5-Day-AI-Agents-Intensive-Course-with-Google

# 5-Day AI Agents Intensive Course with Google > **Over 420,000 developers have participated in this AI Agent course** | Thanks to [sdivyanshu90](https://github.com/sdivyanshu90/5-Day-AI-Agents-Intensive-Course-with-Google) and Google for providing free course resources. 5-day live course replay videos: [youtube](https://www.youtube.com/playlist?list=PLqFaTIg4myu9r7uRoNfbJhHUbLp-1t1YE) New Google course: [25-Day Agents Course - Christmas Gift](https://mp.weixin.qq.com/s/H4C65Vvh58G3g8AZ1vl1lA), learning notes: [25-Day-Agents-Course-by-Google](https://github.com/anxiong2025/25-Day-Agents-Course-by-Google) ## Quick Start ### Prerequisites - Python 3.12+ - [uv](https://docs.astral.sh/uv/) package manager - Google API Key ([get it here](https://aistudio.google.com/apikey)) ### Installation and Configuration ```bash # Install dependencies uv sync # Configure API key cp .env.example .env # Edit .env file and add your GOOGLE_API_KEY ``` ### VS Code Configuration **Required plugin**: Jupyter - Installation: `Cmd+Shift+P` → "Extensions: Install Extensions" → search for "Jupyter" - Select kernel: click on kernel selector in notebook → select `.venv (Python 3.12.x)` ### Run Notebook Open `day1/*.ipynb` in VS Code and press `Shift+Enter` to run cells --- ## Course Outline and Daily Assignments ### ✅ Day 1: Agent Basics **Topic**: Agent classification, Agent Ops, interoperability, and security basics - 📄 [Whitepaper: Introduction to Agents](https://www.kaggle.com/whitepaper-agents) - 🎙️ [Podcast: Unit 1 Summary](https://www.kaggle.com/whitepaper-agents-podcast) - 💻 **Code Experiments**: - [Build your first Agent with Gemini and ADK](https://www.kaggle.com/code/markishere/day-1-prompting-with-gemini) - [Build your first multi-Agent system](https://www.kaggle.com/code/markishere/day-1-agent-architectures) - 📚 [Code Experiment Troubleshooting Guide](https://www.kaggle.com/discussions/general/552193) **Local Notebooks**: - `day1/day1-01-from-prompt-to-action.ipynb` - Basic Agent + Google search - `day1/day1-02-agent-architectures.ipynb` - Multi-Agent patterns (sequential/parallel/dynamic) - `day1/day1-01-First-Agent-Web-UI.py` - FastAPI Web interface (run: `uv run day1/day1-01-First-Agent-Web-UI.py`) --- ### Day 2: Agent Tools and Interoperability (MCP) **Topic**: External tools, real-time data retrieval, Model Context Protocol (MCP) - 📄 [Whitepaper: Agent Tools & Interoperability with MCP](https://www.kaggle.com/whitepaper-agents-tools) - 🎙️ [Podcast: Unit 2 Summary](https://www.kaggle.com/whitepaper-agents-tools-podcast) - 💻 **Code Experiments**: - [Extend Agent capabilities with new tools](https://www.kaggle.com/code/markishere/day-2-tools) - [Tool best practices: MCP and long-running operations](https://www.kaggle.com/code/markishere/day-2-mcp-and-long-running-tools) --- ### Day 3: Context Engineering: Sessions and Memory **Topic**: Context window management, sessions, memory (long-term persistence) - 📄 [Whitepaper: Context Engineering: Sessions & Memory](https://www.kaggle.com/whitepaper-agents-memory) - 🎙️ [Podcast: Unit 3 Summary](https://www.kaggle.com/whitepaper-agents-memory-podcast) - 💻 **Code Experiments**: - [Implement session management for instant context](https://www.kaggle.com/code/markishere/day-3-sessions) - [Implement memory system for long-term personalization](https://www.kaggle.com/code/markishere/day-3-memory) --- ### Day 4: Agent Quality Assurance **Topic**: Evaluation framework, observability (logs/tracing/metrics), LLM-as-a-Judge, human-in-the-loop (HITL) - 📄 [Whitepaper: Agent Quality](https://www.kaggle.com/whitepaper-agents-quality) - 🎙️ [Podcast: Unit 4 Summary](https://www.kaggle.com/whitepaper-agents-quality-podcast) - 💻 **Code Experiments**: - [Implement observability for debugging](https://www.kaggle.com/code/markishere/day-4-observability) - [Evaluate your Agent](https://www.kaggle.com/code/markishere/day-4-evaluation) --- ### Day 5: From Prototype to Production **Topic**: Deployment, scaling, Agent2Agent (A2A) protocol, Vertex AI Agent Engine - 📄 [Whitepaper: Prototype to Production](https://www.kaggle.com/whitepaper-agents-production) - 🎙️ [Podcast: Unit 5 Summary](https://www.kaggle.com/whitepaper-agents-production-podcast) - 💻 **Code Experiments**: - [Implement multi-Agent communication with A2A protocol](https://www.kaggle.com/code/markishere/day-5-a2a) - [[Optional] Deploy to Google Cloud Agent Engine](https://www.kaggle.com/code/markishere/day-5-agent-engine) --- ## Notes - Kaggle code experiments require phone verification - Project uses `.env` to store API keys (do not commit `.env` to git)