KIUA1013 Introduction to Artificial Intelligence
- Course codeKIUA1013
- Number of credits30
- Teaching semester2027 Spring
- Language of instruction and examinationNorwegian/English
- CampusHamar
- Required prerequisite knowledge
Recommended: KIUA1011 The World of AI and KIUA1012 Programming and mathematics
This course deals with intermediate-level topics in mathematics. The course also provides an introduction to intermediate-level topics in probability calculation and statistics. The course introduces basic topics in machine learning. These topics will be supplemented with programming methods and tools. Students will continue to develop general skills in project planning and knowledge sharing.
Learning outcome
Upon successfully passing the course, students will have achieved the following learning outcomes:
Students have:
- Knowledge about intermediate-level topics in mathematics based on basic topics
- Knowledge about intermediate-level topics in probability calculation and statistics based on basic topics
- Knowledge about intermediate-level programming methods and tools based on basic topics in logic and introductory programming
- Knowledge about basic topics in machine learning
Students can:
- Apply intermediate-level topics in mathematics
- Apply intermediate-level topics in probability calculation and statistics
- Apply intermediate-level topics in programming methods and tools
- Apply basic topics in machine learning
Students:
- Have a good understanding of the relevance of intermediate-level topics in mathematics based on basic topics
- Have a good understanding of intermediate-level topics in probability calculation and statistics based on basic topics
- Have a good understanding of intermediate-level topics in programming methods and tools based on basic logic and introductory programming
- Have a good understanding of basic topics in machine learning
- Can understand the importance of classical analogue learning methods before full-scale digital learning methods
- Can work in collaborative projects through different activities
The course comprises a combination of lectures, practical exercises, independent study and academic supervision.
- 1 individual piece of required coursework for written examination 1, requires physical attendance on campus
- 2 individual pieces of required coursework for written examination 2, requires physical attendance on campus
- 2 individual pieces of required coursework for the portfolio examination, requires physical attendance on campus
- Attendance in classes/teaching sessions is mandatory, where physical attendance on campus is required. There is an 80% attendance requirement in teaching sessions and a 100% attendance requirement in specific learning activities. This is in accordance with the teaching plan for each course in the programme of study.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comments |
|---|---|---|---|---|---|---|
Written examination with supervision | ECTS - A-F | Individual | 4 Hour(s) | 33% | Written exam 1 | |
Written examination with supervision | ECTS - A-F | Individual | 4 Hour(s) | 33% | Written exam 2 | |
Portfolio examination | ECTS - A-F | Group | 33% |
Combined examination consisting of three parts, all of which count equally:
- Four-hour invigilated written examination
- Four-hour invigilated written examination
- Portfolio examination in groups
Students may choose which language to use for their examination. The available options are Norwegian Bokmål, Norwegian Nynorsk and English.
Permitted examination support material:
- Literature
- All printed and written resources
- Any use of AI-generated text and content must be clarified with the lecturer, clearly labelled and academically justified in the submission