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

A2E - Second cycle, degree project for Master of Arts/Master of Science (120 credits)

Semester 1

Period 1

• Introduction to Data Science, 5 of 10 credits (1MS041) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Mathematics A1N
• Data, Ethics and Law, 5 credits (1DL002) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Human-Computer Interaction A1N, Image Analysis and Machine Learning A1N

Eligible courses:

• Computer Programming II, 5 credits (1TD722) Main field(s) of study and in-depth level: Computer Science G1F, Technology G1F
• Algorithms and Data Structures I, 5 credits (1DL210) Main field(s) of study and in-depth level: Computer Science G1F, Technology G1F
• Modelling for Combinatorial Optimisation, 5 credits (1DL451) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N
• Scientific Computing for Data Analysis, 5 credits (1TD352) Main field(s) of study and in-depth level: Computer Science G2F, Technology G2F
• Linear Algebra for Data Science, 5 credits (1MA330) Main field(s) of study and in-depth level: Data Science A1N, Mathematics A1N
• Probability Theory II, 5 credits (1MS036) Main field(s) of study and in-depth level: Mathematics G2F
• Software Engineering and Project Management, 5 credits (1DL251) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Technology A1N
• Mathematical Modelling of Football, 5 credits (1RT001) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Image Analysis and Machine Learning A1N, Mathematics A1N

Period 2

• Introduction to Data Science, 5 of 10 credits (1MS041) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Mathematics A1N
• Statistical Machine Learning, 5 credits (1RT700) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Image Analysis and Machine Learning A1N, Mathematics A1N, Technology A1N

Eligible courses:

• Database Design I, 5 credits (1DL301) Main field(s) of study and in-depth level: Computer Science G2F, Sociotechnical Systems G2F, Technology G2F
• Optimisation, 5 credits (1TD184) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Data Science A1N, Technology A1N
• Several Variable Calculus for Data Science, 5 credits (1MA334) Main field(s) of study and in-depth level: Mathematics A1N
• Foundations of Mathematical Analysis, 5 credits (1MA322) Main field(s) of study and in-depth level: Mathematics G2F
• Inference Theory II, 5 credits (1MS037) Main field(s) of study and in-depth level: Mathematics G2F
• Database Design II, 5 credits (1DL400) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Technology A1N

Semester 2

Period 3

• Data Engineering I, 7.5 credits (1TD069) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Data Science A1N, Technology A1N
• Theoretical Foundations for Data Science, 7.5 credits (1MS047) Main field(s) of study and in-depth level: Data Science A1F, Mathematics A1F
• Computer-Intensive Statistics and Data Mining DS, 7.5 credits (1MS043) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Mathematics A1N
• Bayesian Statistics DS, 7.5 credits (1MS031) Main field(s) of study and in-depth level: Mathematics A1N

1MS043 is given even years

1MS031 is given odd years

Period 4

• Applied Linear Algebra for Data Science, 7.5 credits (1TD060) Main field(s) of study and in-depth level: Computer Science A1F, Data Science A1F
• Reinforcement Learning, 7.5 credits (1RT747) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Embedded Systems A1N, Image Analysis and Machine Learning A1N
• Mathematical Topics in Data Science, 7.5 credits (1MS046) Main field(s) of study and in-depth level: Data Science A1F, Mathematics A1F

Semester 3

Period 1

• Advanced Probabilistic Machine Learning, 7.5 credits (1RT003) Main field(s) of study and in-depth level: Computer Science A1F, Image Analysis and Machine Learning A1F, Mathematics A1F
• Artificial Intelligence, 7.5 credits (1DL010) Main field(s) of study and in-depth level: Computer Science A1N
• Data Mining, 7.5 credits (1DL370) Main field(s) of study and in-depth level: Computer Science A1F, Data Science A1F
• Theoretical Statistics DS, 7.5 credits (1MS039) Main field(s) of study and in-depth level: Data Science A1N, Mathematics A1N

1MS039 is given even years

Period 2

• Project in Data Science, 15 credits (1DL507) Main field(s) of study and in-depth level: Data Science A1F, Technology A1F

Or

• Project in Data Science, 7.5 credits (1DL505) Main field(s) of study and in-depth level: Data Science A1F
• Scientific Visualisation, 7.5 credits (1MD140) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Image Analysis and Machine Learning A1N

Semester 4

• Degree Project E in Data Science, 30 credits (1DL510) Main field(s) of study and in-depth level: Data Science A2E