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 Image Analysis, 5 of 10 credits (1MD110) Main field(s) of study and in-depth level: Computer Science A1N, Image Analysis and Machine Learning 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 course 5 credits

• Computer Programming II, 5 credits (1TD722) Main field(s) of study and in-depth level: Computer Science G1F, Technology G1F
• Linear Algebra for Data Science, 5 credits (1MA330) Main field(s) of study and in-depth level: Data Science A1N, Mathematics A1N
• Algorithms and Data Structures I, 5 credits (1DL210) Main field(s) of study and in-depth level: Computer Science G1F, Technology G1F
• Database Design I, 5 credits (1DL301) Main field(s) of study and in-depth level: Computer Science G2F, Sociotechnical Systems G2F, Technology G2F

Period 2

• Introduction to Image Analysis, 5 of 10 credits (1MD110) Main field(s) of study and in-depth level: Computer Science A1N, Image Analysis and Machine Learning 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 course 5 credits

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

1TD184 requires a course in several variable calculus.

• Algorithms and Data Structures II, 5 credits (1DL231) Main field(s) of study and in-depth level: Computer Science G2F
• Database Design I, 5 credits (1DL301) Main field(s) of study and in-depth level: Computer Science G2F, Sociotechnical Systems G2F, Technology G2F
• Human-Computer Interaction, 5 credits (1MD016) Main field(s) of study and in-depth level: Computer Science G1N, Sociotechnical Systems G1N, Technology G1N

Semester 2

Period 3

• 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

Elective course (10 credits)

• Computer Graphics, 10 credits (1TD388) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N
• High Performance Programming, 10 credits (1TD062) Main field(s) of study and in-depth level: Computational Science A1N, Computer Science A1N, Data Science A1N, Technology A1N
• 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
• Scientific Computing for Data Analysis, 5 credits (1TD352) Main field(s) of study and in-depth level: Computer Science G2F, Technology G2F

Period 4

• Advanced Deep Learning for Image Processing, 5 credits (1MD042) Main field(s) of study and in-depth level: Computer Science A1F, Image Analysis and Machine Learning A1F
• Reinforcement Learning, 5 credits (1RT745) Main field(s) of study and in-depth level: Data Science A1N, Embedded Systems A1N, Technology A1N

Specialisation of Image analysis and machine learning for biomedical applications:

• Digital Imaging Systems, 5 credits (1MD041) Main field(s) of study and in-depth level: Image Analysis and Machine Learning A1F

Specialisation in Image analysis and machine learning for social robotics:

• Human-Robot Interaction, 5 credits (1MD043) Main field(s) of study and in-depth level: Computer Science A1N, Human-Computer Interaction A1N, Image Analysis and Machine Learning A1N, Technology A1N

Semester 3

Period 1

• Project in Software Development in Image Analysis and Machine Learning, 10 of 15 credits (1MD036) Main field(s) of study and in-depth level: Image Analysis and Machine Learning A1F

Eligible course, 5 credits

• 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

1RT705 requires a course in several variable analysis.

• 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

Period 2

• Project in Software Development in Image Analysis and Machine Learning, 5 of 15 credits (1MD036) Main field(s) of study and in-depth level: Image Analysis and Machine Learning A1F
• Research Methodology for Image Analysis and Machine Learning, 5 credits (1MD048) Main field(s) of study and in-depth level: Image Analysis and Machine Learning A1F

Specialisation of Image analysis and machine learning for biomedical applications:

• Contemporary Methods in Visual Data Processing, 5 credits (1MD049) Main field(s) of study and in-depth level: Image Analysis and Machine Learning A1F

Specialisation in Image analysis and machine learning for social robotics:

• Intelligent Interactive Systems, 5 credits (1MD032) Main field(s) of study and in-depth level: Computer Science A1N, Human-Computer Interaction A1N, Technology A1N

Semester 4

• Degree Project E in Image Analysis and Machine Learning, 30 credits (1MD038) Main field(s) of study and in-depth level: Image Analysis and Machine Learning A2E