of instructional methods and technologies.
- Assess the impact of learning interventions on organizational performance and employee growth, recommending improvements and adjustments as needed.
- Develop comprehensive learning and development strategies aligned with organizational goals and employee development needs.
- Implement effective training and development programs that enhance employee knowledge, skills, and performance.
About
This course explores effective strategies for leveraging organic channels to enhance online visibility and drive sustainable growth. Dive into search engine optimization (SEO), content marketing, and social media strategies tailored to organic growth. Learn to optimize websites for search engines, create compelling content, and engage audiences organically. Discover techniques for building brand authority, fostering community engagement, and generating leads without paid promotion. Through hands-on exercises and case studies, develop skills in planning, implementing, and measuring success through organic digital marketing channels. This course equips you to harness the power of organic strategies to achieve long-term digital marketing success.
Teachers



Intended learning outcomes
- Discuss the role of social media platforms in organic digital marketing, including best practices for engagement, content promotion, and community management.
- Explain the principles and strategies of content marketing, including content creation, distribution channels, and the role of SEO in content strategy.
- Describe the fundamentals of search engine optimization (SEO), including key concepts such as keywords, on-page optimization, and off-page factors.
- Create engaging and relevant content strategies for organic digital marketing channels, including blogs, videos, and social media posts.
- Utilize social media platforms to cultivate organic engagement, build brand awareness, and foster community interaction.
- Implement effective search engine optimization (SEO) techniques to improve website visibility and organic traffic.
- Evaluate the effectiveness of organic digital marketing efforts through analytics and metrics, adjusting strategies to optimize engagement, traffic, and conversion rates.
- Develop comprehensive organic digital marketing strategies aligned with business objectives, integrating SEO, content marketing, and social media tactics.
- Execute effective implementation of SEO strategies, including keyword research, on-page optimization, and backlink building, to improve search engine rankings.
About
This course explores the diverse landscape of digital marketing strategies that leverage paid channels for optimal reach and engagement. Dive into platforms like Google Ads, social media advertising, and display advertising. Learn to create targeted campaigns, optimize ad performance, and measure ROI effectively. Discover advanced techniques for audience segmentation, ad copywriting, and budget allocation to maximize campaign success. Through practical simulations and real-world case studies, develop skills in planning, executing, and analyzing paid digital marketing campaigns. This course equips you to harness the power of paid channels to drive traffic, conversions, and business growth in the digital age.
Teachers



Intended learning outcomes
- Explain the key principles and best practices for creating effective paid digital marketing campaigns, such as targeting, ad formats, and bidding strategies.
- Discuss the metrics and analytics used to measure the success of paid digital marketing campaigns, including CTR, CPC, conversion rates, and ROI.
- Describe the various paid digital marketing channels available, including Google Ads, social media advertising platforms, and display networks.
- Create targeted paid digital marketing campaigns across platforms such as Google Ads and social media, tailored to specific audience segments.
- Analyze campaign metrics and KPIs to evaluate effectiveness, make data-driven decisions, and optimize future digital marketing efforts.
- Optimize ad performance through A/B testing, keyword optimization, and bid management strategies to maximize ROI.
- Develop comprehensive paid digital marketing strategies aligned with business goals, integrating platforms and tactics to maximize reach and conversions.
- Evaluate the impact of paid digital marketing campaigns on business outcomes, leveraging analytics to optimize strategies and enhance.
- Execute effective campaign management practices, including budget allocation, scheduling, and performance monitoring, to achieve targeted marketing objectives.
About
This course explores the landscape of digital marketing channels and the metrics used to measure their effectiveness. Dive into various channels such as search engine marketing (SEM), social media marketing, email marketing, and display advertising. Learn to create integrated digital marketing strategies that align with business goals. Discover how to analyze and interpret key metrics including click-through rates (CTR), conversion rates, return on investment (ROI), and customer acquisition cost (CAC). Through hands-on projects and case studies, develop skills in optimizing campaigns, tracking performance, and making data-driven decisions to maximize marketing effectiveness.
Teachers



