DAS in Data Science

The DAS in Data Science provides a programme in continuous education that covers the field of data science, with an interdisciplinary viewpoint.

The DAS programme in Data Science offered by ETH Zurich focuses on the management, analysis and utilization of large and complex data sets.

The interdisciplinary programme 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. The participants learn 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.

Given the broad range of research at ETH on data science related topics, the DAS in Data Science allows participants to choose from a diverse set of graduate courses. The programme is co-hosted by the Department of Computer Science (D-INFK), the Department of Information Technology and Electrical Engineering (D-ITET), and the Department of Mathematics (D-MATH). It is also supported by the Swiss Data Science Center (external pageSDSCcall_made), which connects academia, industry, and the public sector to address current challenges in data science.

The powerful capabilities of Data Science will dramatically shape our future. The programme therefore also offers insights into political, societal, legal, ethical and privacy aspects of Data Science.

The target audience for the programme are professionals with work experience and holding a Master's degree in computer science, data science, mathematics, statistics, physics, mechanical engineering, electrical engineering or in a related field.

Participants of the programme will learn about state-of-the-art methods and technologies in the field of data science. Graduates of the programme will have a solid basis in the theoretical foundations of data science as well as in the techniques and methodologies required in practical applications.

The DAS in Data Science consists in total of 35 to 45 ECTS split over a foundations course, a specialization track, a capstone project, and Downloadfurther courses to choose from a list (PDF, 126 KB)vertical_align_bottom. 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)

The programme is intended for part-time study programme and starts every semester. The regular study programme duration is 2 semesters, with a leeway of 2 additional semesters. Applicants have to submit a study plan designed over at most 3 semesters as part of their application. Exceptions can be made on request, in which case a motivation must be provided with the application.

Total workload: approx. 1'050 hours, min. 1 year

Course language: English