MiM - Data Science & AI for Business Track

This course offers a comprehensive introduction to modern data analysis and forecasting techniques, combining foundational statistical concepts with advanced data manipulation using Python. Students will develop the knowledge to analyse data effectively and use Python to manipulate and visualise large datasets. They will gain practical skills to apply statistical principles for performing descriptive statistics, execute calculations and operations on datasets using Python, and create graphical representations to highlight key data features. Additionally, students will enhance their ability to communicate data analysis results clearly and effectively. Through hands-on experience, this course equips students with the essential tools for extracting and interpreting insights from complex data. 

This course explores the principles and practices of Database Management Systems (DBMS), focusing on software solutions for data collection, retrieval, and security. Students will understand the fundamentals of database design and the role of data models in structuring data, as well as analyse various database models and architectures, evaluating their strengths and weaknesses. They will gain practical skills to develop and execute SQL queries for retrieving, manipulating, and managing data in relational databases, and will learn to design and implement relational database schemas, applying best practices for normalization and ensuring data integrity. Additionally, the course fosters a systems thinking approach to database management, equipping students to manage data efficiently and securely. 

This course introduces the mathematical foundations of machine learning, focusing on linear algebra, calculus, numerical optimisation, and probability theory, providing students with the tools needed to understand and implement machine learning algorithms. Participants will gain knowledge of fundamental concepts in linear algebra and calculus, as well as basic principles of numerical optimization and probability theory. They will develop practical skills to apply these mathematical concepts to solve machine learning problems and create tools for analysing machine learning algorithms. Python is used to illustrate these concepts, although it is not part of the course evaluation. 

This course explores portfolio construction with a focus on the mean-variance portfolio theory and its applications to asset pricing models, including the Capital Asset Pricing Model and the Fama-French three-factor model. Students will gain an understanding of the principles of mean-variance portfolio optimisation and the relationship between portfolio optimisation and asset pricing through factor models. Through hands-on exercises and practice sessions in Excel, students will develop skills to simulate investment strategies using market data, calculate mean-variance efficient portfolios, and estimate key parameters such as expected returns, covariances, and betas with respect to factors. This practical approach ensures a thorough understanding of both the theoretical and implementation aspects of portfolio construction. 

This course provides a comprehensive understanding of techniques for constructing optimal portfolios, starting with an evaluation of asset profitability and addressing common challenges in portfolio construction. Students will learn to analyse basic portfolio optimisation techniques and apply Python tools to conduct risk-return analyses of portfolios. Additionally, students will develop practical skills in using Python as a standard tool, collaborate effectively in teams, adopt a systems thinking approach, and design strategies under conditions of uncertainty. By combining theoretical knowledge with hands-on Python applications, this course equips students with the tools and skills necessary for modern portfolio management. 

This course equips students with the skills to read, analyse, and interpret financial reports and accounting data, offering a comprehensive overview of financial accounting concepts and practices. Students will develop an understanding of financial reporting, firm financial statements, and the valuation of firms within modern financial markets. They will gain practical competencies to prepare and interpret Discounted Cash Flow (DCF) and comparable company analyses, as well as evaluate financial reports using key metrics such as liquidity, solvency, and profitability. Additionally, the course emphasises adopting a systems thinking approach and designing strategies under uncertainty, ensuring students are prepared to apply these techniques in a globalised, dynamic environment governed by International Financial Reporting Standards. 

This course focuses on developing key managerial skills for Data Sciences and AI for Business students through an action-learning approach. Participants will gain an understanding of theoretical frameworks related to teams, communication, and leadership while enhancing their ability to give and receive feedback to strengthen leadership capabilities. The course emphasises practical competencies, enabling students to channel creativity in managerial contexts, whether collaborating, leading, or following. Additionally, they will learn to actively listen, reflect on personal leadership and team dynamics, and effectively participate in diverse teams, fostering essential skills for future managerial roles. 

This course provides students with essential skills in data visualization, highlighting its critical role in interpreting and analysing data. Students will gain an understanding of the importance of data visualization in data analysis and learn to apply both basic and advanced visualization techniques using various tools. They will develop practical skills to analyse data sets, create meaningful visual representations to derive insights, and evaluate and refine visualizations based on best practices and interactivity principles. Additionally, the course encourages students to conceive organisational transformations aligned with desirable futures and design strategies to navigate uncertainty, combining technical expertise with strategic thinking. 

