Course programme 2021-2022 | EIT Digital Data Science entry 2021-2022 | Master Computer Science (CS): for students and staff

Academic year 2021-2022

Programme mentors: dr.ir. Maurice van Keulen

Name:

Student number:

Email address

At which university will you complete your exit year?

Is this your first time filling out a course form for this specialization?

Yes
Proceed by filling out the courses below.

No
If you want to change a previously submitted form, please briefly explain your changes in the field below, before proceeding by filling out the course form.

Brief explanation of the changes you're about to submit:

Ethics (mandatory)

191612680 Computer Ethics (1B, 5EC)

DS Core courses (mandatory)

201600070 Machine Learning 1 (1A, 5EC)

201200044 Managing Big Data (1B, 5EC)

201400174 Data Science (1B or 2A, 5EC)

201700080 Information Theory and Statistics (2A, 5EC)

Credits core DST + ethics

EC

DS Advanced courses (4 out of 6)

201600076 Foundations of Information Retrieval (1A, 5EC)

You cannot pick both NLP and Foundations of IR as advanced course. You can take both, but one will need to be part of the electives in your profiling space.

201600074 Natural Language Processing (1A, 5EC)

You cannot pick both NLP and Foundations of IR as advanced course. You can take both, but one will need to be part of the electives in your profiling space.

201600071 Machine Learning 2 (1B, 5EC)

201800177 Deep Learning – theory to practice (1B, 5EC)

191210910 Image Processing and Computer Vision (2A, 5EC)

201700081 Probabilistic programming (2A, 5EC)

192320111 Architecture of Information Systems (2B, 5EC)

Credits Advanced Courses

EC

Note: students are allowed to propose similar courses at the exit university to cover core or advanced courses. This has to be approved by the Programme mentor. If this applies to you, please give a short explaination below and name the UT course and overlapping course at the exit university (preferably including a link to the course description).

(If applicable) Mandatory core / advanced courses I will be covering during my exit year instead of at the UT:

Innovation and Entrepreneurship (mandatory):

201700180 Innovation and Entrepreneurial Finance for EIT students

201700119 Business Development Lab I

201700120 Business Development Lab II

201400613 EIT Summer School (external) (4 EC)

Credits mandatory I&E courses

EC

Profiling space: Data science students can specialize further in one or more of the following data science profiles below. Or pick addional Innovation&Entrepreneurship (I&E) electives.

a) specialist in specific kinds of data, such as natural language text, image data, geographic data, sensor data, networked data,
b) designer of smart services,
c) designer of data science algorithms,
d) multi-disciplinary researcher.

Profiling space: suggested electives

Profiling space: I&E electives

201700019 Brand Management

201800077 Bioresource Business Development & Management

201800079 Bioresource Supply Chain Management

201600155 Global Strategy and Business Development

194105070 Information Systems for the Financial Services Industry

201500008 Empirical Methods for Designers

Profiling space: Other courses (course code, course name):

If you proposed "other courses" above, please explain how these form a coherent DS&T programme targeting your specific individual goals

Credits Profiling space

EC

Total credits (EC):

EC