TU/e, UPM and UNS offer an entry-point program for the Data Science master. It consists of a set of Common Core Competences, a bases in Entrepreneurship and Electives. The following table summarises the TU/e entry-point program (for more information about the courses, visit OSIRIS Student Mobile (osiris-student.nl)):
Technical Common Base
Quartile | Code | Course | Credits |
1 | 2AMI10 | Foundations of process mining1 | 5 |
1 | 2IMM20 | Foundations of data mining | 5 |
1 | 2IMA10 | Advanced Algorithms | 5 |
2 | 2IMV20 | Visualization | 5 |
2 | 2DMT00 | Applied Statistics | 5 |
Core Electives (2 out of 5)
Quartile | Code | Course | Credits |
2 | 2IMA15 | Geometric algorithms2 | 5 |
3 | 2IMV10 | Visual computing project | 5 |
3 | 2DI70 | Statistical learning theory | 5 |
3 | 2AMM15 | Machine Learning Engineering | 5 |
4 | 2AMD15 | Big Data Management | 5 |
Innovation & entrepreneurship module
Quartile | Code | Course | Credits |
2 | 1ZM20 | Technology entrepreneurship | 5 |
3-4 | 1ZM150 | CTEM project | 10 |
3-4 | 2IEIT0 | Winter school | 1 |
2IEIT5 | Summer school | 4 | |
4 | 0LM150 | Entrepreneurship and corporate social responsibility | 5 |
1Students who took the course 2IIE0 Business process intelligence in their bachelor are not allowed to take 2IMI35 or 2AMI10 due to the overlap. 2Students should be advised that due to two Technical common base courses and one Innovation & entrepreneurship course in quartile 2, selecting 2IMA15 Geometric algorithms implies that you need to follow four courses in Q2.
Special track mentor: dr. Renata Medeiros de Carvalho (r.medeiros.de.carvalho@ ) tue.nl