Master in AI & Data Analytics for Business Program

This course introduces participants to the field of AI and data analytics for business from a strategic angle.

Through various case studies, participants critically reflect on how AI and data science might deliver added value for companies across different industries.

This course gives insight into the various real-life aspects of AI solutions and data analytics. Real-life case studies are presented to reveal best practices in AI and data analytics.

By the end of the course, participants are better able to spot AI opportunities in business.

This course introduces participants to the most popular commercial data and AI technology, the AWS Cloud platform. Participants learn about the advantages and disadvantages of using this commercial software package.

Most of the attention goes to acquiring the relevant skills that will enable participants to flourish in a data-driven environment and understand how to create value.

The objective of this course is to introduce participants to data visualization using Tableau.

Participants learn the best practices of data visualization, how to build compelling dashboards, and how to perform visual analytics using Tableau.

The objective of this course is to introduce participants to Python programming. By the end of the course, participants are fluent in advanced Python programming.

This course covers the concepts of relational databases and the industry standard Structured Query Language (SQL).

It gives participants the ability to extract relevant information for AI and data analytics from databases using SQL.

In this course, participants are introduced to the foundational principles of descriptive and predictive analytics.

They learn essential techniques for analyzing historical data to understand past events, and become acquainted with the basic concepts of predictive analytics for predicting future outcomes.

This course provides students with the knowledge and critical perspectives needed to address the sustainability and ethical challenges facing organizations in a rapidly changing global environment.

The first part of the course introduces major sustainability issues affecting businesses, including:

Climate change

Biodiversity loss

Social justice

Labor conditions

Global supply chains

Students explore key concepts, frameworks, tools, and standards for assessing environmental, social, and governance (ESG) impacts, and how organizations can rethink their strategies and redesign their business models to support sustainability transitions. Throughout the course, they reflect critically on ecological limits, stakeholder responsibilities, and the ethical role of business in advancing sustainable development.

The second part of the course is devoted to program-specific applications tailored to the needs of each master’s program.

By the end of the course, students will be able to critically evaluate sustainability and ethical challenges, apply relevant ESG frameworks and ethical reasoning to organizational decision-making, and propose practical solutions that contribute to sustainable business practices.

Credited language courses for all levels are included in the program. French is mandatory for all non-French-speaking students.

Native French-speaking students can choose another language (Chinese, Spanish, German; list subject to change).

This course centers on big data processing and storage, and introduces the architecture of cloud platforms and streaming.

Participants are exposed to leading concepts and technologies in big data, such as Spark and Hadoop, and get acquainted with Databricks.

This course focuses on the fundamental principles of interpretable data science. Participants learn techniques for developing transparent and explainable machine learning models, and gain an understanding of methods for interpreting model predictions, assessing feature importance and supporting trustworthy data-driven decision-making.

In this course, participants learn about the design of recommender systems: the underlying concepts, the design space and the trade-offs.

Participants should understand the design space of recommender systems and be able to provide design recommendations for a particular application domain, as well as critique a design by pointing out its strengths and weaknesses.

This course introduces how network data delivers value in business decision-making.

By the end of the course, participants can scrutinize network data, build a (social) network and draw relevant conclusions that support AI and data-driven solutions.

This course introduces participants to various statistical and machine learning algorithms for AI development.

It is a fundamental course in the curriculum, as it delivers theoretical and hands-on experience in applying basic to state-of-the-art statistical and machine learning algorithms to various prediction problems.

This course delves into the essential techniques for forecasting future trends and patterns from historical data using time-series analysis.

Participants gain the expertise to make informed decisions across industries based on the forecasted outputs.

This course gives participants a unique, hands-on experience of solving a real-life AI and data science challenge for a company.

Participants work in teams on a four-month hackathon project to deliver an AI- and data-driven solution that is acceptable to both data scientists and business managers. They are supported by both academic and company supervisors.

This course equips students with the knowledge and skills required to investigate complex organizational challenges through rigorous research methods. Students learn to identify and analyze business problems, select and apply appropriate research methodologies, and critically engage with academic and professional sources to build robust, evidence-based knowledge.

Emphasis is placed on developing creative solutions to organizational issues and communicating research findings effectively through clear, persuasive, and professional presentation techniques. The course combines a common foundation in research methods with program-specific applications that reflect the research needs and practices of each master’s program.

By the end of the course, students will be able to design and conduct methodologically sound research that supports informed decision-making in organizational and business contexts.

The Career Program aims to help IÉSEG students build and implement their career plan in line with their aspirations, skills and the socio-economic reality of the market.

The objective is to facilitate their integration into the job market, in an environment that allows them to develop personally and professionally.

All students benefit from a credited program tailored to their track or major, taught by a dedicated team of experienced professionals. The Career Program includes collective credited courses, digital resources, and on-demand coaching provided by the Career team for those who need additional support.

A cycle of thematic events fosters connections with companies and helps students build their professional networks. Our teaching approach blends various methods, including digital modules, interactive and blended learning, coaching, peer-to-peer learning, learning by doing, live scenarios, debriefing, and reflection, in line with IÉSEG’s teaching and learning strategy.

Credited language courses for all levels are included in the program. French is mandatory for all non-French-speaking students.

Native French-speaking students can choose another language (Chinese, Spanish, German; list subject to change).

This course covers how to leverage company data and AI to create value and build a competitive advantage.

By the end of the course, participants can understand and manage the data lifecycle and implement a data strategy for a given company setting.

The course covers the basic principles of project management, a managerial discipline that has become unavoidable in today’s AI- and data-driven business contexts.

In industries as diverse as retail, financial services, pharmaceuticals, software and aerospace, AI projects drive business. Effective project management often opens up promising new opportunities, which in turn often translate into increased sales.