Intended learning outcomes
- Describe the various digital marketing channels available, including their features, advantages, and target audiences.
- Explain the key metrics used in digital marketing, such as CTR, conversion rate, ROI, and customer acquisition cost (CAC).
- Discuss the principles and best practices of digital marketing campaign management, including budgeting, targeting strategies, and ad creative optimization.
- Utilize digital marketing tools and platforms to create, manage, and optimize campaigns effectively.
- Implement digital marketing strategies across various channels such as SEM, social media, email, and display advertising.
- Analyze key digital marketing metrics to evaluate campaign performance, identify trends, and make data-driven decisions for optimization.
- Develop integrated digital marketing strategies that align with organizational goals and target audience preferences.
- Execute digital marketing campaigns across multiple channels, demonstrating proficiency in campaign setup, management, and optimization.
- Evaluate the effectiveness of digital marketing efforts through comprehensive analysis of metrics, providing insights and recommendations for continuous improvement.
About
This module provides students with advanced methods and frameworks for
understanding customer needs, and for translating those needs into a
program of research and product development that can be used to create a successful new product or service. It equips students with skills to generate new product hypotheses, to research the potential of a new product or entrepreneurial venture, and to adjust the product offering to fit the needs of customers. This module instills the all-important distinction between a ‘bright idea’ and a ‘business opportunity’ in new product creation.
Using disciplined methods of customer and market analysis, students will gain advanced abilities in defining the core customers for a new product or entrepreneurial venture.
Students will study the complex combination of factors that influence customers to adopt a new product or service. They will gain a comprehensive understanding of what makes entrepreneurial selling unique, and why it is valuable to integrate key aspects of selling and marketing activities in a new venture. Students will learn how to select potential customers through data collection, including customer interviews, and students will learn how to analyse that data to refine a product offering.
Teachers
Intended learning outcomes
- Theories of product creation for business applications.
- Business new product inspiration and creation.
- Key strategies for hypothesis-driven product creation and revision.
- Diverse scholarly views on how new products should be developed and introduced to the market.
- Select topics for the advanced management of product inspiration, market testing, and product revision.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing in discussions about product inspiration and creation.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on a new product.
- Apply an in-depth domain-specific knowledge and understanding to business creativity and innovation.
- Creatively apply the theories learned in the module to develop critical and original solutions for a new product.
- Apply a professional and scholarly approach to research problems related to new product formulation and introduction.
- Create synthetic contextualised discussions of key issues related to new product creation.
- Demonstrate self-direction in research and originality in solutions developed.
- Efficiently manage interdisciplinary issues that arise in the creation and definition of new products.
- Act autonomously in identifying research problems and solutions related to business product innovation and creation.
- Solve problems and be prepared to take leadership decisions related to business creativity and innovation.
About
This module examines iterative product development as a method for improving customer adoption and retention. Students will gain a mastery of iterative product development as a strategy for (a) transforming market research into potential solutions, (b) testing hypotheses about product improvements, and (c) gaining validation for product adjustments.
Students will gain a comprehensive understanding of the concept of a minimum viable product, how to test the market in the early stages of product adoption, and the benefits and weaknesses of incremental product improvements. Students will gain an advanced understanding of concepts related to customer segmentation, cohort analysis, and churn in order to learn from market responses to product changes, increase customer retention, and expand customer adoption.
Teachers
Intended learning outcomes
- Theories for product measurement and adoption.
- Diverse scholarly views on the role of measurement in product adoption.
- Select topics for the advanced management of product adoption and post-adoption optimisation.
- Customer segmentation and cohort analysis.
- Key strategies for reducing churn and increasing user adoption.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on measurement and product adoption.
- Apply an in-depth domain-specific knowledge and understanding to customer segmentation and cohort retention analysis.
- Creatively apply the theories learned in the module to develop critical and original solutions for product measurement in order to drive adoption outcomes.
- Demonstrate self-direction in research and originality in solutions related to increasing and maintaining product adoption while avoiding churn.
- Apply a professional and scholarly approach to research problems of measurement and data-driven decision-making pertaining to product adoption.
- Efficiently manage interdisciplinary issues that arise in connection product improvements and product adoption.
- Create synthetic contextualised discussions of key issues related to product adoption.
- Act autonomously in identifying research problems and solutions related to product adoption.
- Solve problems and be prepared to take leadership decisions related to measuring product adoption.
About
This module provides students with advanced methods needed to understand how a product will fit into a competitive market, and how to introduce the product into that market. This includes advanced research on the receptiveness of a market to the new product, as well as strategies for defining and finding the market that will be most receptive to the product. Students consider product introductions with the goal of what Marc Andreesen called ‘product/market fit’ - a ‘good market with a product that can satisfy that market.’
The module trains students to reflect upon and analyse a company’s go-to- market strategy, and it provides students with sophisticated methods of calculating customer acquisition cost, determining customer break-even, and calculating customer lifetime value.
Teachers
Intended learning outcomes
- Diverse scholarly views on product launches in relation to product/market fit.
- Topics for the advanced management of product introductions.
- Key implementation strategies for introducing a product to a market.
- Product/market fit theories to product launches and implementation strategies.
- Business strategies for product introductions.
- Apply an in-depth domain-specific knowledge and understanding to product/market fit.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of calibrating the relationship between a product and a market.
- Employ the standard modern conventions for the presentation of scholarly work on product launches.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on product/market fit.
- Act autonomously in identifying research problems and solutions related for product introductions.
- Create synthetic contextualised discussions of key issues related to product launches and post-launch market fit.
- Apply a professional and scholarly approach to research problems pertaining to product/market fit.
- Demonstrate self-direction in research and originality in solutions developed.
- Solve problems and be prepared to take leadership decisions related to new product introductions.
- Efficiently manage interdisciplinary issues that arise in determining how to assess new product implementations.
About
This course delves into the critical intersection of ethics and law within healthcare practice. Explore ethical dilemmas, patient rights, and professional responsibilities in medical decision-making. Discuss legal frameworks, regulations, and healthcare policies that govern patient care and organizational practices. Through case studies and discussions, examine issues of confidentiality, informed consent, and end-of-life care. Gain insights into navigating ethical challenges and legal complexities to ensure patient welfare and uphold healthcare standards. This course equips you with the knowledge to navigate ethical dilemmas, legal requirements, and uphold ethical standards in healthcare delivery and decision-making.
Teachers



