DAS in Data Science

Students

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 page SDSC), 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 Download further courses to choose from a list (PDF, 127 KB). 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:

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

A Master's degree in computer science, data science, mathematics, statistics, physics, mechanical engineering, electrical engineering or in a related field, as well as existing work experience.
Applicants must suggest a Download study plan (DOCX, 51 KB) and in particular indicate their chosen specialization track.

The following documents must be filled in and submitted:

  • Fully completed Online Application of the School for Continuing Education with an explanation of 150 - 250 words in section "Personal Motivation";
  • Copy of the Master's degree in German or English (qualifying degrees see above "Admission Requirements");
  • Copy of the transcript in German or English;
  • Up-to-date CV or Resume in German or English;
  • Download Study plan (DOCX, 51 KB), filled in completely and correctly;
  • Further documents required by the School for Continuing Education

Optional documents:

  • English certificate, level C1;
  • Reference letters

Application
ETH Zürich
School for Continuing Education
HG E 17-18.5
Rämistr. 101
8092 Zürich
Tel. +41 44 632 56 59
E-mail:
Application: online

Application period:
- Autumn semester: 1 April until 30 April
- Spring semester: 1 October until 31 October

Admission
Your application will be reviewed by the Admission Committee of the Certificate Programme. Admission requires sufficient scientific fundamental knowledge and pre-knowledge or working experience in the area of data science. The decision is communicated in writing. There is no entitlement to admission.

CHF 12'000.- (incl. CHF 660.- one-time payable semester fee)

Passed courses within the DAS in Data Science programme are accountable for the CAS in Computer Science and the CAS/DAS in Applied Statistics, and vice versa, if applicable. Thus, in compliance with the respective programmes and ETH regulations, it is possible to change from one programme to the other without losing accomplished ECTS points for courses that are accepted as part of the programmes.

Prof. Gunnar Rätsch
Prof. Helmut Bölcskei
Prof. Nicolai Meinshausen
Dr. Ghislain Fourny

Is the programme also offered as a distance learning programme?
No, the DAS is offered only on-site at ETH.

Are there courses offered in the evenings or during the weekends?
No, all courses take place on workdays during the day.

What is the estimated workload?
One credit point equals approximately 30 hours of studying.

Where do I find the timetable?
There is no predefined timetable. Each student compiles his/her own timetable. The courses of the current and the previous semesters can be found on www.vvz.ethz.ch. Usually, the times of the courses remain the same.

Are there additional costs to bare if the regular programme duration of two semester will be exceeded?
No, in this case there are no additional costs. It is irrelevant whether a student finishes the programme in two or four semesters

Contact

Tamlyn Altmann

ETH Zurich
Universitätstrasse 6
CAB F 64.1
8092 Zurich
Switzerland

School for Continuing Education
  • +41 44 632 56 59
  • Website

ETH Zurich
Rämistrasse 101
HG E 17-18.5
8092 Zurich
Switzerland

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