SummerAI
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Mine otsikasti
Study materials and assignment instructions.
Schedule: TBD
Lecturer: Priit Järv
Lectures
- week 1: Introduction
- week 2: Machine Learning
- week 3: Large Language Models
- week 4: Technical Aspects of Machine Learning
- week 5: Ethics and Impact of AI
- week 6: Closed book test
Assignments
Homework
Complete these as a group, outside the classroom.
Teachable Machine (deadline XX.YY)
Lab Work
Complete these as a group.
For each assigment, write a text file with answers to the questions or results of the lab work. One or more groups will present their results to everyone. There will be a joint discussion.
- Classical Machine Learning (XX.YY)
- Neural Network (XX.YY)
- LLM themed, to be decided (XX.YY)
Submitting results
Where to submit will be clarified before the start of the summer school.
Grading
Your grade will be formed by:
- 50% participation: actively taking part of solving the homework. Will be self-graded.
- 50% written test.