Build Agentic AI with Python
Master Python core syntax and data structures, then build AI agents with LangChain and LangGraph — agents that use tools, manage conversation state, and handle multi-step reasoning.
Python Programming
42 ChaptersMaster the core syntax, data structures, and APIs through code-centric tutorials. The essential prerequisite for Agentic AI development.
33Data Classes for Simple Structured Data34Comprehensions: A Compact Way to Create Lists, Dictionaries, and Sets35How Iteration Works: Iterables and Iterators36Generators and Lazy Iteration37Built-in Functions and Useful Tools38Decorators: Adding Behavior to Functions39Essential Standard Library Modules40Writing Clean and Readable Code41Debugging and Testing Your Code42A Gentle Introduction to Type Hints (Optional)
LangChain & LangGraph
18 ChaptersLearn how to design and implement agentic AI systems based on LangChain and LangGraph by integrating LLMs, tool usage, and multi-step reasoning.
09Build Your First RAG System10Smarter Retrieval: Filters, Thresholds, and MMR11Conversational RAG: Adding Memory to Retrieval1212: Building Tools for Your Agent13Connecting Tools to the LLM14Building the Agent Loop15Building Your First Graph with LangGraph16Prebuilt Components and Multi-Branch Routing17State Persistence and Checkpointing18Multi-Agent Systems — The Supervisor Pattern