autumn 2022
DTE-2501 AI Methods and Applications - 10 ECTS
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 reinforcement 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.
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.
Examination
Examination: | Date: | Grade scale: |
---|---|---|
Portfolio | 09.12.2022 14:00 (Hand in) | A–E, fail F |
Coursework requirements:To take an examination, the student must have passed the following coursework requirements: |
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Mandatory exercises | Approved – not approved |
More info about the portfolio
Portfolio assessment with the following three components (assessment basis):
- Two programming works (can be submitted in either English or Norwegian)
- One e-test for selected parts of the syllabus
The grade will be based on all three components in the portfolio. The weights of the components will be presented in the introductory presentation.
- About the course
- Campus: Narvik | Bodø | Annet | Online |
- ECTS: 10
- Course code: DTE-2501
- Responsible unit
- Institutt for datateknologi og beregningsorienterte ingeniørfag
- Tidligere år og semester for dette emnet