Data science & management

The CAS in Data Science & Management focusses not only AI and use cases, but covers all relevant aspects required to manage a successful transformation towards a data- and AI-driven enterprise.

On the technical side, you will explore the latest trends, such as generativeAI, LLMs or data mesh as well as the underlying foundations and gain hands-on experiences with AI and ML, using a low-code platform. On the business dies, you will learn how to define a data and AI strategy and roadmap that creates sustainable business value, including effective data governance and data democratization within your organization.

No, the CAS in Data Science & Management is designed for decision-makers. We will demystify latest trends and (AI, machine learning, big data) without requiring programming skills (SQL, Python, etc.). The focus is on strategic analysis and data-driven decision-making, with hands-on sessions and real business cases at the root of the program to ensure participants can directly apply their learning to practical challenges.

Yes, absolutely. This executive education program includes several practical case studies and applied exercises based on real data sets from different industries. The goal is not to train technical data scientists, but to enable you to understand how to extract, read, and interpret data to guide informed decision-making.

These scenarios help you:

• Identify relevant patterns in the data.
• Understand the limitations of interpreting a dataset.
• Communicate effectively
• Mobilize concrete insights in a managerial or strategic context.

The goal is to master the fundamentals of analytical thinking so you can play an active role in data projects within your organization.

Artificial intelligence (AI) and machine learning (ML) are central to the program, but always with an accessible and strategic approach. You won't become a data scientist or developer, but you will learn to understand what lies behind these technologies and how to apply them in a business context: how they work, how they “learn” from data, and above all, how they can transform processes, professions, and business models.

The speakers will help you demystify these concepts, which are often perceived as opaque, so that you can grasp their concrete applications in your professional context. Particular attention is paid to the limitations and potential abuses of these technologies, particularly in terms of the reliability of results, the transparency of models, and the impact on individuals and organizations.

In short, AI and ML are not treated as black boxes to be endured, but as powerful tools to be understood, evaluated, and used with discernment.

Absolutely. Data governance and quality are major themes of the program, addressed not as technical constraints, but as essential drivers of performance and trust within organizations. An entire module is devoted to managing data as a strategic asset, with a particular focus on the reliability, traceability, and security of information.

Participants learn how to implement governance tailored to their organization's context, how to define robust quality standards, and how to ensure data consistency over time and across different silos.

The issue of regulatory compliance, particularly with regard to the GDPR and the use of personal data in AI systems, is also addressed. Those who wish to go further in this area can take the complementary Data Protection & AI program course (link), offered in parallel.

This part of the CAS thus enables participants to develop a clear vision of the responsibilities associated with data management, while providing professionals with concrete tools to make it a sustainable asset.

Yes, the CAS in Data Science & Management is a program designed and delivered jointly by two leading institutions in Switzerland: HEC Lausanne (University of Lausanne) and EPFL. You will benefit from the combined expertise of an internationally recognized management faculty and a world-class engineering school, giving the degree dual academic legitimacy and strong recognition in the marketplace.

The CAS in Data Science & Management draws on the expertise of two major partner centers in the field of data in Switzerland:

The Swiss Data Science Center (SDSC), a key player in the Swiss innovation landscape, which supports the implementation of complex data projects by integrating cutting-edge approaches in data science and artificial intelligence.

The Competence Center Corporate Data Quality (CC CDQ), which specializes in data governance and quality. This center contributes to training by providing a structured and operational approach to data management as a strategic asset.

Thanks to these collaborations, the program incorporates the latest practices in data strategy, data management, and responsible innovation.

No, the CAS in Data Science & Management is taught exclusively in English. This approach reflects the resolutely international nature of the field of data science and data management, whose terminology, tools, and practices are predominantly English-speaking. Participants must therefore have a good command of professional English, both spoken and written, in order to follow the courses, interact with the speakers, and complete the individual project (IDP).