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
• Linear Algebra for Data Science, 5 credits (1MA330) Main field(s) of study and in-depth level: Data Science A1N, Mathematics A1N

Eligible course:

• Modelling for Combinatorial Optimisation, 5 credits (1DL451) Main field(s) of study and in-depth level: Computer Science A1N, Data Science 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
• Database Design I, 5 credits (1DL301) Main field(s) of study and in-depth level: Computer Science G2F, Sociotechnical Systems G2F, Technology G2F

Eligible course:

• Optimisation, 5 credits (1TD184) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Data Science A1N, Technology A1N

Semester 2

Period 3

• Data Engineering I, 5 credits (1TD169) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Data Science A1N, Technology A1N
• Deep Learning, 5 credits (1RT720) Main field(s) of study and in-depth level: Computer Science A1F, Data Science A1F, Image Analysis and Machine Learning A1F, Technology A1F
• Foundations of Data Science, 5 of 10 credits (1MS048) Main field(s) of study and in-depth level: Data Science A1F, Mathematics A1F
• Bayesian Statistics, 5 of 10 credits (1MS900) Main field(s) of study and in-depth level: Data Science A1N, Mathematics A1N

1MS900 is given every odd year.

• Scientific Computing for Data Analysis, 5 credits (1TD352) Main field(s) of study and in-depth level: Computer Science G2F, Technology G2F

Period 4

• Reinforcement Learning, 5 credits (1RT745) Main field(s) of study and in-depth level: Data Science A1N, Embedded Systems A1N, Technology A1N
• Foundations of Data Science, 5 of 10 credits (1MS048) Main field(s) of study and in-depth level: Data Science A1F, Mathematics A1F
• Topics in Data Science, 5 credits (1MS050) Main field(s) of study and in-depth level: Data Science A1F, Mathematics A1F
• Bayesian Statistics, 5 of 10 credits (1MS900) Main field(s) of study and in-depth level: Data Science A1N, Mathematics A1N
• Analysis of Time Series, 10 credits (1MS014) Main field(s) of study and in-depth level: Data Science A1N, Financial Mathematics A1N, Mathematics A1N
• Data Security and Privacy, 5 credits (1DT114) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Technology A1N
• Degree Project D in Data Science, 15 credits (1DL390) Main field(s) of study and in-depth level: Data Science A1E

Semester 3

Period 1

• Project in Data Science, 5 of 10 credits (1DL508) Main field(s) of study and in-depth level: Data Science A1F
• Advanced Probabilistic Machine Learning, 5 credits (1RT705) Main field(s) of study and in-depth level: Computer Science A1F, Data Science A1F, Mathematics A1F, Technology A1F
• Artificial Intelligence, 5 credits (1DL340) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Technology A1N
• Data Mining I, 5 credits (1DL360) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Technology A1N
• Large Language Models and Societal Consequences of Artificial Intelligence, 5 credits (1RT730) Main field(s) of study and in-depth level: Computer Science A1F, Data Science A1F, Image Analysis and Machine Learning A1F
• 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

• Project in Data Science, 5 of 10 credits (1DL508) Main field(s) of study and in-depth level: Data Science A1F
• Computer-Intensive Statistics and Applications, 10 credits (1MS049) Main field(s) of study and in-depth level: Computer Science A1N, Data Science A1N, Financial Mathematics A1N, Mathematics A1N
• Mining of Social Data, 10 credits (1DL465) Main field(s) of study and in-depth level: Computer Science A1F, Data Science A1F

1DL465 Social Data Mining is offered if resources allow.

Semester 4

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