Print Course syllabus
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
School
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.
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Books
Artificial intelligence : a modern approach
3.,[updated] ed. : Boston : Pearson Education, cop. 2010 - xviii, 1132 s.
ISBN: 9780132071482 (pbk.) LIBRIS-ID: 11712972
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Reference litterature
Artificial intelligence : a modern approach
3.,[updated] ed. : Boston : Pearson Education, cop. 2010 - xviii, 1132 s.
ISBN: 9780132071482 (pbk.) LIBRIS-ID: 11712972
Articles
Vetenskapliga konferens- och journalartiklar som är relevanta för föreläsningarna och projektet
Akademin för innovation, design och teknik,
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.
Tuition
Lectures and project supervision.
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 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
Interim Regulations and Other Regulations
The course completely overlaps with DVA406 Intelligent systems 7,5 credits.