Intended learning outcomes
- Explain the legal frameworks and regulations governing healthcare practice, including patient rights, confidentiality, and informed consent.
- Discuss the ethical considerations in end-of-life care, patient-provider relationships, and healthcare decision-making.
- Describe the ethical principles and theories relevant to healthcare practice, such as autonomy, beneficence, non-maleficence, and justice.
- Evaluate healthcare policies and legal frameworks to ensure compliance and ethical practice in patient care and organizational policies.
- Demonstrate effective communication skills to facilitate informed consent and ethical decision-making processes with patients and their families.
- Apply ethical principles and theories to analyze and resolve complex ethical dilemmas in healthcare settings.
- Evaluate ethical dilemmas and propose solutions that uphold ethical standards, legal requirements, and patient rights in healthcare settings.
- Develop policies and procedures that promote ethical practice and compliance with legal standards in healthcare organizations.
- Apply ethical reasoning and legal principles to make informed decisions in complex healthcare scenarios, ensuring patient welfare and ethical integrity.
About
This module has been designed to foster a strong safety culture by disseminating safe behaviours throughout the organisation, with a strong focus on leadership development at all levels.
Teachers
Intended learning outcomes
- Diverse scholarly views on the role of leadership in health and safety.
- Select topics for the advanced management of health and safety
- Key strategies for promoting health and safety in a work environment.
- Apply an in-depth domain-specific knowledge and understanding to health and safety leadership.
- Understand and demonstrate the importance of leadership for improving health and safety performance.
- Create synthetic contextualised discussions of key issues related to health and safety.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on health and safety.
- Critically assess the relevance of quality management and various quality management models.
- Creatively apply the theories learned in the module to develop critical and original solutions for health and safety leadership
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Understand and demonstrate the impact of leadership on team cohesion and functioning in the health and safety sector.
About
The purpose of this module is to give learners an opportunity to integrate all the knowledge from their programme of learning by developing a project in which they plan and implement a new product, service or process. Learners need to take a full and active role in all aspects of the project, and the selection of an appropriate management issue is crucial to success. Learners will cover a full range of management activities and roles, including resource and people management and implementation of change. The result needs to be a substantial report in a style appropriate for consideration by senior management
Teachers
Intended learning outcomes
- Diverse scholarly views on the role of software in product management.
- Communication planning and management within a project context.
- Select topics in advanced product management.
- Project Management strategies and practices in a global context.
- Creatively apply the theories learned in the module to develop critical and original solutions for product management in order to drive adoption outcomes.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on product management.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Develop project specifications, schedule, controls, and evaluation of project work, using various project management tools.
- Act autonomously in identifying research problems and solutions related to product management.
- Create synthetic contextualised discussions of key issues related to product management.
- Implement and evaluate the outcomes of a project.
- Apply an in-depth domain-specific knowledge and understanding to product management.
- Efficiently manage interdisciplinary issues that arise in connection product management.
About
This module provides an introduction to the main areas of Enterprise Risk Management. This module also covers Risk Management processes and strategies. Numerous case studies from various business sectors will illustrate the increasing importance of Enterprise Risk Management.
Teachers
Intended learning outcomes
- Diverse scholarly views on the role of risk management
- Key methods to manage and organisation’s risk, including risk optimisation, and management of market risk, credit risk, operational and other risks.
- Select topics for the advanced management of various risks in a business setting.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on risk management.
- Demonstrate an understanding of the relevance of ERM to stakeholders.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- Apply a professional and scholarly approach to research problems of measurement and data-driven decision-making pertaining to risk management.
- Create synthetic contextualised discussions of key issues related to risk management.
- Act autonomously in identifying research problems and solutions related to risk management
- Describe and show an understanding of different risk categories.
- Demonstrate an understanding of risk management frameworks for financial organisations in different regulatory environments.
About
This course explores the essential principles and practices for efficient management of materials and supplies in healthcare settings. Learn about inventory control, procurement strategies, and supply chain logistics tailored to healthcare needs. Delve into techniques for optimizing inventory levels, reducing waste, and ensuring timely availability of medical supplies. Through case studies and practical applications, gain skills in managing healthcare materials to support patient care, enhance operational efficiency, and minimize costs. This course equips you with the knowledge to effectively navigate the complexities of material management in healthcare, ensuring quality service delivery and patient satisfaction.
Teachers



