Data Science and Technology (DST)

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, intelligent transportation, logistics, and business intelligence.

specialization courses

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

The following 4 courses are mandatory:

  • 201200044 Managing Big Data (1B)
  • 201400174 Data Science (1B, 2A)
  • 201600070 Basic Machine Learning (1A)
  • 201700080 Information Theory and Statistics (2A)

Advanced courses

At least 4 courses should be chosen out of the following:

  • 201600071 Advanced Machine Learning (1B)
  • 201600076 Foundations of Information Retrieval (1A)
  • 192652150 Service-oriented Architecture with Web services (2A)
  • 192320111 Architectures of Information Systems (2B)
  • 201300074 Research Experiments in Databases and Information Retrieval (2B)
  • 201700081 Probabilistic programming (2A)

profiling spacE

Requirements: No additional requirements apply, but the data science student is suggested to further specialize in one or more of the following data science profiles: 

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:
(a) 201600074 Natural Language Processing (1A) 
(a) 201600075 Speech Processing(1B) 
(a) 191210910 Image Processing and Computer Vision (2A) 
(a) 201600083 Advanced Research Project in Information Retrieval (1B) 
(a,b) 201500042 Privacy-Enhancing Technologies (2B) 
(a,c) 201400408 Complex Networks (2A) 
(a,c) 201400229 Algorithms for Geographic Data (2A) 
(b) 192320220 Advanced Architectures of Information Systems (1AB) 
(b) 192320501 Electronic Commerce (1B) 
(b,d) 201600028 Telemedicine and Data Analysis for Monitoring (1B) 
(c) 192135310 Modeling and Analysis of Concurrent Systems 1 (1A) 
(c) 191571090 Time Series Analysis (1A) 
(c) 201400353 Signals with Information (1B) 
(c) 191520751 Graph Theory (2A) 
(c) other courses on fundamentals and algorithms of signal processing, stochastic processing, etc.
(d) 193810020 Advanced Techniques for Signal Analysis (2A)
(d) other courses on data analysis from fields like health/medicine, social sciences, business sciences, bio-informatics.


Maurice van Keulen, programme mentor

Dr.ir. M (Maurice) van Keulen.
Room: Zilverling 2013;
Phone: 53 489 3688;
Email: m.vankeulen@utwente.nl.

The Service, Cybersecurity and Safety (SCS) group and the Database (DB) group are jointly responsible for the DST master specialization. The DST master specialization is related to the Twente Graduate School programme on Services Science. Students from DST can participate in the Services Science programme once they are admitted and comply with the additional constraints as described in: www.utwente.nl/en/education/post-graduate/tgs/programmes/ctit/services-science/.