Study program Master's Data Science in Business and Entrepreneurship
A two-year master’s program combining the theory and practice of data science & business
Combining the technological know-how of Eindhoven University of Technology (TU/e) with the business, legal and societal insights of Tilburg University (TiU), the program draws on the best in theory and practice from two leading Dutch universities. The master’s program in Data Science in Business and Entrepreneurship is designed to shape you into an all-round data scientist. You will acquire the skills that you need to order to find solutions to business and societal problems – that means passing through the Curriculum entire cycle, from approaching a problem from a data analysis perspective to implementing an appropriate data science solution, while at the same time taking account of its potential legal and social implications.
Start as of February
- If you would start as of February, the program will differ slightly. Check the differences in this February intake infographic.
- For more detailed information, read the relevant part of this document.
The program
Each year of this two-year master’s program is divided into two semesters. The first runs from September to January, and the second from February to July. Each semester consists of a series of courses, followed by a written examination period lasting two to three weeks. The program is divided into the following components:
- 10 compulsory courses (60 EC)
- 5 elective courses (30 EC)
- A master’s thesis (30 EC)
Compulsory courses
See the course descriptions for more detailed information on the compulsory courses
Year one
Semester A
- Data Intrapreneurship in Action
- Data Mining
- Data Engineering
- Strategy and Business Models
- Social Network Analysis for Data Scientists
Semester B
- Data Consultancy in Action
- Interactive and Explainable AI Design
Year 2
Semester C
- Data Entrepreneurship in Action
- Intellectual Property and Privacy
- Master thesis
Semester D
- Data Ethics and Entrepreneurship
- Master Thesis
Elective courses/specializations
On top of the mandatory courses and master’s thesis, students have to pass 5 elective courses worth 30 EC in total. Students are expected to choose one of the following specializations:
- Data Engineer
- Data Scientist
- Data Entrepreneur/Consultant
- Data-Driven Researcher
To qualify for a certain specialization a students should pass at least three courses from the relevant courses, including the core course (the course which is on the top of the list, marked in bold). Students are strongly recommended to write their thesis in line with the specialization.
Be aware of the entry requirements for certain courses:
- In order to be eligible for Advanced Data Architectures, a student needs to have passed Data Engineering.
- In order to be eligible for Cybersecurity, a student needs to have passed Data Engineering.
- In order to be eligible for Deep Learning, a student needs to have passed Data Mining.
- In order to be eligible for Data Forensics, a student needs to have passed Social Network Analysis for Data Scientist.
Homologation program
The homologation program is intended to bring the knowledge of the students coming from different studies to a comparable level, and to provide a good connection between a student’s knowledge and the contents of the core program. A deficiency on databases is the most frequent deficiency for direct admission. This master’s program offers a homologation program for students with this deficiency.
For more detailed information, read the relevant part of this document.
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