autumn 2021
DTE-2501 AI Methods and Applications - 10 ECTS

Last changed 13.04.2021

Type of course

This course can be taken as a single subject course

Course content

The course targets machine-based problem solving and basic Natural Language processing methods. The course introduces swarm intelligence, ant colony optimization, and genetic algorithms. Further on, fuzzy systems and fuzzy computing are introduced along with ensemble techniques, inductive systems, entropy, elementary clustering techniques K-NN, K-means and Q-learning along with Dynamic Programming.

Objectives of the course

On completion of the course, the successful student is expected to have the following:

Knowledge

The student will have:

  • An overview of numerous approaches in artificial intelligence.
  • Basic understanding of possibilities and limitations of the approaches presented in the course.
  • Basic understanding of the theory and application of the approaches presented in the course.

Skills

The student should be able to:

  • Program, adapt and apply AI algorithms on predefined problems.
  • Analyze and evaluate results of AI algorithms.

General Competence

  • Can apply the knowledge and skills to solve problems and communicate about the results with other specialists in the field of computer science.


Language of instruction

English

Teaching methods

The subject uses so-called "Flipped classroom", i.e., lectures are posted online continuously during the semester in the form of short instructional videos and demonstrations of 10-20 minutes. In addition, exercises and control questions related to each video are used.

The subject teaches in the autumn semester with teacher-led and assistant-led learning and / or exercises. Online students will have access to a teaching assistant for afternoon / evening support.


Information to incoming exchange students

This course is available for inbound exchange students.

There are no academic prerequisites to add this module in your Learning Agreement.Nevertheless, please see recommended prerequisites.

Bachelor Level

Do you have questions about this module?  Please check the following website to contact the course coordinator for exchange students at the faculty: https://en.uit.no/education/art?p_document_id=510412.

Deadline: 15th April 


Assessment

Course work requirement (work requirements)

  • Mandatory exercises: 4 of 6 approved exercises (Pass / Fail)

Examination and assessment:

Folder assessment with the following content (assessment basis):

  • Mandatory work: 2 programming works (Grade: A-F)
  • Multiple choice test for parts of the syllabus (Grade: A-F)

Work and multiple-choice tests can be weighted differently in their contribution to the final grade in the course.

If the work requirements are not met (delivered and passed at least 4 of 6 submissions) the candidate will not qualify to get a grade in the course.

If more than 30% of the portfolio (assessment basis) is missing (i.e. has passed less than 70% of the portfolio), one will not qualify for continuation and must take the course again at the next ordinary period.

The portfolio (exercises and tests) can be delivered in Norwegian or English.

Continuation

Continuation consists of completing the folder within a deadline. The parts of the work requirements that were missing during ordinary deadline will be replaced by new corresponding work requirements that must be made within the agreed deadline.


Schedule

  • About the course
  • Campus: Narvik | Bodø | Annet | Digitalt |
  • ECTS: 10
  • Course code: DTE-2501