course-details-portlet

AIS2101

Intelligent Systems

Choose study year
Credits 7.5
Level Intermediate course, level II
Course start Spring 2025
Duration 1 semester
Language of instruction English and norwegian
Location Ålesund
Examination arrangement Portfolio assessment

About

About the course

Course content

Selected topics will be announced at the start of the semester and may include some of the following:

  • Introduction to artificial intelligence
  • Rule-based expert systems
  • Frame-based systems
  • Fuzzy logic and fuzzy expert systems
  • Agent-based modelling and simulation
  • Evolutionary algorithms
  • Machine learning
  • Artificial neural networks
  • Reinforcement learning
  • Hybrid intelligent systems
  • Possibly other topics

Learning outcome

Knowledge

  • The candidate can explain and compare theory, principles, applications, strengths and weaknesses of methods presented in the course

Skills

  • The candidate can demonstrate the use of methods presented in the course, both through digital tools and simulation

General competence

  • The candidate can use digital tools for implementation of intelligent systems
  • The candidate can explain the value of intelligent systems for sustainable processes, services, or systems
  • The candidate can present problems and relevant solution methods in a professional and scientific manner
  • The candidate can discuss ethical challenges of artificial intelligence

Learning methods and activities

Learning activities generally include a mix of lectures, tutorials and practical lab/project work. A constructivist approach for learning is endorsed, with focus on problem solving and practical application of theory.

Further on evaluation

The final grade is based on an overall evaluation of the portfolio. The portfolio consists of work that is carried out and documented through digital submissions during the term. The number of assignments is generally consistent with the number of taught topics (typically 4-6). Both individual and team assignments may be given. Assignments are designed to help students achieve specific course learning outcomes, and feedback is given to students during the period of the portfolio. The re-sit exam is an oral exam in August.

Specific conditions

Admission to a programme of study is required:
Automation and Intelligent Systems - Engineering (BIAIS)

Required previous knowledge

The course has no prerequisites. It is a requirement that students are enrolled in the study programme to which the course belongs.

Course materials

An updated course overview, including curriculum, is presented at the start of the semester and will typically also include English material.

Credit reductions

Course code Reduction From
IE303312 7.5 sp Autumn 2021
This course has academic overlap with the course in the table above. If you take overlapping courses, you will receive a credit reduction in the course where you have the lowest grade. If the grades are the same, the reduction will be applied to the course completed most recently.

Subject areas

  • Computer and Information Science
  • Engineering Cybernetics
  • Engineering

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of ICT and Natural Sciences