Notice: The information about the subjects of the four courses is for guidance only and may change over time. We strive to keep it updated, so we recommend checking it periodically to have the latest details
First Year
1st Semester
Calculus and Algebra
Students develop a rigorous understanding of calculus and linear algebra – the mathematical language underpinning machine learning and AI. By the end of the course, students will have the quantitative reasoning skills and mathematical fluency needed to succeed in the program's advanced courses.
Students are introduced to the core principles behind how computers work from mathematical logic and hardware architecture to operating systems and programming. Through the course, students will be able to think algorithmically to solve problems and write their own Python programs.
Students gain the essential economic tools to understand how markets operate, exploring supply and demand dynamics, price elasticity, and market structures. Students will be able to apply economic reasoning to strategic business decisions and policy challenges.
Students examine the social structures, power dynamics, and ideologies that shape individuals, organisations, and the modern world. They will draw on sociological theories and apply them to real-world issues such as algorithmic bias and global governance. The course will help students sharpen their critical thinking and emerge as more ethically informed professionals.
Students gain a comprehensive introduction to descriptive statistics and probability, covering data summarisation, probability models, and discrete and continuous random variables, with hands-on practice using Excel. By the end of the course, students will be confident in applying statistical reasoning and communicating data-driven insights in a business context.
Students expand their foundational knowledge of calculus and algebra to delve deeper into multivariable calculus, differential equations, numerical methods, and function spaces. The course will provide students with the mathematical tools needed to excel in disciplines such as data science, quantitative finance, and research.
Students are introduced to the legal frameworks that govern business activity, including corporate law, intellectual property, competition law, commercial contracts, and crisis management. By the end of the course, students will have the practical skills needed to identify legal considerations in business decision-making and collaborate effectively with legal professionals.
Students explore the theory and practice of statistical inference, learning to make data-driven decisions using techniques such as hypothesis testing, estimation, regression analysis, and clustering. By applying these tools to real business environments, students will develop strong analytical and data literacy skills, along with practical experience using statistical software tools.
Students explore how the aggregate economy functions in a global context, analyzing fiscal and monetary policy, labor markets, and open-economy models. The course aims to equip students with the skills needed to critically evaluate economic trends and understand the broader economic forces shaping the business environment.
Students build on their foundational knowledge of Python to master the principles of object-oriented programming, including inheritance, encapsulation, and polymorphism. They will also learn to use libraries such as NumPy to manipulate and analyze large datasets. Students will be able to design scalable and well-structured Python programs, as well as apply systematic testing and debugging techniques to solve problems.
Students are introduced to fundamental algorithmic thinking and data structures, covering sorting algorithms, recursion, trees, graphs, dynamic programming, and heuristic search. Through lectures and hands-on Python exercises, students will have a robust computational toolkit for more advanced studies in AI and machine learning.
Students will learn to interpret and evaluate the financial health of companies and corporate groups, covering advanced financial statements, consolidation processes, and profitability and market analysis. Through the course, students will be able to diagnose a company's financial position and make informed recommendations using real company data including sustainability reporting.
Students are introduced to the essential concepts, tools, and frameworks underpinning modern marketing. Through honing the three core pillars of understanding, creating, and executing, students will have practical skills in market research, segmentation, targeting, positioning, and marketing mix decision-making.
Students explore the core principles driving how companies create and deliver goods and services, from innovation and planning to quality management, sustainability, and digital transformation. Using frameworks such as Lean, Six Sigma, and Industry 4.0, students will be capable in aligning operational decisions with broader corporate strategy to drive efficiency, quality, and competitive advantage.
Students learn the core practices of modern software development, covering software design principles, terminal scripting, version control with Git and GitHub, containerisation with Docker, and server deployment. Through hands-on exercises and collaborative projects, students will have the technical foundations needed to succeed in advanced studies in system architecture, DevOps, and database management.
Students explore the key theories and concepts that shape how people behave, collaborate, and lead within organizations, including motivation, team dynamics, conflict management, and transformational leadership. By the end of the course, students will have a greater understanding of their own leadership style and the tools needed to make a meaningful and responsible impact in any team or organization.
