Code and material for the class "Introduction to GenAI for Engineers"
| # | name | open in | solution |
|---|---|---|---|
| 1 | Explore Tokens |  |
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| 2 | Explore Embeddings | |
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| 3 | What are Vector Databases? | |
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| 4 | Diffusion Models | |
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| 5 | Video Models | |
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| 6 | RAG From Scratch | |
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| 7 | Haystack Basics | |
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| 8 | Haystack RAG | |
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| 9 | Guardrails | |
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| 10 | Observability | |
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| 11 | Function Calling | |
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| 12 | Agents | |
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| 13 | Agents for Income Statement Analysis | |
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| 14 | Stock Agent OpenAI | |
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Note
Some notebooks require environment variables (such as API keys) to be set. These can be configured directly in the notebooks or via Colab secrets when running in Google Colab.
Note
The project uses Python 3.12 for compatibility with Colab.
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Install uv, following the official docs: https://docs.astral.sh/uv/getting-started/installation/
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Run:
uv sync --all-groups- It is highly recommended to use
nbstripoutto avoid pushing the output of jupyter notebooks. Install it with:
pre-commit installThis class was created by the AI team at xtream, with contributions from:
The material in this repository was used in classes and seminars taught at:
- Catholic University of Milan, 2025
- Lavazza, 2025
- Fabrick, 2025
- Atlante, 2025
- CRIF, 2024 & 2025
- Talent Garden, 2025
- Zuccari, 2025
- TWIN Agency, 2024
- WeRoad, 2024
- Banca CF+, 2023
- Boolean Dataweek, 2023
And was the base for the 10+ talks and workshops, including:
- Embeddings, Transformers, RLHF: Three Key Ideas to Understand ChatGPT, AI Conf, 2024, Milan, Italy
- How to Build Your Own GPT, AMLD, 2024, Lausanne, Switzerland
- Embeddings, Transformers, RLHF: Three Key Ideas to Understand ChatGPT, PyCon IT, 2024, Florence, Italy
- Beyond ChatGPT: RAG and Fine-Tuning, University of Pavia, 2024, Pavia, Italy
- Embeddings, Transformers, RLHF: Three Key Ideas to Understand ChatGPT, BI Digital, 2023, Biella, Italy
- Embeddings, Transformers, RLHF: Three Key Ideas to Understand ChatGPT, SIIAM Congress, 2023, Rome, Italy