This is a hub for notes and codelabs/notebooks associated with Google’s 5 Day Intensive Generative AI Course.
Notes
- Google Gemini: Introduction and snippets to the Gemini developer API via the Python SDK
- Foundational LLMs and Text Generation
- Prompt Engineering
- LLM Evaluation
- Embeddings
- AI Agents
- Fine Tuning LLMs
- MLOps
Code Labs & Kaggle Notebooks
- Day 1 - Prompting
- Day 1 - Evaluation and Structured Output
- Day 2 - Document Q&A with RAG
- Day 2 - Embeddings and Similarity Scores
- Day 2 - Classifying embeddings with Keras and the Gemini API
- Day 3 - Function Calling with the Gemini API
- Day 3 - Building an agent with LangGraph
- Day 4 - Fine Tuning a Custom Model
- Day 4 - Google Search Grounding with the Gemini API. Grounding is a framework that gives the model access to Google Search (in this case) to confirm answers.
Whitepapers
- Foundational LLMs and Text Generation
- Prompt Engineering
- Embeddings and Vector Stores
- AI Agents
- Solving Domain-Specific Problems Using LLMs
- Operationalizing Generative AI on Vertex AI