The Data Science and Technology (DST) master specialization connects the important fields of data science and smart services via information systems. In this master specialization you will get acquainted with and work on the following topics: big data, data analytics, information inference, context-aware applications, smart services. With data science, one learns how to dig for value in data by analyzing various data sources. With service engineering, one learns how to design services that effectively use system capabilities to satisfy user needs and requirements. Information systems that can use the results of data science to get more value out of data and become context-aware may turn traditional services into smart services. We already see applications of this in various domains such as pervasive health, well-being, sports, intelligent transportation, logistics, and business intelligence.
Core courses Cs
In addition to the programme below, you must also comply to the overall programme requirements of Computer Science by completing the following mandatory components:
Core courses DST
The following 4 courses are mandatory:
- 201600070 Machine Learning 1 (1A)
- 201200044 Managing Big Data (1B)
- 202300200 Data Science (1B, 2A)
- 201700080 Information Theory and Statistics (2A)
Advanced courses DST
At least 4 courses should be chosen out of the following:
- 202200103 Image Processing and Computer Vision (1A)
- 201600076 Foundations of Information Retrieval (1A) or 201600074 Natural Language Processing (1A)
- 202100258 FAIR Data Engineering (1A)*
- 201600071 Machine Learning 2(1B)
- 201800177 Deep Learning - From Theory to Practice (1B)
- 192320111 Architectures of Information Systems (1B)
- 201700081 Probabilistic programming (2A)
- 202100291 Ontology-Driven Conceptual Modeling (2B)*
*Students who started before 2024 and want to take any of these as an advanced course, contact master-coordinator-cs@utwente.nl.
profiling space: Data Science profiles
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
The following are suggested courses for the profiling space related to the above profiles:
- (a) 201600083 Advanced Information Retrieval (1B)
- (a) 201600081 Advanced Natural Language Processing (1B)
- (a) 201600075 Speech Processing (1B)
- (a) 201600082 Advanced Speech processing (2A)
- (a,b) 201700075 Internet of Things (1A)
- (a,b) 202100263 Linked Data and Semantic Web (2A)
- (a,b) 202300046 Privacy-Enhancing Technologies (1B)
- (a,b,c,d,e) 201300074 Research Experiments in Databases and Information Retrieval (REDI) (2B)
- (a,b,c,d,e) 202000029 Empirical and Design Science Research in Information Systems (2A)
- (a,b,c,d,e) 202200251 Capita Selecta DST (YEAR)
- (a,c) 201800222 Complex Networks (1A)
- (a,c) 201500040 Introduction to Biometrics (1A)
- (a,c) 201700364 Spatial Statistics (2B)
- (a,d) 202300201 Data Science Additional Topics (1B, 2A)
- (a,d) 201900060 3D modelling for City Digital Twins based on geospatial information
- (a,d) 193810020 Advanced Techniques for Signal Analysis (2A)
- (a) 201100254 Advanced Computer Vision and Pattern Recognition (2B)
- (b) 201400277 Enterprise Architecture (1A)
- (b) 202300064 Simulation (1A)
- (b) 202000027 Enterprise Security (1B)
- (b) 192376500 Business Process Integration lab (1B)
- (b) 192320501 Electronic Commerce (1B)
- (b) 201100051 Information Services (2A)
- (b) 192652150 Service-oriented Architecture Web Services (2A)
- (b,d) 202000028 Smart Industry (2B)
- (c) 191506103 Statistics and Probability (1A)
- (c) 192135310 Modeling and Analysis of Concurrent Systems (1A)
- (c) 201900115 Statistical Learning (1A)
- (c) 202001281 Signals with Information (1B)
- (c) 191520751 Graph Theory (note 4EC, 2A)
- (c) 192111092 Advanced Logic (2B)
- (c) 191571090 Time Series Analysis (2B)
- (c,d) 202100112 Graphical Models and Causality
- (d) 201700196 Advanced Discrete Event Simulation
- (d) 202001583 Sports Interaction Technology: Designing Interactive Systems for Sports (2B)
- (a,b,c,d) 202300336 Explainable AI (2B)
- (d) 202400120 Learning Analytics (1B)
- (b,c,d) Green Software development (1A)
- (c) other courses on fundamentals and algorithms of signal processing, stochastic processing, etc.