Intended learning outcomes
- Describe the principles and concepts of material management in healthcare, including inventory control and supply chain logistics.
- Discuss regulatory requirements and guidelines related to inventory management and material handling in healthcare settings.
- Explain the importance of effective procurement strategies and vendor relationships in healthcare material management.
- Implement supply chain logistics strategies to improve the efficiency and reliability of material flow within healthcare facilities.
- Apply inventory management techniques specific to healthcare settings to optimize stock levels and reduce costs.
- Utilize procurement strategies and vendor management skills to ensure timely and cost-effective acquisition of medical supplies.
- Evaluate and optimize inventory systems and supply chain processes to enhance healthcare material availability and reduce waste.
- Design and implement comprehensive material management strategies that meet healthcare facility needs while ensuring cost-effectiveness and efficiency.
- Lead initiatives to improve material management practices within healthcare organizations, demonstrating effective decision-making and resource allocation.
About
This course provides a thorough exploration of techniques to enhance healthcare quality and performance. Learn the principles of benchmarking, including identifying best practices and setting performance standards. Delve into quality management frameworks and tools, such as Six Sigma and Lean, tailored for healthcare settings. Through practical exercises and real-world case studies, gain skills in measuring, analyzing, and improving healthcare processes. This course equips you with the knowledge to drive continuous improvement, ensure patient safety, and achieve excellence in healthcare delivery, ultimately leading to better patient outcomes and organizational efficiency.
Teachers



Intended learning outcomes
- Explain different quality management frameworks and their application in healthcare settings, such as Six Sigma and Lean methodologies.
- Describe the principles and importance of benchmarking in healthcare quality improvement.
- Discuss the role of quality indicators and metrics in monitoring and improving healthcare outcomes.
- Evaluate healthcare quality indicators and benchmarks to assess performance against industry standards.
- Develop strategies for implementing best practices identified through benchmarking to enhance patient care and safety.
- Apply quality management tools and techniques, such as Six Sigma and Lean methodologies, to streamline healthcare processes and improve efficiency.
- Implement effective benchmarking processes to identify and adopt best practices in healthcare delivery.
- Evaluate the impact of quality management strategies on healthcare outcomes and patient satisfaction.
- Lead quality improvement initiatives by applying advanced quality management tools and methodologies in healthcare settings.
About
This course offers a comprehensive exploration of creating and overseeing effective distribution networks. Learn the principles of channel design, including selecting and managing intermediaries, logistics coordination, and performance evaluation. Delve into strategies for optimizing distribution efficiency and ensuring seamless product flow from producers to consumers. Through practical exercises and case studies, gain insights into managing relationships with channel partners, resolving conflicts, and adapting to market changes. This course equips you with the skills and knowledge to design robust distribution channels that enhance customer satisfaction and drive business success.
Teachers



Intended learning outcomes
- Identify key components and functions of distribution channels and their roles in the supply chain.
- Explain the principles of channel design and the factors influencing channel selection and management.
- Compare different distribution channel strategies and their impacts on market reach and customer satisfaction.
- Analyze distribution channel structures and evaluate their effectiveness in various market contexts.
- Design optimal distribution networks by applying principles of channel design and logistics coordination to real-world scenarios.
- Manage relationships with channel partners, using conflict resolution and performance evaluation techniques to ensure seamless product flow and customer satisfaction.
- Assess the performance of distribution channels and make data-driven adjustments to enhance operational effectiveness and customer satisfaction.
- Implement effective logistics and coordination practices to optimize product flow and distribution efficiency.
- Develop comprehensive distribution channel strategies that align with business objectives and market demands.
About
This course delves into the critical role of data analytics in optimizing supply chain operations. Explore methodologies and tools for collecting, analyzing, and interpreting supply chain data to enhance efficiency and decision-making. Learn to leverage analytics to forecast demand, manage inventory, and improve logistics. Discover how data-driven insights can mitigate risks, reduce costs, and enhance overall supply chain performance. Through practical applications and case studies, develop skills in using statistical models, optimization techniques, and data visualization tools to solve real-world supply chain challenges. This course equips you with the knowledge to drive strategic improvements and innovation within supply chain management.
Teachers



Intended learning outcomes
- Explain the fundamental principles and concepts of supply chain management and logistics.
- Describe different analytical techniques and tools used in supply chain analytics, such as optimization models, simulation, and predictive analytics.
- Discuss the role of data analytics in supply chain decision-making, including forecasting, inventory management, and risk mitigation.
- Utilize data analytics tools and software to analyze and interpret supply chain data effectively.
- Apply statistical techniques and optimization models to improve supply chain processes and decision-making.
- Create visualizations and reports to communicate supply chain insights and recommendations to stakeholders.
- Evaluate supply chain performance using analytics-based metrics and KPIs, recommending continuous improvement initiatives.
- Develop and implement data-driven supply chain strategies that optimize efficiency and reduce costs.
- Apply supply chain analytics techniques to identify and solve complex supply chain problems and challenges.
About
Teachers



