The course is intended to suit teachers who are going to teach artificial intelligence in the upper secondary school. It has therefore both technical and didactic contents. The course brings up, on a general level, central technical principles that form the basis of today's AI systems, for example neural networks, knowledge representations and statistical methods. Furthermore, current AI applications, their possibilities and limitations, are dealt with. A didactic view permeates the course. At the same time as the students learn about AI technology, they work on transforming their newly acquired knowledge to contents suited for the upper secondary school.
LL141U Teaching artificial intelligence in upper secondary school: Technical perspectives 7.5 credits
Information per course offering
Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.
Information for Autumn 2025 Start 25 Aug 2025 contract education
- Course location
KTH Campus
- Duration
- 25 Aug 2025 - 12 Jan 2026
- Periods
- P1 (3.5 hp), P2 (4.0 hp)
- Pace of study
25%
- Application code
50586
- Form of study
Normal Daytime
- Language of instruction
Swedish
- Course memo
- Course memo is not published
- Number of places
Places are not limited
- Target group
- No information inserted
- Planned modular schedule
- [object Object]
- Schedule
- Schedule is not published
- Part of programme
- No information inserted
Contact
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus LL141U (Autumn 2024–)Headings with content from the Course syllabus LL141U (Autumn 2024–) are denoted with an asterisk ( )
Content and learning outcomes
Course contents
Intended learning outcomes
On completion of the course, the student should be able to
1. Describe principles for the development of AI systems
2. Discuss risks and safety aspects of various types of AI systems
3. Use AI tools to design simple models
4. Test AI models and discuss their usability and possibilities
5. On a general level, follow the development within AI
6. Plan and evaluate teaching about the above technical aspects of AI for pupils in the upper secondary school
Literature and preparations
Literature
You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
P, F
Examination
- INL1 - Written assignments, 4.0 credits, grading scale: P, F
- SEM1 - Seminars and exercises, 3.5 credits, grading scale: P, F
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information
Course room in Canvas
Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.
Offered by
Main field of study
Technology
Education cycle
First cycle