- (d) other courses on data analysis from fields like health/medicine, social sciences, business sciences, bio-informatics, engineering.
EIT Digital DS Entry year
The requirements for the specialization in Data Science and Technology can also be fulfilled by completing the DST programme at the EIT Digital Masterschool, one year of which takes place at the University of Twente. For the EIT Entry year, the same requirements exist in core and advanced courses as for regular DST. Additionally, there are some extra EIT requirements on Innovation and Entrepreneurship.
Mandatory core and advanced courses
- 191612680 computer ethics
- All DST core courses
- At least 4 DST advanced courses
Mandatory I&E courses EIT:
- 202100178 I&E Basics: Innovation Management for EIT
- 201700119 Business Development Lab I
- 201700120 Business Development Lab II
- 201400613 EIT Summer School (external) (4 EC)
Additional electives: See DST profiling courses or the following I&E elective courses:
- 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
EIT Digital DS Exit year
The requirements for the specialization in Data Science and Technology can also be fulfilled by completing the DST programme at the EIT Digital Masterschool, one year of which takes place at the University of Twente. Exit year students have completed a programme in the entry year at one of our partner universities. Nevertheless, students need to comply with our requirements for a core and advanced programme (see below). Students are expected to show how the courses in their programme at the entry university cover at least most of the core and advanced courses with at least the same amount of EC as the core and advanced courses at the UT. This has to be approved by the Programme mentor. The intention is that students minimize the number of core and advanced courses they still have to do in their exit year, so that sufficient room for electives remain. A grade transcript of the entry university needs to be provided in the end to prove that the covering courses have at least the same amount of ECs and have been passed.
Mandatory EXIT
The exit year counts at least 60 EC. It consists of the following mandotory parts:
- 191612680 Computer Ethics (5EC, 1B)
- 201800524 Research Topics EIT (4EC) and 201800525 I&E Study EIT (6EC)
- 192199978 Final Project (30 EC)
if not covered by the entry year
Courses to be largely covered by the entry year at another university (see explanation above), but if not the remaining courses need to be covered as part of the exit year:
- 201600070 Machine Learning 1 (1A)
- 201200044 Managing Big Data (1B)
- 202300200 Data Science (1B, 2A)
- 201700080 Information Theory and Statistics (2A) or 191506103 Statistics and Probability (1A)
PLus 3 out of:
- 202200103 Image Processing and Computer Vision (1A)
- 201600076 Foundations of Information Retrieval (1A) or 201600074 Natural Language Processing (1A)
- 202100258 FAIR Data Engineering (1A)
- 201600071 Machine Learning 2(1B)
- 201800177 Deep Learning - From Theory to Practice (1B)
- 192320111 Architectures of Information Systems (1B)
- 201700081 Probabilistic programming (2A)
- 202100291 Ontology-Driven Conceptual Modeling (2B)
Profiling/elective courses 'Data Science for Persona Information"
The below courses are specifically suggested for the EIT specialisation “Data Science for Persona Information”. These are course related to topics such as health and sports, wellbeing, biometrics and privacy. Though any other courses suggested for the profiling space of the Data Science & Technology programme are also allowed.
- 201500222 Technology for Health
- 201400353 Signals with Information
- 201500040 Introduction to Biometrics
- 201100254 Advanced Computer Vision & Pattern Recognition
- 201700075 Internet of Things
- 201400408 Complex Networks
- 202300336 Explainable AI
- 202001583 Sports Interaction Technology: Designing Interactive Systems for Sport