The programme overview is adopted 2025-02-24 by Dean of Education.

• AUTUMN TERM

  • Study period 1

    • Elective courses

      Course code and name	Module, credits/period	Block	Note	Examination	Re-examination (okt 2025 - aug 2026)
      DAT246 Empirical software engineering	Written and oral assignments 2.5 credits
      DAT246 Empirical software engineering	Examination 5 credits		S
      DAT441 Advanced topics in machine learning	Written and oral assignments 3.5 credits
      DAT441 Advanced topics in machine learning	Examination 4 credits		S
      DAT465 Causality and machine learning	Written and oral assignments 7.5 credits		E
      DAT625 Structured machine learning	Written and oral assignments 7.5 credits		E
      EEN100 Statistics and machine learning in high dimensions	Oral examination 6 credits
      EEN100 Statistics and machine learning in high dimensions	Project 1.5 credits		S
      FFR105 Stochastic optimization algorithms	Examination 7.5 credits		E
      FFR135 Artificial neural networks	Examination 7.5 credits		E
      MVE188 Computational methods for Bayesian statistics	Project 2 credits
      MVE188 Computational methods for Bayesian statistics	Examination 5.5 credits		S
      RRY025 Image processing	Examination 7.5 credits		E
      SSY340 Deep machine learning	Project 3 credits
      SSY340 Deep machine learning	Written and oral assignments 4.5 credits		S
      TIN093 Algorithms	Examination 7.5 credits		E
      TMA265 Numerical linear algebra	Examination 7.5 credits		E
      TMA882 High performance computing	Examination 7.5 credits		E

  • Study period 2

    • Elective courses

      Course code and name	Module, credits/period	Block	Note	Examination	Re-examination (okt 2025 - aug 2026)
      DAT450 Machine learning for natural language processing	Written and oral assignments 7.5 credits		S
      DAT570 Continuous optimization in data science	Written and oral assignments 7.5 credits		E
      EEN020 Computer vision	Project 3 credits
      EEN020 Computer vision	Written and oral assignments 4.5 credits		S
      MVE095 Options and mathematics	Examination 7.5 credits		E
      MVE172 Basic stochastic processes and financial applications	Laboratory 3 credits
      MVE172 Basic stochastic processes and financial applications	Examination 4.5 credits		S
      MVE190 Statistical learning with regression models	Examination 7.5 credits		E
      SSY130 Applied signal processing	Examination 7.5 credits		S
      SSY316 Advanced probabilistic machine learning	Project 7.5 credits		E
      TDA251 Algorithms, advanced course	Project 7.5 credits		E
      TDA357 Databases	Examination 4.5 credits
      TDA357 Databases	Laboratory 3 credits		S
      TDA507 Computational methods in bioinformatics	Written and oral assignments 7.5 credits		E
      TDA596 Distributed systems	Examination 6 credits
      TDA596 Distributed systems	Laboratory 1.5 credits		S
      TEK656 Creating technology-based ventures	Examination 7.5 credits		E
      TMA522 Large scale optimization	Examination (part A) 6 credits
      TMA522 Large scale optimization	Project (part B) 1.5 credits		S

• Diploma thesis

  Course code and name	Module, credits/period	Block	Note	Examination	Re-examination (okt 2025 - aug 2026)
  DATX60 Master's thesis in Computer science and engineering	Diploma thesis (part A) 30 credits		*
  MVEX60 Master's thesis in Mathematics	Diploma thesis (part A) 30 credits		*
  DATX05 Master's thesis in Computer science and engineering	Diploma thesis 30 credits		*
  DATX60 Master's thesis in Computer science and engineering	Diploma thesis (part B) 30 credits		*
  MVEX03 Master's thesis in Mathematics	Diploma thesis 30 credits		*
  MVEX60 Master's thesis in Mathematics	Diploma thesis (part B) 30 credits		*

• DIG: Digital examination is an examination written in the Inspera system. The student will bring their own computer and access the exam via Safe exam browser.
• S: Final grade. All module grades are reported before the final grade for the course can be reported.
• E: The only module in the course. Module grade and grade for the course are reported at the same time.
• *: The module includes education in another period