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Course syllabus - Intelligent Systems

Scope

7.5 credits

Course code

DVA439

Valid from

Autumn semester 2015

Education level

Second cycle

Progressive Specialisation

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

Main area(s)

Computer Science

Organisation

School of Innovation, Design and Engineering

Ratified

2014-06-24

Literature lists

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

    • Ratified date: 2020-11-20
    • Latest update: 2025-05-27

    Books

    Russell, Stuart Jonathan; Norvig, Peter

    Artificial intelligence: a modern approach

    ISBN: 9780132071482 (pbk.)

    LIBRIS-ID: 11712972

    3.,[updated] ed., Boston, Pearson Education, xviii, 1132 s.

Objectives

This course aims to offer a foundation of intelligent system techniques and their application in various real-world domains and how to implement a system with “intelligent” functionality. Students will learn to judge when intelligent functionality and artificial intelligence may be a good solution for a problem and be able to choose suitable AI methods and techniques. Students will also acquire knowledge enabling them to develop necessary skills to design and implement an intelligent system.

Learning outcomes

After finishing this course the student will be able to:

  1. describe in detail the class of problems that a specific type of artificial intelligence technique and/or algorithm is
    suitable to address,
  2. show the ability to design and implement a prototype in artificial intelligence, furthermore, propose further
    improvements and
  3. show the ability to write a scientific report in artificial intelligence, which fulfills the requirements for a good
    reporting culture, as well as a scientific perspective.

Course content

Intelligent agents, fuzzy control, fuzzy adaptive control, multi-sensor data and information fusion, decision analysis with
uncertainty, case-based reasoning, signal analysis and multi-objective optimization.

Specific requirements

At least 90 ECTS credits in computer science and/or electronics where at least 15 credits in programming are included. In addition Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.

Examination

Project (PRO1), 3,5 credits, marks Fail (U), 3, 4 or 5, (examines learning objectives 1-3)
Examination (TEN1), written examination, 4 credits, marks Fail (U), 3, 4 or 5, (examines learning objectives 1-2)

A student who has a certificate from MDU regarding disability study support, can request adaptions for the examination. It is the examiner who takes decisions on any adaptions, based on the certificate and other conditions.

Grade

Grading scale: 5, 4, 3

Interim Regulations and Other Regulations

The course completely overlaps with DVA406 Intelligent systems 7,5 credits.