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
Keep going
Other courses on this track
Most learners move through two or three courses as they grow.
Try Agentic AI for free.
One live demo class, no commitment. Rates for this course are published per class.
