AI essentials (DAT105)
The course is intended for anyone who is interested in learning about artificial intelligence (AI) in an intuitive way. The course is flexible and fully digital with recorded lectures, structured in modules that can easily be adapted to fit your schedule.
Course description for study year 2024-2025
Course code
DAT105
Version
1
Credits (ECTS)
5
Semester tution start
Autumn
Number of semesters
1
Exam semester
Autumn
Language of instruction
English, Norwegian
Content
The course provides you with the foundations to understand and be critical about AI technologies and its use for your idea, business, studies or job. The content ranges from understanding what AI and some of the most common terminology in the domain (for example, deep learning) is, considerations before adopting AI for the problem at hand, what is generative AI, available generative AI tools, best practices for generative AI tools to limitations of some of the available AI tools and ethical/legal implications of them.
The course is structured in four independent blocks, each of them covering a specific topic. In particular, the first block introduces essential bits of knowledge to understand what AI is and the common terminology of AI, the second block gives an overview of considerations before using AI for the problem at hand. The third module introduces the concept of generative AI, including ChatGPT and other recent breakthroughs, and best practices and considerations for the technologies. Finally, the last module dwells on the implications of using AI, from an ethical perspective.
Learning outcome
Upon successfull completion of the course, the student should have the following learning outcomes:
Knowledge
- Know what AI is, and the differences between AI and AGI.
- Know basic terminology within the AI-domain: deep learning, generative AI or large language models (LLM).
- Know some of the main requisites to develop AI systems such as ChatGPT.
- Know some of the current limitations of AI systems.
- Know what the current main types of generative AI applications are.
- Know what the main available tools for generative AI are.
- Know what the best practices for generative AI tools are.
- Know what the ethical implications of using AI systems are.
- Know some of the legal limitations and implications of using AI systems.
Skills
- Be able to assess if AI is appropriate for the problem under consideration.
- Be capable of being critical about the output of an AI system.
- Be able to use generative AI tools.
- Be able to choose the right AI tool for your problem.
- Be able to understand common AI concepts and talk about them.
Required prerequisite knowledge
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Project assignment | 1/1 | 1 Semesters | Passed / Not Passed | All |
The final project will be available through most of the semester, so that you can work on it at the same time as you follow the lectures. The project assignment is individual and students are expected to deliver substantially different reports, either in the form of different problem choices or different proposed methodology to solve similar problems. The student is expected to choose a problem deemed relevant in their area of expertise (job, study…), and propose a solution using the AI knowledge and tools learnt during the course. Initial problem examples and expected types of solutions will be provided by the instructor. An initial assessment of the problem will be available for those students that want to ensure their problem choice is relevant. If a student is facing difficulties, the instructor will provide support to define the problem. The project can be written in english or norwegian.