Intended learning outcomes
About
This course offers a practical and theoretical foundation of machine learning, enabling future business leaders to leverage machine learning for data-driven insights and competitive advantage. Key topics include supervised and unsupervised learning, predictive analytics, and model evaluation. Students will explore how machine learning algorithms can be applied to solve complex business problems across various domains such as marketing, finance, and operations. Through case studies and hands-on projects, students will gain practical experience in building and implementing machine learning models. Interactive sessions with industry experts provide additional insights into best practices and real-world applications. By the end of this course, students will be equipped with the skills and knowledge to integrate machine learning into business strategies, enhancing their ability to make informed, data-driven decisions.
Teachers



Intended learning outcomes
- Recognize the importance of data quality, data preprocessing, and feature engineering in preparing datasets for machine learning analysis.
- Identify common evaluation metrics and techniques used to assess the performance and generalization ability of machine learning models, such as confusion matrices, ROC curves, and cross-validation.
- Understand the theoretical foundations and working principles of popular machine learning algorithms, including linear regression, logistic regression, decision trees, k-nearest neighbors, and neural networks.
- Tune model hyperparameters, select appropriate features, and optimize model performance through iterative experimentation and validation.
- Implement machine learning algorithms using programming languages and libraries such as Python, scikit-learn, and TensorFlow to develop predictive models for decision support systems.
- Continuously monitor model performance and iterate on model improvements to adapt to changing business requirements and data dynamics.
- Conduct exploratory data analysis (EDA) and data preprocessing techniques to understand the characteristics and patterns within complex datasets.
- Implement a variety of machine learning algorithms, including regression, classification, clustering, and ensemble methods, to develop predictive models that enhance strategic decision-making.
- Evaluate the effectiveness and performance of machine learning models in solving real-world business problems and improving decision processes.
About
This course is designed to explore how Artificial Intelligence (AI) and Machine Learning (ML) can revolutionize business practices. This course provides a comprehensive overview of leveraging AI and ML to drive innovation and efficiency in various business functions.Key topics include AI and ML fundamentals, data analytics, automation, and predictive modeling. Students will learn how to implement AI/ML solutions in areas such as marketing, finance, operations, and customer service. Through case studies of leading organizations and interactive sessions, students will gain insights into successful AI/ML strategies and applications. Hands-on projects and collaboration with industry experts will further enhance their ability to design and deploy AI/ML solutions.By the end of this course, MBA students will be equipped with the knowledge and skills to integrate AI and ML into their business strategies, driving growth, efficiency, and innovation in their organizations.
Teachers



Intended learning outcomes
- Explore emerging trends and technologies in AI/ML, such as edge computing, federated learning, and AI-driven automation, and their potential applications and implications for business innovation and efficiency.
- Explain the concepts and techniques of advanced data analytics, including predictive modeling, pattern recognition, and anomaly detection, in the context of business intelligence and insights generation.
- Identify common business problems and use cases where AI/ML technologies have demonstrated significant value and impact, such as customer segmentation, fraud detection, demand forecasting, and personalized recommendations.
- Design and implement end-to-end AI/ML solutions, including data ingestion, preprocessing, model training, evaluation, and deployment, within business environments and infrastructures.
- Evaluate model performance and optimize parameters through techniques such as cross-validation, hyper parameter tuning, and ensemble learning to achieve desired business outcomes and objectives.
- Apply statistical methods and hypothesis testing to validate findings and conclusions drawn from data analysis and modeling exercises.
- Communicate data-driven insights effectively to stakeholders through reports, presentations, and visualization tools to facilitate informed decision-making and drive organizational growth.
- Foster a culture of innovation and continuous improvement by championing the adoption of AI/ML solutions, fostering cross-functional collaboration, and promoting knowledge sharing and best practices.
- Utilize domain knowledge and data-driven insights to identify suitable AI/ML approaches and algorithms for solving diverse business problems effectively.
About
This course explores the transformative world of Artificial Intelligence (AI) and Machine Learning (ML) in this comprehensive MBA specialization course. It provides an in-depth understanding of how AI and ML are reshaping industries and driving innovation. Key topics include the fundamentals of AI and ML, data-driven decision-making, and the integration of AI/ML in business functions such as marketing, finance, and operations. Students will examine case studies of leading organizations, gaining insights into best practices and common pitfalls. The course also covers emerging trends and ethical considerations, preparing students to navigate AI-driven business environments. Hands-on projects and interactive sessions with industry experts offer practical experience, enhancing students’ ability to apply AI and ML concepts in a business context. By the end of this course, students will be equipped to harness AI and ML for innovation, efficiency, and sustainable growth in their organizations.
Teachers



