A hands‑on masterclass that takes you from zero to a fully functional AI agent. No prior experience — just curiosity and a terminal.
Week 1: Foundations
Understand what makes an AI agent different from a chatbot. Learn the core loop: Think → Act → Observe → Iterate. Set up Python, install LangChain, and build your first "Hello World" agent that can answer questions by calling a single function.
from langchain.agents import create_react_agent
agent = create_react_agent(llm, tools, prompt)
agent.invoke({"input": "Hello, world!"})
Week 2: Tool Integration
Give your agent real capabilities. Integrate web search (DuckDuckGo API), PDF parsing (PyMuPDF), and text summarization tools. Learn to write tool definitions as JSON schemas so the LLM knows when and how to use each tool.
Week 3: Memory & Context
Add short‑term memory (conversation buffer) and long‑term memory (vector database with embeddings). Your agent will remember past conversations, retrieve relevant documents, and maintain context across multi‑turn interactions.
Week 4: Deployment & Multi‑Agent Systems
Deploy your agent as a production API endpoint using FastAPI. Bonus module: build a multi‑agent system where an Orchestrator agent delegates tasks to specialized ResearchAgent, CodeAgent, and WriterAgent instances. Ship it.
- Learn the architecture of modern AI agents
- Integrate web search, PDF parsing, and summarization tools
- Deploy your agent as an API endpoint in production
- Bonus: Build a multi‑agent collaboration system