Course description forACIT4080 Intelligent User Interfaces

Introduction

The course focuses on the use of artificial intelligence technology as well as image, video and sound analysis to meet the user's needs, as well as handle ambiguous interaction situations.

Required preliminary courses

No formal requirements over and above the admission requirements.

Learning outcomes

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of this course the student

  • has specialized knowledge of intelligent systems and their role in intelligent user interfaces
  • has specialized knowledge of ontologies and the semantic gap
  • has specialized knowledge of the applications of smart home technology

Skills

On successful completion of this course the student

  • can apply classification and categorization to organize data, particularly with k-means, neural networks, fuzzy logic and neuro-fuzzy classification
  • can apply optimization techniques to find good solutions to problems using hill climbing, Tabu search and genetic algorithms
  • can apply intelligent techniques, such as association rules to implement recommender systems
  • can apply techniques from sound analysis, image analysis and video analysis to realize multi-modal input

General competence

On successful completion of this course the student

  • can analyse ethical aspects of automatic collection, storage, automatic interpretation and use of person-related measurements
  • can analyse opportunities and limitations associated with intelligent systems for given problems

Teaching and learning methods

This course is organized as a series of lectures, seminars discussing examples from research literature, and practical work. Lectures cover central theories in artificial intelligence, sound, image and video analysis followed by practical problem solving. Students present research papers in class, using theory to solve new and real problems and developing working prototypes.

Course Requirements

  • Six obligatory assignments. Students work on each assignment individually.
  • Individual oral presentation of research article (45 minutes with questions).

Assessment

  • Project examination in groups. The examination consists of a project report (3000-4000 words). This part of the examination counts 90% of the final grade.
  • Group presentation with demo (30 minutes for each group). This part of the examination counts 10% of the final grade.

Each group may consist of up to three candidates. Both exams must be passed in order to pass the course.

The grade for the group presentation cannot be appealed.

Grading scale

For the final assessment a grading scale from A to E is used, where A denotes the highest and E the lowest pass grade, and F denotes a fail.

Examiners

Two internal examiners will assess the report and oral presentation. External examiner is used periodically.

Course information

Course name in Norwegian
Intelligent User Interfaces
Study programme
Fall: Master's Degree Programme in Applied Computer and Information Technology
Weight
10 ECTS
Year of study
2019
Schedule
FALL 2019
Programme description
Fall 2019: Master's Degree Programme in Applied Computer and Information Technology
Subject History