Intended learning outcomes
- Define reinforcement learning and its components, including agents, environments, states, actions, and rewards.
- Describe the architecture and workings of artificial neural networks (ANNs) and deep neural networks (DNNs), including feedforward and convolutional neural networks.
- Understand the principles and objectives of semi-supervised learning and its distinction from supervised and unsupervised learning.
- Evaluate and fine-tune reinforcement learning models through simulation, experimentation, and performance analysis in diverse application domains.
- Fine-tune pre-trained deep learning models and architectures to achieve better performance and adaptability to specific datasets and tasks.
- Interpret and communicate the results of semi-supervised learning experiments, including model performance metrics and insights gained from unlabeled data.
- Identify the core concepts and components of reinforcement learning, including agents, environments, actions, and rewards.
- Explore the fundamental principles and architectures of deep learning models, including artificial neural networks and deep neural networks.
- Analyze the principles and techniques of semi-supervised learning to recognize its potential applications and advantages.
About
This course delves into essential methodologies for understanding user preferences and competitive landscapes in business contexts. Explore techniques for conducting qualitative and quantitative research to uncover user needs, behaviors, and preferences. Analyze competitive analysis frameworks to identify market trends, strengths, and weaknesses of competitors. Learn to leverage insights from user and competition research to inform strategic decision-making and product development. Through practical exercises and case studies, gain skills in data interpretation, market segmentation, and developing actionable insights. This course equips you to effectively navigate market dynamics, innovate products, and enhance competitive positioning.
Teachers



Intended learning outcomes
- Explain the importance of user research in understanding customer needs, behaviours, and preferences.
- Discuss competitive analysis frameworks and tools for evaluating market competition, including SWOT analysis, Porter's Five Forces, and market segmentation.
- Describe various qualitative and quantitative research methods used to gather user data and preferences.
- Utilize competitive analysis frameworks to assess market dynamics, identify competitors' strategies, and evaluate competitive strengths and weaknesses.
- Generate actionable recommendations based on user and competition research to inform strategic decision-making and product development.
- Conduct qualitative and quantitative research methods to gather user insights and preferences.
- Apply advanced research techniques to gather and analyze user data effectively, providing actionable insights for business decisions.
- Develop comprehensive competitive intelligence reports that identify market trends, assess competitors' strategies, and recommend strategic responses.
- Evaluate the impact of user and competition research on business strategy and propose adjustments to enhance competitive positioning.
About
This course explores the strategies and processes involved in bringing new products to market and optimizing their growth. Learn to identify market opportunities, conduct market research, and develop innovative products that meet customer needs. Delve into stages of product lifecycle management, from concept development to commercialization. Gain insights into pricing strategies, distribution channels, and marketing tactics to maximize product adoption and profitability. Through case studies and hands-on projects, acquire skills in product innovation, strategic planning, and fostering sustainable growth. This course prepares you to drive product success in dynamic market environments, ensuring sustainable business growth.
Teachers



Intended learning outcomes
- Explain the importance of market research, consumer behavior analysis, and competitive analysis in product development.
- Discuss various strategies for pricing, distribution, and promotion to drive product growth and market penetration.
- Describe the stages of product development lifecycle, from ideation and concept development to commercialization and launch.
- Evaluate product performance metrics and make data-driven decisions to optimize product positioning and growth strategies.
- Implement effective product development strategies, including market research, concept testing, and product iteration.
- Create innovative product concepts and prototypes that address market needs and opportunities.
- Develop comprehensive product development plans that integrate market insights, innovation strategies, and commercialization tactics.
- Evaluate product performance and iterate strategies based on market feedback and competitive analysis to sustain growth and profitability.
- Execute effective product launch strategies, including marketing campaigns and distribution plans, to maximize market adoption and growth.
About
This course immerses you in the creative and technical aspects of product design from concept to realization. Explore the principles of design thinking, prototype development, and user-centered design methodologies. Learn to identify user needs, conduct market research, and integrate feedback into iterative design processes. Delve into CAD tools, materials selection, and manufacturing considerations to create functional and innovative products. Through hands-on projects and collaborative exercises, develop skills in ideation, prototyping, and refining designs based on usability and market viability. This course prepares you to envision and bring to life products that meet both user expectations and business objectives.
Teachers



Intended learning outcomes
- Explain the importance of user research, market analysis, and feasibility studies in the product design process.
- Describe the principles and stages of product design, including ideation, concept development, and prototyping.
- Discuss various design methodologies and tools used in product development, such as CAD software, rapid prototyping techniques, and materials selection.
- Generate creative product concepts and prototypes that address user needs and market demands.
- Utilize design thinking methodologies and user-centered design principles to develop innovative and user-friendly product designs.
- Demonstrate proficiency in using CAD software and other design tools to create detailed product specifications and prototypes.
- Develop innovative product designs that integrate user feedback, market research, and functional requirements.
- Evaluate and refine product designs based on usability testing, feedback from stakeholders, and market viability assessments.
- Apply design principles and technical knowledge to prototype and iterate product designs effectively.
About
In this module, students learn about the complex responsibilities facing business leaders today. Through cases about difficult managerial decisions, the course examines the legal, ethical, and economic responsibilities of corporate leaders. It also teaches students about management and governance systems leaders can use to promote responsible conduct by companies and their employees, and shows how personal values can play a critical role in effective leadership. Additionally, this module is designed to deepen and extend students' conceptual and practical understanding of leadership in organisations, extending beyond the application of knowledge in practical judgements that achieve business outcomes, to embrace wider social and ethical considerations. The course is experiential and multidisciplinary, requiring participants to reflect on the social and ethical responsibilities of leaders in relation to their own experiences. It is designed to help students discover insights about themselves as leaders, fostering the development of self-awareness, including strengths and opportunities for personal growth.
Teachers



