Curricula

Requirements

You must take WASP courses corresponding to 27hp. These should be selected as follows:

• You must take the mandatory course (3hp)
• You must take  2 out of the 3 foundational courses. (12hp)
• You must take additional WASP courses corresponding to 12hp. These courses can either be foundational  and/or advanced. Note that the introductory courses can not be included in the required 27hp.

You may in addition take as many courses as you want to.

Curriculum

Mandatory course (given yearly)

• Ethical, Legal and Societal Aspects of AI and Autonomous Systems (3hp)

Foundational courses (given yearly)

• Autonomous Systems (6hp)
• AI and Machine Learning (6hp)
• Software Engineering and Cloud Computing (6hp)

Advanced courses (given every second year)

• Deep Learning for Natural Language Processing (6hp)
• Deep Learning (6hp)
• Graphical Models, Bayesian Learning and Statistical Relational Learning (6hp)
• Interaction, Collaboration, and Visualization (6hp)
• Learning Feature Representations (6hp)
• Learning Theory (new, 6hp)
• Reinforcement Learning (new, 6hp)
• Scalable Data Science and Distributed Machine Learning (6hp)
• Topological Data analysis (6hp)
• WASP Project course (6hp)

Introductory courses

• Introduction to logic for AI (2hp)
• Introduction to Mathematics for Machine Learning (4hp)

If you switch to the joint curriculum and have taken the course Autonomous Systems 2, you can count this course (6hp) as one of your elective courses.

Requirements

You must take WASP courses corresponding to 27hp. These should be selected as follows:

• You must take the mandatory courses (21hp)
• You must take at least 1 out of the 2 prioritized courses (6hp)
• You must take courses corresponding to at least 27hp.

You may in addition take as many courses as you want to.

Changes

• The mandatory course ”Learning Theory and Reinforcement Learning” has been extended and is divided into two courses: “Learning Theory” and “Reinforcement Learning”. If you have not taken the original course you must take at least one of these two new courses, free of choice.

Curriculum

Courses not given yearly are given every second year.

Mandatory courses

• Deep Learning (6hp) Renamed from “Deep learning and GANs”
• Ethical, Legal and Societal Aspects of AI and Autonomous Systems (3hp)
• Graphical Models, Bayesian Learning and Statistical Relational Learning (6hp)
• Scalable Data Science and Distributed Machine Learning (6hp)

Prioritized courses

Unless you have already taken the course “Learning theory and reinforcement learning”, you must take at least 1 of the following 2 courses:

• Learning Theory (new, 6hp)
• Reinforcement Learning (new, 6hp)

Elective courses

• Autonomous Systems (6hp)
• AI and Machine Learning (6hp)
• Deep Learning for Natural Language Processing (6hp)
• Interaction, Collaboration, and Visualization (6hp)
• Introduction to logic for AI (2hp)
• Introduction to Mathematics for Machine Learning (4hp)
• Learning Feature Representations (6hp)
• Software Engineering and Cloud Computing (6hp)
• Topological Data analysis (6hp)
• WASP Project course (6hp)

Requirements

You must take WASP courses corresponding to 24hp. These should be selected as follows:

• You must take the mandatory courses (24hp)
• If you have not taken the mandatory course Autonomous Systems 2, you may take another 6hp course free of choice, with an exception made for the two introductory courses (Introduction to Logic for AI & Mathematics for Machine Learning), which cannot be part of the required 24hp.

You may in addition take as many courses as you want to.

Changes

• The mandatory course ”Autonomous Systems 1” is no longer given. If you have not yet taken this course you must take the new course “Autonomous Systems” instead.
• The mandatory course ”Autonomous Systems 2” is no longer given. If you have not taken this course you must take WASP course(s) free of choice (with exceptions made for the introductory courses) corresponding to 6hp instead.

Curriculum

Courses not given yearly are given every second year.

Mandatory courses

• Autonomous Systems 1 (6hp, replaced by “Autonomous Systems”, new, 6hp, given yearly)
• Autonomous Systems 2 (Closed and replaced by elective courses free of choice)
• Software Engineering and Cloud Computing (6hp)
• WASP Project course (6hp)

Elective courses

• AI and Machine Learning (6hp)
• Deep Learning (6hp)
• Deep Learning for Natural Language Processing (6hp)
• Ethical, Legal and Societal Aspects of AI and Autonomous Systems (3hp)
• Graphical Models, Bayesian Learning and Statistical Relational Learning (6hp)
• Interaction, Collaboration, and Visualization (6hp)
• Learning Feature Representations (6hp)
• Learning Theory ( 6hp)
• Reinforcement Learning (6hp)
• Scalable Data Science and Distributed Machine Learning (6hp)
• Topological Data analysis (6hp)

Introductory courses:

• Introduction to logic for AI (2hp)
• Introduction to Mathematics for Machine Learning (4hp)

• “Autonomous systems 1” (AS track) was given for the last time 2020 and is replaced by “Autonomous Systems”.
• “Autonomous systems 2” (AS track) was given for the last time 2020 and is not replaced.
• “Learning Theory and Reinforcement Learning” (AI track) was given for the last time 2020. The course has been extended and is divided into the two courses “Learning Theory” and “Reinforcement Learning”.