Data Science & Technology is a two-year Master of Science programme with a total of 120 credits.
DATA SCIENCE & TECHNOLOGY PROGRAMME STRUCTURE
A typical first-year timetable includes five required courses (25 credits), electives related to the specialization (25 credits) and a number of electives in other disciplines (10 credits). In the second year, you will either take additional specialization courses or do an internship (20 credits). The remaining 40 credits in the second year are devoted to the graduation project, which involves a preliminary research exploration and literature study, called Research Topics, and the Master’s thesis.
Click on the course to find out the course details.
MANDATORY (45 EC):
BASIC COURSES (20 EC):
- Architecture of Information Systems (5 EC)
- Service-oriented architecture with web services (5 EC)
- Managing Big Data (5 EC)
- Data Science (5 EC)
ADVANCED COURSES (25-45 EC):
- Graph Theory (5 EC)
- Empirical Research & Data Analysis (5 EC)
- Secure Data management (5 EC)
- Advanced Design of Software Architectures - Model Driven Engineering (5 EC)
- Information Retrieval (5 EC)
- Introduction to Machine Learning (5 EC)
- Advanced Machine Learning (5 EC)
- Advanced Architecture of Information Systems (5 EC)
- Electronic Commerce (5 EC)
- Design Science Methodology (5 EC)
- Software Management (5 EC)
- Research Experiments with Data and Information Retrieval (5 EC)
- Capita selecta specialization (5 EC)
Other courses chosen from any specialization to obtain the minimally required number of 120 credits
More specific information can be found on the programme website for enrolled students.