Functions, Tools and Agents with LangChain
by DeepLearning.AI × LangChain
Master function/tool calling — the mechanism that lets LLMs actually do things — with LangChain.
Overview
This course zooms in on the single most important agent primitive: structured function/tool calling. You learn how models emit structured calls, how to bind Python tools, how to parse and validate outputs with Pydantic, and how to compose it all using LangChain Expression Language (LCEL). It's the connective tissue between an LLM and the real world, and this course makes it concrete.
At a Glance
- Topic
- Agentic
- Level
- Intermediate
- Format
- Course
- Cost
- Free
- Duration
- ~1-2 hours
- Provider
- DeepLearning.AI × LangChain
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓How LLM function/tool calling works under the hood
- ✓Binding Python tools and validating structured output
- ✓Composing chains with LangChain Expression Language (LCEL)
- ✓Building a conversational agent that uses tools
Highlights
- •Deep on the tool-calling primitive most agents depend on
- •Pydantic-based structured outputs
Who It’s For
Best For
- ✓Developers who want reliable tool/function calling
Prerequisites
- •Intermediate Python
FAQ
What is Functions, Tools and Agents with LangChain?
A focused course on LLM function calling, tool binding, and the LangChain Expression Language for composing agentic chains.
Is Functions, Tools and Agents with LangChain free?
Functions, Tools and Agents with LangChain is free to access.
What level is Functions, Tools and Agents with LangChain for?
Functions, Tools and Agents with LangChain is aimed at a intermediate audience. Recommended background: Intermediate Python.
How long does Functions, Tools and Agents with LangChain take?
Expect roughly ~1-2 hours. Most learners work through it at their own pace.
What will I learn from Functions, Tools and Agents with LangChain?
You'll learn: How LLM function/tool calling works under the hood; Binding Python tools and validating structured output; Composing chains with LangChain Expression Language (LCEL); Building a conversational agent that uses tools.