This course examines bond markets, yield curve dynamics, and interest rate risk management using duration and convexity analysis. Students will gain an understanding of bond pricing, yield curves, and interest rate risks, as well as the principles and pricing models behind derivatives such as forwards, options, and swaps. They will develop skills in the structure, pricing, and valuation of bonds, along with proficiency in pricing derivatives using models like binomial trees and the Black-Scholes formula. The course also covers hedging strategies to mitigate financial risks. Additionally, students will adopt a systems thinking approach and design strategies to address uncertainty in financial markets. 

This course provides participants with fundamental knowledge of marketing, highlighting its pivotal role within organisations. Students will gain an understanding of what marketing is, its function within an organisation, and the process of value creation from the perspectives of customers, organisations, and society as a whole. They will also develop the ability to integrate various marketing tools and techniques in a coherent manner and will learn to conceive organisational transformations aligned with desirable futures, equipping them with both theoretical insights and practical skills for effective marketing practices. 

This course provides a hands-on introduction to quantitative modelling and machine learning, focusing on their implementation in Python for business applications. Students will gain familiarity with key machine learning approaches for supervised and unsupervised learning, along with an understanding of biases, ethical concerns, and risks associated with ML studies. They will develop practical skills to perform a complete machine learning analysis, including assessing important metrics and evaluating the statistical significance of results. Additionally, the course emphasises adopting a systems thinking approach and designing strategies under uncertainty, equipping students with both technical and strategic capabilities for applying machine learning to real-world business challenges. 

This course introduces the essential analytical tools and concepts used in Corporate and Business Strategy. Students will understand the role of external and internal environments in strategic analysis and learn to use financial analysis to inform strategic recommendations. They will develop the ability to make strategic decisions aimed at building competitive advantage and apply key frameworks such as Industrial Organisation, the Resource-Based View (RBV), and Transaction Cost Theory (TCT) to address corporate strategy decisions, including vertical integration, diversification, internationalisation, and mergers and acquisitions. The course equips students with both theoretical and practical insights for effective strategic decision-making. 

This course equips students with essential skills to effectively use cost, financial, and non-financial information for decision-making, planning, and controlling operations while implementing business strategies. Participants will gain an understanding of the principles and techniques of cost and management accounting, recognising their importance in both organisational and societal contexts. They will develop practical expertise in methods such as product costing, budgeting, social and environmental accounting, and the sustainability balanced scorecard. Furthermore, students will learn to design and implement comprehensive performance management systems that integrate financial and non-financial metrics to evaluate organisational performance. The course also emphasises adopting a systems thinking approach and envisioning organisational transformations aligned with desirable futures, ensuring a strategic and holistic approach to management. 

This course provides a foundational framework for assessing national and international macroeconomic developments, essential for business and investment decisions. Students will understand the short-, medium-, and long-term interactions between output, money, prices, and the labour market, as well as the key international relationships between trade, capital flows, exchange rates, and interest rates. They will also explore the determinants of long-term economic growth. By applying this knowledge, participants will develop the ability to evaluate the likely paths of key economic variables, assess risk scenarios, and use proven frameworks to explain countries' long-term economic trajectories and the impact of policies on growth, supported by real-world examples and practical analysis. 

This course examines the ethical dilemmas and regulatory frameworks surrounding the development and deployment of AI, focusing on issues such as bias, privacy, accountability, and transparency to promote the responsible use of AI. Students will gain an understanding of major national and international regulatory frameworks, such as GDPR and the EU AI Act, and key ethical principles including fairness, transparency, accountability, and privacy. They will develop skills to apply ethical frameworks to real-world AI scenarios, effectively communicate complex ethical and regulatory issues to diverse stakeholders, adopt a systems thinking approach, and conceive organisational transformations aligned with desirable futures. This course equips students to navigate the ethical and regulatory landscape of AI with a forward-thinking and practical perspective. 

This course explores the transformative impact of emerging platforms and decentralised technologies on the financial services industry, focusing on the rise of fintech startups and the entry of BigTech companies into finance. Students will gain an understanding of the structural drivers behind these changes, the fintech industry's origins, key players, business models, and value drivers. The course provides a thorough examination of distributed ledger technologies, covering both protocol and application layers, and evaluates when blockchain and tokenisation enable fundamental innovation. Participants will also learn how fintech companies leverage new market mechanisms to create value, identify and assess innovative fintech ventures and opportunities, and adopt a systems thinking approach to address industry challenges. Additionally, the course emphasises envisioning organisational transformations aligned with desirable futures, equipping students with the knowledge and skills to thrive in the evolving financial landscape. 