Intended learning outcomes
- Select topics for advanced cultivation and management skills related to one’s own experiences.
- Critical knowledge of ways in which one’s behaviours and decision-making can impact others and affect goals of leading with integrity.
- Theories of corporate responsibility in relation to ethical considerations.
- Specialised knowledge of key strategies for cultivating reflective leadership.
- Diverse scholarly views on self-awareness.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on the social and ethical responsibilities of leaders in relation to their own experiences.
- Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of responsible leadership.
- Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing, when communicating about the cultivation of social and ethical responsibilities faced by leaders.
- Efficiently manage interdisciplinary issues that arise when assessing the conditions for corporate accountability.
- Demonstrate self-direction in cultivating habits that improve accountability while in leadership positions.
- Create synthetic contextualised discussions of key issues related to leadership and corporate accountability.
- Solve problems and be prepared to take leadership decisions related to social and ethical considerations.
About
This module focuses on multiple aspects of team dynamics and structure, with a focus on the organisational intelligence needed to lead and manage diverse organisations in a varied marketplace. Theories of organisational behaviour, social psychology, and anthropology are critically discussed in relation to real-world scenarios.
Additionally, this module introduces students to the challenges and opportunities faced in multifaceted workplaces and provides evidence-based insights and practical strategies for how to accelerate team engagement and belonging as a pathway to sustainability and competitive advantage. Ultimately, this module enables students to successfully build and lead organisations that are multifaceted, equitable, and engaging.
Teachers
Intended learning outcomes
- The impact of employing persons with varying backgrounds on firm strategy, organisational performance, and market leadership.
- Strategic approaches that organisations use to foster cross-team and cross-cultural collaboration.
- The impact of cross-cultural competence and incompetence on global business practices.
- Frameworks for comparing and contrasting workers’ values and diagnosing potential complications.
- Employ the standard modern conventions for practising conscious inclusion in teams and organisations.
- Creatively apply the theories learned in the module to develop strategic approaches that organisations can use to foster workforce collaboration and leverage difference as a source of sustainable competitive advantage.
- Autonomously gather material and organise it into a coherent, comprehensive presentation on the social and ethical responsibilities of leaders in relation to their own experiences through the use of fieldwork.
- Understand and assess the historical evolution of workplace sustainability and equity globally.
- Critically discuss diverse workplaces and inclusion in terms of organisations and society.
- Efficiently manage interdisciplinary issues related to the relationship between culture and self-presentation in a workplace setting.
About
This module is designed to provide students with the skills and knowledge to influence and lead social impact in business and impact contexts. By the conclusion of this module, students should have a strong foundation in social impact and social change, including approaches to funding impact, scaling programmes, and interventions, public-private partnerships, corporate engagement, impact investment decision-making, blended capital, and approaches to intentional impact.
The module will pivot around multiple case studies addressing social issues through which students learn and test social impact frameworks and concepts. Once students have gained a mastery of perspectives and methodologies necessary to consider and address a social issue from the ground up, they will next learn to identify and utilise effective measures of outputs and progress and explore the core levers and potentials to change outcomes for people, communities and market systems.
Teachers



Intended learning outcomes
- Critical knowledge of public-private partnerships and corporate engagement in relation to social change.
- Impact investment decision-making and its impact on global business.
- The impact of diversity, equity, and inclusion in organisations on approaches to intentional impact.
- Strategic approaches that organisations use to foster social change.
- Autonomously gather material and organise it into coherent, comprehensive presentations identifying and utilising effective measures of outputs and progress that explore the core levers and potentials to change outcomes for people, communities, and market systems
- Creatively apply the theories learned in the module to test social impact frameworks and concepts
- Ability to critically discuss social change programmes and interventions in terms of organisations and society.
- Efficiently manage interdisciplinary issues related to funding impact in a corporate setting.
- Understand and assess the historical evolution of social impact and social change globally.
About
Teachers



