Text

Course syllabus - Learning Systems

7.5 credits

CDT407

Autumn semester 2013

Second cycle

A1F (Second cycle, has second-cycle course/s as entry requirements).

Computer Science

School of Innovation, Design and Engineering

2013-01-25

This syllabus is not current and will not be given any more

Literature lists

Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.

Objectives

This course aims to give a wide knowledge in different learning systems, advantages, limits and application areas.

Learning outcomes

After finishing this course a student will be able to do the following:

- Having a (vague) problem definition choose an algorithm and explain why it is suitable for the given problem as well as show how it can solve the problem.
- Analyze the results of applying an algorithm to a problem. Discuss the results and propose improvements or other more suitable algorithms
- Write a scientific report and explain every step from definition of a problem to analysis of the results

Course content

Artificial neural nets; evolutionary algorithms; reinforcement learning; Bayesian nets; case-based reasoning; clustring and fuzzy systems.

Specific requirements

At least 120 credits where theoretical and practical competences in datastructures and algorithms and an object-oriented language like C, C#, C++ or Java are included. In addition Swedish course B/Swedish course 2 and English course A/English course 5 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 2.

Examination

Exercise (INL1), 1.5 credits, marks Pass (G)
Exercise, laboratory work (LAB1), 3 credits, marks Pass (G)
Examination (TEN1), 3 credits, marks 3, 4 or 5

A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.

Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.

Grade

Pass with distinction, Pass with credit, Pass, Fail