This course introduces data integration techniques, with a focus on Application Programming Interfaces (APIs) and Extract, Transform, Load (ETL) processes. Students will develop an understanding of the fundamentals of APIs and their role in data integration, as well as the principles of ETL processes and their application in data workflows. Through hands-on exercises using tools like Python and relevant libraries, participants will acquire practical skills to extract data from APIs, process it through ETL pipelines, and apply these techniques to real-world business and analytics scenarios. The course also emphasises adopting a systems thinking approach and envisioning organisational transformations aligned with desirable futures, equipping students with the skills to leverage data integration for decision-making and innovation. 

This course provides an introduction to the fundamental concepts and business applications of blockchain technology, with a focus on its implications for the financial industry. Students will gain an understanding of the basic principles of blockchain and explore its potential applications within finance. They will develop the ability to assess the technology's impact on the financial sector, engage in discussions about future trends and developments in blockchain, and adopt a systems thinking approach. Additionally, the course encourages students to envision organisational transformations aligned with desirable futures, equipping them with the knowledge to navigate and innovate in a blockchain-driven landscape. 

This course focuses on the application of time series modelling in the financial sector to support informed decision-making. Students will critically evaluate the market efficiency hypothesis and explore the limitations and potential predictability of financial returns. They will gain familiarity with key statistical models used in finance and learn to estimate and predict the mean and variance of financial returns, particularly for portfolio management purposes. In a multivariate context, the course will cover techniques for estimating large or dynamic covariance matrices and integrating beliefs into statistical models. Using Python, participants will develop practical skills to make forecasts and effectively report and interpret results from statistical models, equipping them for data-driven decision-making in finance. 

This course focuses on developing VBA programming skills for solving option pricing problems, using Excel as an effective pedagogical tool to understand the mechanisms behind option valuation. Students will gain an understanding of how VBA in Excel provides a robust and efficient framework for pricing derivatives and explore the differences between various option pricing methods. They will acquire practical competencies to price vanilla and exotic options using methods such as Cox-Ross-Rubinstein, Black-Scholes, and Monte Carlo simulations, and to program efficient VBA routines for each of these methods. The course combines theoretical understanding with hands-on programming skills, equipping students to develop their own derivatives pricing tools. 

This course equips students with the knowledge and skills to implement fixed income strategies, understand interest rate derivatives, and construct interest rate structured products. Participants will learn to bootstrap yield curves for pricing Interest Rate Swaps and Constant Maturity Swaps and gain an understanding of interest rate option pricing models. They will develop practical competencies to create fixed income strategies, effectively neutralising duration and convexity, as well as comprehend the motives behind and the construction of interest rate structured products. This course provides both theoretical foundations and hands-on expertise for managing and innovating in fixed income markets. 

This course explores the transformative potential of Generative AI (GenAI), the fastest-spreading technology in history, and its role in enhancing business operations and creating competitive advantages. Students will gain an understanding of the technical foundations of GenAI, including the data, processes, and technologies required for its integration into companies, while identifying key applications, business value, and challenges across various sectors. Participants will develop practical skills through hands-on experience with GenAI tools such as Large Language Models and text-to-image generators, including the use of prompt engineering techniques. Additionally, the course addresses the ethical, social, and environmental implications of scaling GenAI in business, emphasising responsible management. Students will learn to integrate GenAI into business strategies, design strategies under uncertainty, and conceive organisational transformations aligned with desirable futures, ensuring readiness to harness GenAI’s potential responsibly and effectively. 

This course explores the transformative potential of Generative Artificial Intelligence (GenAI) and focuses on mastering prompt engineering as a critical skill to interact effectively with GenAI models. Students will learn to identify and apply various prompting frameworks and best practices, enabling them to generate accurate, relevant, and contextually appropriate outputs. The course addresses ethical and regulatory considerations in leveraging AI for business and provides hands-on experience in creating effective prompts to interact with Multimodal Large Language Models. Participants will also develop skills to build custom GPT solutions tailored to business challenges and design strategies under uncertainty, equipping them to harness GenAI for personal productivity, innovation, and strategic applications in diverse business contexts.