Students acquire the essential skills to design, manage, and query both relational and NoSQL databases. They will learn to model data using entity-relationship diagrams, write SQL queries in MySQL, and manipulate data in MongoDB. The course aims to prepare students to contribute to the development of modern data-driven applications and to the definition of business strategies based on information.
Students acquire the analytical tools to understand how companies create value for shareholders, covering investment appraisal, capital budgeting, cost of capital, and discounted cash flow analysis. Students will be able to confidently evaluate financial decisions and apply industry-standard valuation models in professional settings.
Students receive a comprehensive introduction to artificial intelligence and machine learning. They will explore the mathematical foundations behind supervised learning algorithms, data preparation, optimization, and model evaluation. Through hands-on Python programming and group projects, students will gain the fundamental knowledge needed to tackle complex data-driven challenges and confidently progress to advanced AI topics such as deep learning and neural networks.
Students are introduced to the theory and practical application of optimization techniques and computational modeling, including heuristic search, simulated annealing, Monte Carlo simulations, and genetic algorithms applied to complex business and economics challenges. Students will learn to design and implement algorithmic solutions to real-world problems in areas such as finance, operations management, and strategic planning.
Students apply AI to real-world business and sustainability challenges, developing end-to-end projects that integrate technical implementation, qualitative research, design thinking, and impact evaluation aligned with the UN Sustainable Development Goals. By the end, students would have built a functional AI solution that solves a real-world problem.
Cloud Solutions
Students are introduced to cloud computing, exploring how industry-leading platforms such as AWS, Microsoft Azure, and Google Cloud Platform can be used to build scalable, secure, and efficient data analytics solutions. By the end of the course, students will be equipped to design, deploy, and manage real-world cloud architectures and automate infrastructure deployment.
Students advance their Python data visualisation skills by learning to build interactive dashboards using industry-standard tools like Streamlit. They will also explore the principles of effective visual design and data storytelling in real-world business contexts. By the end, students will be equipped to communicate data insights with clarity and impact, and to recognise the cognitive biases that can undermine sound decision-making.
Students will take a deep dive into advanced machine learning techniques including ensemble methods, clustering, reinforcement learning, and active learning. They will learn to design, implement, and optimise complete machine learning pipelines applied to real-world business problems. Students will have the technical expertise and critical judgment needed to evaluate model performance and anticipate the broader implications of deploying AI solutions.
Students explore how large, diversified companies are managed at the highest level, examining decisions around diversification, mergers and acquisitions, alliances, and international expansion. Through case studies and hands-on company analysis, students will learn the analytical frameworks and strategic thinking skills needed to tackle the complex challenges faced by today's top executives.
Students explore how leaders can responsibly leverage artificial intelligence, examining the strategic, ethical, and organizational dimensions of AI adoption in contexts ranging from data-driven organizational design to managing large-scale digital transformations. The course aims to equip students with the skills to develop AI-ready organizations, apply people analytics in leadership decisions, and address the human and ethical challenges of AI implementation.
Students explore the intersection of artificial intelligence, ethics, law, and society, examining how technical decisions in AI development have real-world consequences for fairness, accountability, and power through case studies and the analysis of frameworks such as the EU AI Act. Students will be equipped to critically assess the ethical and legal implications of AI systems and design responsible governance strategies.
Students are introduced to the theoretical foundations and practical applications of powerful neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, and Transformers. Gaining hands-on experience in building and training models in PyTorch for computer vision and natural language processing, students will be equipped to design end-to-end deep learning solutions and communicate their results to both technical and non-technical audiences.
Students gain advanced, hands-on experience in the design and deployment of AI-powered systems using industry-leading tools such as GitHub Actions, AWS, and Docker. They will build end-to-end CI/CD pipelines and production-ready MLOps solutions, including a fully integrated Retrieval-Augmented Generation (RAG) system. Students will be prepared to bridge the gap between AI development and real-world deployment, with highly in-demand skills in automation, cloud infrastructure, and operational excellence.
In the seventh semester, all students take part in an international exchange, completing 30 credits at one of Esade’s partner universities or business schools worldwide. This immersive experience will broaden your global perspective on business management while enhancing your ability to design and develop innovative solutions powered by artificial intelligence.