Google × Kaggle — Generative AI Course
My working notes from the Google × Kaggle Generative AI course. Notes are organized by concept (each topic gets its own page), and tracked by day in the progress table below.
Notes here are my own summaries and paraphrases of the course material, plus my takeaways — not copies of the original copyrighted content.
How these notes work
- Paste workflow: I paste each day's course material; it gets distilled into concept notes under this folder.
- By concept: each topic (embeddings, RAG, agents, …) lives in its own page and grows as the course revisits it.
- Cross-linked: key terms link to the AI Engineering Glossary; things I don't fully grasp go to Open Questions.
Progress tracker
| Day | Date | Topics covered | Notes |
|---|---|---|---|
| 1 | 2026-06-28 | Introduction to Agents — 4 components, the agentic loop, 5-level taxonomy, Agent Ops & evals, interoperability (A2A), security, self-evolving agents | Agents |
Concept notes
- Agents — what an agent is, architecture, taxonomy, Agent Ops, interop, security (Day 1)