Study programme for |
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MPDSC - DATA SCIENCE AND AI, MSC PROGR
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Academic year: 2021/2022 |
DATA SCIENCE OCH AI, MASTERPROGRAM |
The Study programme is adopted 2019-02-21 by Dean of Education |
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First Year |
Explanations
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|
|
Dept |
Course code |
Module code |
Note |
Block |
Course name, Module type |
Extent/ period |
Regular
exam |
Re-sit examination Oct -21 up to Aug -22 |
|
AUTUMN TERM |
Study period 1 |
Compulsory courses
|
37 |
DAT405 |
0119 E |
|
|
Introduction to data science and AI, Written and oral assignments |
7,5 |
|
|
|
11 |
TMA947 |
0203 S |
|
|
Nonlinear optimisation, Examination |
6,0 |
28/10-2021 am J
|
04/01-2022 am J Change
|
16/08-2022 am J Change
|
Elective courses
|
37 |
DAT246 |
0214 S |
|
A |
Empirical software engineering, Examination |
5,0 |
25/10-2021 pm J
|
05/01-2022 am L Change
|
23/08-2022 pm J
|
30 |
FFR105 |
0199 E |
|
D |
Stochastic optimization algorithms, Examination |
7,5 |
27/10-2021 pm J
|
03/01-2022 am J
|
25/08-2022 am J
|
11 |
MVE187 |
0117 |
|
|
Computational methods for Bayesian statistics, Project |
2,0 |
|
|
|
70 |
RRY025 |
0107 E |
1) 2) 3) |
C+ |
Image processing, Examination |
7,5 |
28/10-2021 pm J
|
04/01-2022 pm J
|
19/08-2022 pm J
|
32 |
SSY340 |
0217 S |
|
A |
Deep machine learning, Written and oral assignments |
4,5 |
|
|
|
37 |
TIN093 |
0114 E |
4) |
A |
Algorithms, Examination |
7,5 |
23/10-2021 pm L
|
|
25/08-2022 pm J
|
11 |
TMA881 |
0101 E |
1) |
|
High performance computing, Examination |
7,5 |
Contact examiner
|
Contact examiner
|
Contact examiner
|
|
Study period 2 |
Compulsory courses
|
11 |
MVE550 |
0118 |
|
B |
Stochastic processes and Bayesian inference, Examination |
6,0 |
08/01-2022 am J
|
13/04-2022 am J
|
22/08-2022 am J
|
Elective courses
|
37 |
DAT450 |
0120 S |
1) 3) |
A |
Machine learning for natural language processing, Written and oral assignments |
7,5 |
|
|
|
32 |
EEN020 |
0218 S |
|
C |
Computer vision, Written and oral assignments |
4,5 |
|
|
|
11 |
MVE172 |
0120 |
1) |
|
Basic stochastic processes and financial applications, Laboratory |
3,0 |
|
|
|
11 |
MVE190 |
0108 E |
|
|
Linear statistical models, Examination |
7,5 |
11/01-2022 pm J
|
12/04-2022 pm J Change
|
18/08-2022 pm J Change
|
32 |
SSY316 |
0120 E |
1) |
B |
Advanced probabilistic machine learning, Project |
7,5 |
|
|
|
37 |
TDA357 |
0106 |
4) |
D+ |
Databases, Examination |
4,5 |
12/01-2022 pm J
|
|
25/08-2022 pm J
|
37 |
TDA507 |
0113 E |
|
A |
Computational methods in bioinformatics, Written and oral assignments |
7,5 |
|
|
|
37 |
TDA596 |
0207 S |
|
C |
Distributed systems, Laboratory |
1,5 |
|
|
|
11 |
TMA521 |
0197 S |
1) |
|
Large scale optimization, Examination |
7,5 |
14/01-2022 pm J
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12/04-2022 am J Change
|
23/08-2022 pm J Change
|
|
|
SPRING TERM |
Study period 3 |
Compulsory courses
|
37 |
DAT410 |
0119 E |
|
D |
Design of AI systems, Written and oral assignments |
7,5 |
|
|
|
Elective courses
|
37 |
DAT340 |
0217 S |
4) 5) |
B |
Applied Machine Learning, Written and oral assignments |
3,5 |
|
|
|
32 |
SSY098 |
0219 S |
1) 2) |
C |
Image analysis, Laboratory |
4,0 |
|
|
|
37 |
TDA233 |
0220 S |
4) 5) |
B |
Algorithms for machine learning and inference, Examination |
4,5 |
15/03-2022 pm J
|
10/06-2022 am J
|
24/08-2022 am J
|
37 |
TDA357 |
0206 S |
4) |
|
Databases, Laboratory |
3,0 |
|
|
|
37 |
TIN093 |
0114 E |
4) |
A+ |
Algorithms, Examination |
7,5 |
16/03-2022 am J
|
|
25/08-2022 pm J
|
|
Study period 4 |
Elective courses
|
37 |
DAT340 |
0117 |
4) |
C |
Applied Machine Learning, Examination |
4,0 |
Contact examiner
|
Contact examiner
|
Contact examiner
|
37 |
DAT440 |
0120 |
1) |
B |
Advanced topics in machine learning, Written and oral assignments |
3,5 |
|
|
|
37 |
DAT470 |
0121 |
4) |
A |
Computational techniques for large-scale data, Written and oral assignments |
4,5 |
|
|
|
37 |
DAT475 |
0121 |
4) |
D |
Advanced databases, Written and oral assignments |
3,0 |
|
|
|
11 |
MVE165 |
0107 S |
|
|
Linear and integer optimization with applications, Examination |
7,5 |
02/06-2022 am J
|
03/01-2022 am J Change
|
25/08-2022 pm J Change
|
11 |
MVE441 |
0220 S |
4) |
|
Statistical learning for big data, Take-home examination |
6,0 |
|
|
|
11 |
TMS016 |
0101 S |
1) |
|
Spatial statistics and image analysis, Examination |
7,5 |
01/06-2022 pm J
|
Contact examiner
|
24/08-2022 pm J Change
|
|
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1) Compulsory elective: Compulsory elective course. (DAT440, DAT450, DAT465, MVE172, RRY025, SSY098, SSY316, TMA521, TMA881, TMS016, TMS088): 2 of stated courses are required for the degree |
2) Overlap: Only one of the marked courses can be included in the degree (RRY025, SSY098) |
3) Recommendation: The course is normally followed during the second year of the Masters programme (DAT450, RRY025) |
4) Compulsory elective: Compulsory elective course. (DAT340, DAT470, DAT475, MVE095, MVE441, TDA233, TDA357, TIN093): 2 of stated courses are required for the degree |
5) Overlap: Only one of the marked courses can be included in the degree (DAT340, TDA233) |
* Element includes education in another quarter |
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. |
DIG Digital examination is a examination written in the Inspera system. The student will bring their own computer and access the exam via Safe exam browser |
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