Programme overview

A curriculum that bridges data science and business strategy

The Data Science and Marketing Analytics specialisation combines courses from data science and marketing into one coherent master programme focused on using data to solve real business challenges. No advanced prior knowledge is required—core courses in computer and data science lay the groundwork for more advanced seminars, where you will explore state-of-the-art machine learning methods and apply them to real-life business problems.

The curriculum

This specialisation consists of core courses, seminars, electives, and a master thesis, spread across five blocks of eight weeks. The structure is designed to gradually build your knowledge and skills, while offering opportunities for deep application and reflection.

• Block 1 introduces three core courses (4 ECTS each), providing the foundational knowledge and skills you will need to succeed in the programme.
• Blocks 2 and 3 provide intensive seminars where you learn new methods from machine learning and artificial intelligence and you apply these methods to real-world business problems. These seminars are highly interactive and require full-time commitment and active participation.
• Block 4 includes one final course and an elective of your choice.
• Blocks 4 and 5 are also dedicated to your master thesis, which is based on independent research under the supervision of a faculty member.

Curriculum overview

• 50% Computer science, machine learning and artificial intelligence
• 50% Marketing and business

The coursework is designed to balance theory and practice, with a strong emphasis on applying your skills to real-world data and decision-making.

In class

A key strength of machine learning and artificial intelligence is their predictive power. For marketing analysts, this opens up new ways to improve customer experience—making shopping more relevant and effective. In class, you will explore cases such as:

• Composing personalised product recommendations
• Identifying a customer’s stage in the buying process
• Delivering the right information at the right time to enhance engagement

These cases illustrate how data science can be used not only to understand behaviour, but also to shape it—creating value for both businesses and consumers.

Study schedule

Find all the courses in the Course catalogue

Disclaimer

This overview provides a general impression of the 2027-2028 curriculum. It is not the current study schedule. Enrolled students can find the most up-to-date version on MyEUR. Please note that minor changes may occur in future academic years.