Entry requirements

120 credits including 15 credits in mathematics and 60 credits in computer science, including 20 credits in programming/algorithms/data structures. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

On completion of the course, the student should be able to:

• describe how, and why, natural computation methods work, explain principles and show examples,
• set up and solve typical problems, by implementation or computer simulation tools,
• decide which machine learning methods/algorithms are suitable for which type of learning problems, i.e. know about their most important weaknesses and advantages,
• recognize typical effects of less suitable choices (problem setup and parameter selection, for example) and determine how the results can be improved based on this.

Content

The course introduces various natural computation methods. The course is divided into a theoretical part and a practical part.

The theoretical part consists of lectures and literature on various topics, including (but not limited to):

• learning paradigms (supervised, unsupervised and reinforcement learning),
• artificial neural networks for classification, function approximation and clustering,
• deep learning,
• reinforcement learning and temporal difference learning,
• evolutionary computing (genetic algorithms and genetic programming), and
• swarm Intelligence (ant colony optimisation, particle swarm optimisation).

The practical part consists of assignments.

Instruction

Lectures and assignments.

Assessment

The assessment in the theory section (4 credits) of the course consists of a combination of written and oral examinations.

The assessment in the practical section (3.5 credits) of the course consists of assignments and oral examinations.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Other directives

The course cannot be included in the same degree as 1DL073, 1DT071, 1DT022 or 1DT646