Intended learning outcomes
About
The focus of this module is to introduce concepts, skills, and strategies for performing competitively in the business market where organisations rather than households are the customers. This module provides a managerial introduction to the strategic and tactical aspects of business marketing decisions and marketing channel strategy. Students examine the strategic concepts and tools that guide market selection, successful differentiation in business markets, and supply chain management. Students will examine how product and service decisions are designed to deliver the B2B value proposition, how pricing captures customer value, how value is communicated to and among customers, and how marketing channels are used to make this value accessible to target customers. Additionally, students will compare and contrast how the strategic and tactical processes of developing and managing value-generating relationships differ between B2B and B2C markets. Moreover, students will also gain an understanding of how to manage channel power, conflict, and relationships.
Teachers



Intended learning outcomes
- A critical understanding of the process by which strategic market analysis guides the development of B2B marketing programmes that integrate product pricing, communications, and channel decisions
- The ability to assess differing systematic approaches to problem solving and decision-making in business marketing organisations through the use of case studies.
- Design strategies and structures to effectively serve the B2B market.
- Analyse market opportunities and company capabilities as the basis for market selection, developing competitive differentiation, and formulating marketing channel strategy in contemporary business markets.
- Develop a business marketing plan for real-life applications.
- Develop managerial orientation to implementing and controlling B2B marketing programmes and managing channel relationships.
- Develop a managerial perspective on the marketing function in firms that target business and government customers in both domestic and global contexts.
- Critically discuss the applications, challenges, and environment of B2B marketing, including the unique nature of organisational buying behaviour.
About
This module examines specific issues involved in building and managing global brands in such a way that they contribute to shareholder value. A global brand uses the same name and logo and has awareness, availability, and acceptance in multiple regions of the world. It shares the same strategic principles, values, positioning, and marketing throughout the world. Although the marketing mix can vary, it is managed in an internationally coordinated manner. Throughout this module, students will develop skills related to building strong global brands; developing marketing mix strategies that are an effective combination of global standardisation, local adaptation, and worldwide learning; and managing global brands.
Teachers



Intended learning outcomes
- e) Relevance of theories for business applications in the domain of global brand management.
- d) Diverse scholarly views on evidence-based brand management in a business context.
- b) Key theoretical topics pertaining to brand management such as multichannel and multicultural strategies, global standardisation, local adaptation, and worldwide learning.
- c) Selected topics for the advanced management of brands considering customer perceptions and expectations.
- a) A critical understanding of the factors driving global brand recognition and engagement at a level required for managerial decisionmaking.
- b) Employ the standard modern conventions for the presentation of scholarly work and scholarly referencing.
- a) Autonomously gather evidence and organise it into a coherent, comprehensive presentation advocating specific approaches to brand management.
- c) Creatively apply the theories learned in the module to develop critical and original solutions for the challenges of global brand management in a business context.
- d) Apply in-depth domain-specific knowledge and understanding to branding strategies in a business context.
- a) Participate in and analyse discussions of key issues related to international branding.
- d) Demonstrate self-direction in gathering and using evidence and data for developing marketing strategies related to brand.
- b) Apply a professional and scholarly approach to data and evidence as factors in developing a global brand.
- f) Solve problems and be prepared to take leadership decisions related to evidence-based decision-making in a business context.
- c) Efficiently manage interdisciplinary and diverse kinds of evidence that inform branding.
- e) Act autonomously in identifying research problems and solutions related to global branding in a business context.
About
The role of marketing management in organisations is to identify and measure the needs and wants of consumers, to determine which targets the business can serve, to decide on the appropriate offerings to serve these markets, and to determine the optimal methods of pricing, promoting, and distributing the firm’s offerings. Successful organisations are those that integrate the objectives and resources of the organisation with the needs and opportunities of the marketplace. The goal of this module is to facilitate student achievement of these goals regardless of career path.
Throughout the module, students will study various tools for generating marketing insights from data in such areas as segmentation, targeting and positioning, satisfaction management, customer lifetime analysis, customer choice, product and price decisions using conjoint analysis, and text analysis, and search analytics.
Teachers



Intended learning outcomes
- A specialised knowledge of real-world applications of conjoint analysis.
- Select topics in marketing data collection, analysis, and interpretation.
- Various scholarly approaches to cluster analysis methods for marketing segmentation, analysis, and positioning.
- A critical understanding of selected marketing concepts within the context of specific business problems and their applications.
- Conduct customer lifetime analysis.
- Apply marketing concepts to real-life marketing situations.
- Use various data visualisation tools to communicate clearly about customer behavior, preferences, or other insights.
- Set up regressions, interpret outputs, analyse confounding effects and biases, and distinguish between economic and statistical significance.
- Critically analyse different methods for data-driven decision making in a marketing context..
- Assess the major functions that comprise the marketing task in organisations, and create data-informed approaches to these functions..
- Measure customer lifetime value and use that information to evaluate strategic marketing alternatives.
Entry Requirements
Application Process
Submit initial Application
Complete the online application form with your personal information
Documentation Review
Submit required transcripts, certificates, and supporting documents
Assessment
Your application will be evaluated against program requirements
Interview
Selected candidates may be invited for an interview
Decision
Receive an admission decision
Enrollment
Complete registration and prepare to begin your studies
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