Syllabus
Last changed: 23.10.24
Date | General Topic | Homework | Assignments |
---|---|---|---|
09.10 | Admin, Architectures: Statistical and Probabilistic Language Models | Familiarization with Google Colab | |
16.10 | Architectures: Perceptrons and Neural Networks | ||
23.10 | Architectures: Perceptrons and Neural Networks (part 2) | Assignment 1 | |
30.10 | Transformer: General architecture | ||
06.11 | Transformer: The Attention mechanism | ||
13.11 | Transformer: Transformer models: Decoder/Encode only models | Assignment 2 | |
20.11 | Using pre-trained models | ||
27.11 | Study week | ||
04.12 | Transfer learning: fine-tuning | ||
11.12 | Adapting models for specific tasks | Assignment 3 | |
18.12 | Adapting models for specific tasks | ||
08.01 | Adapting models for specific tasks | Assignment 4 | |
15.01 | Probing LLMs | ||
22.01 | Probing LLMs | Assignment 5 | |
29.01 | TBD |