The programme overview is adopted 2026-02-11 by Dean of Education.

• AUTUMN TERM

  • Study period 1

    • Elective courses

      Course code and name	Module, credits/period	Block	Note	Examination	Re-examination (okt 2026 - aug 2027)
      DAT105 Computer architecture	Project 1.5 credits	A
      DAT105 Computer architecture	Examination 6 credits	A	S	Mon 26/10-2026 pm J	Thu 07/01-2027 pm J Tue 17/08-2027 pm J
      DAT350 Types for programs and proofs	Oral examination 7.5 credits	C	E
      DAT441 Advanced topics in machine learning	Written and oral assignments 3.5 credits	B
      DAT441 Advanced topics in machine learning	Examination 4 credits	B	S	Mon 26/10-2026 am J INSP	Tue 05/01-2027 am J INSP Mon 16/08-2027 pm J INSP
      DAT650 Formal methods in software development	Laboratory 2.5 credits	B
      DAT650 Formal methods in software development	Examination 5 credits	B	S	Thu 29/10-2026 am J	Mon 04/01-2027 pm J Mon 16/08-2027 pm J
      SSY340 Deep machine learning	Project 3 credits	A
      SSY340 Deep machine learning	Written and oral assignments 4.5 credits	A	S

  • Study period 2

    • Compulsory courses

      Course code and name	Module, credits/period	Block	Note	Examination	Re-examination (okt 2026 - aug 2027)
      DAT315 The computer scientist in society	Written and oral assignments 7.5 credits	A+	E

    • Elective courses

      Course code and name	Module, credits/period	Block	Note	Examination	Re-examination (okt 2026 - aug 2027)
      DAT278 Sustainable computing	Laboratory 1.5 credits	A+
      DAT278 Sustainable computing	Examination 6 credits	A+	S	Wed 13/01-2027 am J INSP	Wed 31/03-2027 am J INSP Thu 19/08-2027 am J INSP
      DAT415 Computability	Examination 4.5 credits	A		Wed 13/01-2027 am J	Fri 02/04-2027 am J Wed 18/08-2027 am J
      DAT415 Computability	Written and oral assignments 3 credits	A	S
      DAT450 Machine learning for natural language processing	Written and oral assignments 7.5 credits	A	S
      DAT566 Introduction to data science and AI	Written and oral assignments 4 credits	D
      DAT566 Introduction to data science and AI	Examination 3.5 credits	D	S	Tue 12/01-2027 pm J INSP	Thu 18/03-2027 am J INSP Fri 27/08-2027 pm J INSP
      DAT615 Neuro-symbolic AI	Examination 7.5 credits	D	E	Tue 12/01-2027 pm J	Wed 31/03-2027 pm J Wed 18/08-2027 pm J
      DAT655 Data privacy	Laboratory 3 credits	B
      DAT655 Data privacy	Examination 4.5 credits	B	S	Thu 14/01-2027 am J	Wed 31/03-2027 pm J Thu 26/08-2027 pm J
      EEN020 Computer vision	Project 3 credits	C
      EEN020 Computer vision	Written and oral assignments 4.5 credits	C	S
      TDA251 Algorithms, advanced course	Project 7.5 credits	C	E
      TDA352 Cryptography	Laboratory 1.5 credits	D
      TDA352 Cryptography	Examination 6 credits	D	S	Fri 15/01-2027 am J	Thu 01/04-2027 am J Fri 27/08-2027 am J
      TDA362 Computer graphics	Examination 6 credits	D+		Fri 15/01-2027 am J	Fri 02/04-2027 pm J Tue 24/08-2027 pm J
      TDA362 Computer graphics	Laboratory 1.5 credits	D+	S
      TDA452 Functional programming	Laboratory 3 credits	C
      TDA452 Functional programming	Examination 4.5 credits	C	S	Tue 12/01-2027 am J INSP	Thu 01/04-2027 pm J INSP
      TDA507 Computational methods in bioinformatics	Written and oral assignments 7.5 credits		E
      TEK010 Creating new business	Examination 7.5 credits	B	E	Mon 11/01-2027 am J INSP	Wed 31/03-2027 am J INSP Mon 23/08-2027 pm J INSP

• Diploma thesis

  Course code and name	Module, credits/period	Block	Note	Examination	Re-examination (okt 2026 - aug 2027)
  DATX60 Master's thesis in Computer science and engineering	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		*

• 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