This course provides an applied perspective on mathematical programming (MP), rather than focusing on algorithms. It serves three purposes:

Providing a selective catalogue of practical MP problems faced by managers

Linking these problems to the different types of mathematical optimization methods

Formulating MP problems and interpreting their solutions within a spreadsheet

In this course, participants are introduced to the fundamental principles of optimization for business decision-making. They learn how to formulate and solve mathematical optimization models for complex business problems, with a focus on applications in supply chain management, logistics, transportation and finance.

The course covers linear, nonlinear and integer optimization techniques, and provides hands-on experience with specialized optimization software to support data-driven decision-making.

This course equips students with the knowledge and skills required to investigate complex organizational challenges through rigorous research methods. Students learn to identify and analyze business problems, select and apply appropriate research methodologies, and critically engage with academic and professional sources to build robust, evidence-based knowledge.

Emphasis is placed on developing creative solutions to organizational issues and communicating research findings effectively through clear, persuasive, and professional presentation techniques. The course combines a common foundation in research methods with program-specific applications that reflect the research needs and practices of each master’s program.

By the end of the course, students will be able to design and conduct methodologically sound research that supports informed decision-making in organizational and business contexts.

This course gives participants an in-depth understanding of entrepreneurship, new business development, and business plan writing.

Through lectures, testimonials, fieldwork, and group assignments, participants are confronted with the how, where, when, with whom, and why of starting and developing new business activities.

As part of an international and multicultural team, participants work on an operational business plan with one of two aims:

The creation of a new venture (NVC track)

The acceleration of new business for an already established SME (NBD track)

The course thus goes beyond theory: hands-on experience is gained through out-of-class fieldwork covering all steps of the entrepreneurial decision-making process, for example idea generation, feasibility analysis, industry study, market analysis, marketing plan, production plan, product development, and financial statements.

In doing so, participants acquire entrepreneurial knowledge and behaviors that support innovative solutions and new value creation.

This course equips students with the analytical tools and strategic perspective to understand how geopolitical dynamics impact global business environments. Through an interdisciplinary approach, students explore the influence of political risk, international relations, and global power shifts on trade, investment, supply chains, and corporate strategy.

Emphasis is placed on real-world cases and interactive discussions to help students assess geopolitical risk and adapt business decisions accordingly. By the end of the course, participants will be able to integrate geopolitical thinking into strategic planning, enabling responsible and resilient decision-making in complex international contexts.

Particular attention is given to the social impact of geopolitical shifts, encouraging students to consider how business decisions can promote inclusive growth, ethical practices, and long-term societal resilience.

This is a modular, asynchronous course designed to give participants a comprehensive and integrated understanding of AI and its transformative impact on business strategy. Bridging technical knowledge and strategic insight, the course guides learners through a rich curriculum that explores how AI drives innovation, enhances operational efficiency, and creates sustainable competitive advantages.

The learning journey culminates in real-world case studies that demonstrate how leading organizations have successfully integrated AI into their strategies, operations, and innovation processes. These examples provide actionable insights and help bridge theory and practice.

Crucially, the course also addresses the broader societal and environmental impacts of AI, placing ethical, ecological, and workforce considerations at the heart of strategic decision-making. By the end of the course, participants will understand not only how AI works, but also how to deploy it responsibly and strategically for long-term business success in complex, dynamic environments.

Creativity is one of the critical components of an organization’s ability to survive and thrive in today’s competitive and dynamic markets. This course gives participants a rich understanding of how creativity can be fostered and managed in a work setting.

They will acquire knowledge of the various theoretical conceptualizations of creativity (how to define it), its antecedents (what makes you and others more creative) and its outcomes (what impact it has), as well as of design thinking techniques and tools to lead teams through the creative journey.

Here are some of the questions we will address:

How do creative ideas happen?

How can we foster our creativity and the creativity of those around us?

What are the paths of creative development of individuals who succeed in their creative endeavors?

What are the implications for fostering and managing creativity in the workplace?

What are the obstacles to creativity?

What is the nature of creativity in teams and organizations?

During the course, a variety of teaching and learning techniques (including design thinking) will be used to help participants think critically and imaginatively about different perspectives on creativity.

To make learning a shared experience between participants and the instructor, the course integrates real challenges and practical experiences of creativity: projects, presentations, experiential exercises, and critical reflection on the course materials.

This advanced course offers a comprehensive exploration of how organizations can effectively manage, measure, and align performance at individual, team, and organizational levels. It begins by clarifying the concept of performance management: what it is, what it is not, and what characterizes effective strategic performance practices.

Students will examine the challenges of defining and measuring performance accurately, and how to align performance indicators with broader strategic goals such as employee engagement, retention, and organizational growth. Throughout the course, they will work with a range of human resource management tools applicable at the various stages of the performance management cycle. Legal, ethical, and reporting considerations, as well as software solutions, are also addressed to provide a holistic understanding of modern performance systems.

A key focus of the course is the social dimension of performance management. Students will explore how to design systems that are valid, reliable, and fair for all employees, with a strong emphasis on eliminating bias and supporting diversity, inclusion, and social justice.

The course encourages critical assessment of whether performance systems genuinely enable all individuals, regardless of background, to demonstrate their full potential. This includes addressing how organizational culture, leadership behaviors, and system design can unintentionally disadvantage certain groups, and how such challenges can be effectively mitigated in practice.

Credited language courses for all levels are included in the program. French is mandatory for all non-French-speaking students.

Native French-speaking students can choose another language (Chinese, Spanish, German; list subject to change).

4- to 6-month internship or work experience anywhere in the world. Alternatively, students can opt for a consulting project or a thesis.