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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:

Advanced courses

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

  • 201600071 Advanced Machine Learning (1B)
  • 201600076 Foundations of Information Retrieval (1A, only in 2019-2020 1B)
  • 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 Information Retrieval (1B, only in 2019-2020 2A)
(a) 201600081 Advanced Natural Language Processing (1B)
(a) 201600082 Advanced Speech processing (2A)
(a) 201100254 Advanced Computer Vision and Pattern Recognition (2B)
(a,b) 201700075 Internet of Things (1A)
(a,b) 201500042 Privacy-Enhancing Technologies (2B) 
(a,c) 201800222 Complex Networks (1A)
(a,c) 201700364 Spatial Statistics (2B)
(a,d) 193810020 Advanced Techniques for Signal Analysis (2A)
(a,d) 201800063 Traffic Forecasting and Analysis (1B)
(b) 192376500 Business Process Integration Lab (1B)
(b) 192320501 Electronic Commerce (1B) 
(b,d) 201600028 Telemedicine and Data Analysis for Monitoring (1B)
(c) 201800177 Deep Learning - From Theory to Practice (1B) 
(c) 192135310 Modeling and Analysis of Concurrent Systems 1 (1A) 
(c) 191571090 Time Series Analysis (2B) 
(c) 201400353 Signals with Information (1B) 
(c) 191520751 Graph Theory (2A)
(c) 192111092 Advanced Logic (2B) 
(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.

PROGRAMME MENTORs M. van Keulen (Maurice)
Programme mentor DST

dr. N. Strisciuglio (Nicola)
Programme mentor DST

Study advisor