Courses

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