Master's Programme in Computer Science – Computer Science

120 credits

Outline, TDV2M, DATA

Code
TDV2M
Specialisation code
DATA
Finalised by
The Faculty Board of Science and Technology, 6 November 2024
Registration number
TEKNAT 2023/166

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.

Period 1

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

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

1DL450 is given in terms of resources.

Period 2

1DT004 and 1DT063 cannot be included in the same degree.

1DL451 cannot be included in the same degree as any of 1DL441, 1DL442, 1DL448 or 1DL449.

1DL305 cannot be included in the same degree as 1DL301.

Semester 2

Period 3

1MD046 cannot be included in the same degree as 1MD002 and 1MD003.

1DT194 Wireless Communication and Networked Embedded Systems cannot be included in the same degree as 1DT095 Wireless Communication and Networked Embedded Systems and 1DT103 Wireless Communication and Networked Embedded Systems.

1DT116 cannot be included in the same degree as 1DL550.

1TD062 cannot be included in the same degree as any of 1DL560, 1TD351, 1TD480 and 1TD064.

Period 4

1DL705 and 1DL710 is given in terms of resources.

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

1DT195 and 1DT103 cannot be included in the same degree.

1DT114 cannot be included in the same degree as 1DT098.

1DT076 cannot be included in the same degree as 1DT075.

1MD043 cannot be included in the same degree as 1MD044.

Semester 3

Semester 3 and 4

In semester 3, the student can choose from the above for semester 1 (periods 1 and 2), provided that the prerequisites are met. It is also possible to take the following courses. During semester 3-4, the student is expected to take the course 1DT540, 30 credits or 1DT550, 45 credits. 

In case of few participants or lack of resources, the following courses can be cancelled or given with another form of teaching: 1DL465, 1DL705, 1DL710, 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.

1TD054 cannot be included in the same degree as 1TD055.

Period 2

Semester 4

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