Exploiting generative artificial intelligence (4cr)
Code: KL00DX67-3003
General information
- Enrollment
- 07.05.2025 - 31.08.2025
- Registration for the implementation has ended.
- Timing
- 21.08.2025 - 12.10.2025
- Implementation is running.
- Number of ECTS credits allocated
- 4 cr
- Local portion
- 0 cr
- Virtual portion
- 4 cr
- Mode of delivery
- Distance learning
- Campus
- SeAMK Seinäjoki, Frami
- Teaching languages
- Finnish
- Degree programmes
- Bachelor of Engineering, Information Technology
Evaluation scale
1-5
Objective
Student can explain the principles of language models (LLM) and is able to apply them in practical tasks, also programmatically. Student can install LLM locally or on a private cloud. Student can fine-tune LLM and apply Retrieval-Augmented Generation (RAG) techniques.
Content
- Using the large language model (LLM) programmatically
- Exploiting a locally installed language model
- Exploring cloud-based solutions
- Language model fine-tuning and Retrieval-Augmented Generation (RAG)
Assessment criteria, satisfactory (1)
Student can explain the principles of language models (LLM) and is able to apply them in practical tasks, also programmatically. Student can install LLM locally or on a private cloud.
Assessment criteria, good (3)
Student can explain the principles of language models (LLM) and is able to apply them in practical tasks, also programmatically. Student can install LLM locally or on a private cloud. Student can fine-tune LLM and apply Retrieval-Augmented Generation (RAG) techniques.
Assessment criteria, excellent (5)
Student can explain the principles of language models (LLM) and is able to apply them in practical tasks, also programmatically. Student can install LLM locally or on a private cloud. Student can fine-tune LLM and apply Retrieval-Augmented Generation (RAG) techniques. Student understands how fine-tuning improves the performance of the model.