Outline for Master's Programme in Computer Science

Masterprogram i datavetenskap

Specialisation: Computer Science (Datavetenskap)

The following designations are used:
G1N - First cycle, has only upper-secondary level entry requirements
G1F - First cycle, has less than 60 credits in first-cycle courses as entry requirements
G2F - First cycle, has at least 60 credits in first-cycle courses as entry requirements
A1N - Second cycle, has only first-cycle courses as entry requirements, at least 120 credits
A1F - Second cycle, has second-cycle courses as entry requirements
A1E - Second cycle, contains degree project for Master of Arts/Master of Science (60 credits)
A2E - Second cycle, degree project for Master of Arts/Master of Science (120 credits)

Semester 1

Courses are selected freely from below, provided that eligibility requirements are fulfilled. Study counselling is provided so that the selected courses together fullfill graduation requirements.

If the number of students who want to attend the following courses are few, the courses might be cancelled or given with different teaching approach: 1DL442 and 1DL450.

Period 1

1DL010 Artificial Intelligence and 1DL340 Artificial Intelligence cannot be included in the same degree.

1DL442 cannot be included in the same degree as any of the the courses 1DL441 Combinatorial Optimisation using Constraint Programming, 1DL451 Modelling for Combinatorial Optimisation, 1DL448 Modelling for Combinatorial Optimisation or 1DL449 Constraint Modelling for Combinatorial Optimisation.

1DL360 Data Mining I and 1DL370 Data Mining cannot be included in the same degree.

Period 2

1DL441 Combinatorial Optimisation using Constraint Programming and 1DL451 Modelling for combinatorial optimisation cannot be included in the same degree. 1DT004 Real Time Systems and 1DT063 Real Time System I cannot be included in the same degree.

1DL442 cannot be included in the same degree as any of the the courses 1DL441 Combinatorial Optimisation using Constraint Programming, 1DL451 Modelling for Combinatorial Optimisation, 1DL448 Modelling for Combinatorial Optimisation or 1DL449 Constraint Modelling for Combinatorial Optimisation.

Semester 2

Students who select a course of 7.5 credits are recommended to combine two courses of 7.5 credts in the same period.

Period 3

1DT095 Wireless Communication and Networked Embedded Systems and 1DT103 Wireless Communication and Networked Embedded Systems cannot be included in the same degree.

Period 4

Students who select a course of 7.5 credits are recommended to combine two courses of 7.5 credts in the same period.

The student who intends to obtain A Degree of Master (One Year) shall take the course Degree project D below.

Optional course in English during period 13 or 21

1DT095 Wireless Communication and Networked Embedded Systems and 1DT103 Wireless Communication and Networked Embedded Systems cannot be included in the same degree.

Semester 3

Semester 3 and 4
The student can, during semester 3, select among the courses offered for semester 1 (period 1 and 2), provided that the prerequisite requirements are fulfilled. It is also possible to elect one of the courses below. The student is expected, during semester 3-4, to elect one of the courses 1DT540 Degree project E in Computer Science 30 credits or 1DT550 Degree project E in Computer Science 45 credits. Degree project course cannot be started by a student who is studying the course 1DT054 Project DV during the same semester.

Students who select a course of 7.5 credits are recommended to combine two courses of 7.5 credts in the same period.

If the number of students who want to attend the following course are few, the course might be cancelled or given with different teaching approach: 1DT059

Period 1

1DL010 Artificial Intelligence and 1DL340 Artificial Intelligence cannot be included in the same degree.
1RT003 Advanced Probabilistic Machine Learning and 1RT705 Advanced Probabilistic Machine Learning cannot be included in the same degree.
1DL370 Data Mining cannot be included in the same degree as 1DL360 Data Mining I, 1DL460 Data Mining II or 1DL025 Data Mining.

Period 2

Semester 4

Outline revisions

Outline(s) part of syllabus from Autumn 2022:

  • Latest outline for the specialisation Computer Science (applies from Autumn 2022)
Last modified: 2022-04-26