Kids · Professional

Agentic AI

Learn what makes AI "Agentic" and how to build agents. AI agents are changing how software gets built: they reason, take actions and adapt to what they find. This hands-on course gives you a practical foundation in agentic AI with LangChain. You will learn the core ideas, apply them to a real project, and finish with the skills and confidence to design, build, and debug agents of your own.

12 sessions
Advanced
AI & machine learning
Career & portfolio

Building AI Agents with LangChain

What they'll walk away with

  • Build your own AI assistant

Curriculum

5 modules over 12 sessions, each ending in something built.

01

Introduction to Agentic AI and LangChain

  • Introduction to Agentic AI and LangChain
  • What is Agent? Agents vs LLMs
  • What Makes AI Agentic
  • The LangChain Ecosystem and Core Components
  • The ReAct Pattern: How Agents Think and Act
  • Environment Setup and Your First Model Call
02

Prompts, Prompt Engineering and Messages

  • Message Types: System, Human, AI, Tool
  • Prompt Engineering Fundamentals
  • Writing a System Prompt for an Agent
  • Structured Output
03

Building the Research Agent: UI, Tracing, Memory, Tools

  • A Chat UI with Gradio
  • Tracing and Debugging with LangSmith
  • Adding Conversation Memory
  • Giving the agent Tools
  • Convert REST API into Tool
  • Capstone: The Complete Research Assistant
04

Retrieval-Augmented Generation (RAG)

  • Introduction to VectorDB; Difference with Traditional DBs
  • Introduction to RAG and why it matters
  • Embedding models
  • Document Loaders and Retrieval Chains
  • Indexing and querying documents and Generation
05

MCP Servers

  • Introduction to MCP
  • Core concepts: Tools, Resources, Prompts
  • Moving Local Tools to MCP Server
  • Establish Server <--> Client Communications

What you'll need

  • Python

Try Agentic AI for free.

One live demo class, no commitment. Rates for this course are published per class.