Description de la formation

Diploma of Advanced Studies (DAS) ist eine Nachdiplomausbildung der Hochschulen und entspricht mindestens 30 ECTS-Punkten. Dieses DAS verlangt 35 bis 45 ECTS-Punkte.

The interdisciplinary programme conveys knowledge across the fields of mathematics, computer science and electrical engineering. This includes all levels of abstraction of technologies relevant to data science, from hardware and electronics, clusters and networks, through big data systems, to machine learning, algorithms and statistics. It also offers insights into political, societal, legal, ethical and privacy aspects of data science.

The participants are taught how to understand and use complex data management (storage, querying, infrastructures, networks etc.) and analysis techniques (machine learning, statistics etc.) in order to utilise them in a broad range of applications.

Structure and Format

The DAS in Data Science split over a foundations course, a specialization track, a capstone project, and further courses to choose from. The capstone project gives an opportunity to put the acquired knowledge into practice on real data sets. In order to achieve the basic knowledge the foundation course must be taken in the first semester. At least 12 ECTS have to be acquired in the specialization track before the start of the capstone project.

Foundation course (min. 6 ECTS). One of:

• Introduction to Estimation and Machine Learning (6 ECTS - autumn semester)
• Introduction to Machine Learning (8 ECTS - spring semester)
• Computational Statistics (8 ECTS - spring semester)

Specialization track (mind. 12 ECTS): Courses must be taken from one of the following tracks.

• Hardware for Machine Learning
• Image Analysis and Computer Vision
• Neural Information Processing
• Statistics
• Machine Learning and Artificial Intelligence
• Big Data Systems

Capstone Project (8 ECTS)

Total workload: approx. 1'050 hours

Plan de la formation

1 ECTS-Kreditpunkt entspricht einem Aufwand von 25-30 Arbeitsstunden.