Courses offered in the Fall semester (30 ECTS)
- Probability Theory & Introduction to Machine Learning TEL901 (7ECTS)
- Practical Data Science and Applications (7ECTS)
- Programming and Database Fundamentals (7ECTS)
- Optimization TEL714 (7ECTS)
- Research seminar/ Independent Study/Capstone project (2ECTS)
Courses offered in the Spring semester (30 ECTS)
- Machine Learning INF905 (Required, 7ECTS)
- Research seminar/ Independent Study/Capstone project (Required, 2ECTS)
- At least one from Group A
- Big Data Processing and Analysis INF903 (A, 7ECTS)
- Time Series Modeling and Analysis MTH901 (A, 7ECTS)
- Generative Artificial Intelligence INF726 (A, 7ECTS)
- Probabilistic Graphical Models and Inference Algorithms TEL908 (A, 7ECTS)
- Detection and Estimation Theory TEL902 (A, 7ECTS)
- At most two from Group B
- Advanced Concepts in Machine Learning and Pattern Recognition INF907 (B, 7ECTS)
- Quantum Machine Learning, Optimization and Applications PHY902 (B, 7ECTS)
- Quantum Information and Quantum Estimation MTH711 (B, 7ECTS)
- Secure Systems ECA901 (B, 7ECTS)
- Nonlinear Systems SYS901 (B, 7ECTS)
- Reinforcement learning and Dynamic Optimization INF723 (B, 7ECTS)
- Decision Making and Learning in Multiagent Worlds INF904 (B, 7ECTS)
More information about the courses can be found on TUC eclass