Unleash the Power of Large Language Models Using LangChain

A concise, hands-on LangChain masterclass that equips you to prototype and deploy powerful LLM workflows in just two hours.

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access	Lifetime
level	Beginner
certificate	Certificate of completion
language	English

#Educative

Description
Additional information

What will you learn in Unleash the Power of Large Language Models Using LangChain Course

Understand the core concepts of language models and the architecture of LangChain
Craft and manage prompt templates, parse LLM outputs, and handle message formats

Integrate external tools and services into LangChain workflows for extended functionality
Generate and work with embeddings, store and query vectors in vector databases

Program Overview

Module 1: Introduction to LangChain

⏳ 25 minutes

Topics: What Is a Language Model?; What Is LangChain and Why Does It Matter?; Use Cases of LangChain
Hands-on: Complete the initial interactive lessons to grasp core LangChain components and real-world integration scenarios

Module 2: Exploring LangChain

⏳ 45 minutes

Topics: Chat Models, Messages, and Prompt Templates; Parsing Outputs; Runnables & Expression Language; Tools; Embeddings & Vector Stores
Hands-on: Build and test simple chains—craft prompts, parse outputs, invoke tools, and retrieve embeddings from vector stores

Module 3: LangGraph Basics

⏳ 45 minutes

Topics: What Is LangGraph?; Main Components of LangGraph; Why Traditional Chains Fall Short; How to Create a Routing System; LangGraph Quiz
Hands-on: Configure and evaluate a router chain to orchestrate multi-agent workflows dynamically

Module 4: Wrapping Up

⏳ 10 minutes

Topics: Integrating LangChain with LLMs, dynamic agents, and future possibilities
Hands-on: Finalize the course with a practical wrap-up and explore the “Query CSV Files with Natural Language Using LangChain and Panel” project

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Job Outlook

The average Artificial Intelligence Engineer salary in the U.S. is $106,386 per year as of June 2025
Employment of software developers, quality assurance analysts, and testers is projected to grow 17% from 2023 to 2033
Proficiency with LLM frameworks and prompt engineering drives roles like AI Engineer, Machine Learning Engineer, and AI Consultant
LangChain expertise is increasingly sought after for building chatbots, retrieval-augmented generation systems, and custom LLM services

9.6Expert Score

Highly Recommendedx

This Educative course delivers a concise, hands-on journey through LangChain—from basic chains and prompt templates to advanced LangGraph routing—using interactive code snippets and real-time feedback. It’s ideal for developers and data scientists wanting to rapidly prototype LLM applications.

Value

Price

9.2

Skills

9.4

Information

9.5

PROS

Fully interactive, in-browser coding environment eliminates setup overhead
Clear progression from basic chains to complex multi-agent workflows
Real-world project example (“Query CSV Files with Natural Language”) reinforces learning

CONS

Text-based format may not suit learners who prefer video instruction
Limited depth on deployment and scaling best practices outside of core LangChain APIs