The academic year is divided to four periods. The current locations of Data Science courses are given below.
Year 1, Period 1 |
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Year 1, Period 2 |
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Year 1, Period 3 |
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Year 1, Period 4 |
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Intensive period and summer courses |
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Year 2, Period 1 |
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Year 2, Period 2 |
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Year 2, Period 3 |
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Year 2, Period 4 |
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Elective courses
List A of elective courses on Period 1
- Computational Statistics I
- Design and Analysis of Algorithms
- Introduction to Artificial Intelligence (highly recommended for year 1)
- Introduction to Big Data Management
- Inverse Problems 1: Convolution and Deconvolution
- Data Science Project II (available in year 2)
- Data Science Seminar II (available in year 2)
List B of elective courses on Period 2
- String Processing Algorithms* / Data Compression Techniques** (alternating years)
- High Dimensional Statistics** (every other year)
- Research Project in Cognitive Science (can be used as Data Science Project; year 2; term/teaching period varies)
- Data Science Project II (continued, year 2)
- Data Science Seminar II (continued, year 2)
* Given every other academic year (given in 2018-19)
** Given every other academic year (given in 2019-20)
List C of elective courses on Period 3
- Cloud and Edge Computing
- Cognition & Brain Function
- Network Analysis
- Scientific Computing III* / Tools of High Performance Computing** (alternating years)
* Given every other academic year (given in 2018-19)
** Given every other academic year (given in 2019-20)
List D of elective courses on Period 4
- Spatial Modelling and Bayesian Inference* / Advanced Bayesian Inference** (alternating years)
- Advanced Course in Machine Learning
- Interactive Data Visualization
- Philosophy of Artificial Intelligence
- Scientific Computing III* (continued) / Tools of High Performance Computing** (continued; alternating years)
* Given every other academic year (given in 2018-19)
** Given every other academic year (given in 2019-20)
Additional courses
Every academic year, the programme offers also some additional courses. These courses cannot, however, counted as a part of the 20 credits of specialisation studies in Data Science in the current degree structure.
This kind of additional courses in Academic year 2019-2020 are the following:
- Computer Vision (Period 1; year 2; will become elective in the future)
- Deep Learning (possible given in Spring 2020; will become elective in the future)
- Introduction to Information Retrieval (Period 3; will become elective in the future)
- Trustworthy Machine Learning (Period 2; year 2; will become elective in the future)
- Multidisplinary course: Computational Analysis of the Changing World (intensive course at the beginning of Period 3)