What are LangChain agents?

LangChain agents are AI-driven workflows that can select and use available tools to perform tasks. They can help applications handle multi-step tasks and interact with external services.

What is the difference between LangChain and LangGraph?

LangChain provides components and abstractions for building LLM-powered applications, while LangGraph is designed for building more stateful and controllable graph-based workflows, particularly for complex agent applications.

Is LangChain certification useful for a career?

LangChain certification can demonstrate completed learning and practical exposure to LangChain-based AI application development. Its value is strengthened when combined with hands-on projects, programming skills, and relevant professional experience.

What are the career opportunities after LangChain training?

Learners can explore roles such as LangChain Developer, AI Application Developer, LLM Application Developer, AI Engineer, RAG Developer, AI Solutions Engineer, and AI Automation Engineer depending on their existing technical experience.

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LangChain

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LangChain

Q: What is LangChain and why is it used?

LangChain is a framework for developing applications powered by language models. It helps developers connect models with prompts, tools, APIs, external data, memory, retrieval systems, and structured workflows.

Q: What will I learn in a LangChain course?

You will learn LangChain fundamentals, architecture, prompts, models, chains, memory, tools, agents, embeddings, vector stores, RAG, APIs, workflows, LangGraph fundamentals, testing, and practical application development.

Q: Is LangChain training suitable for beginners?

LangChain training is most suitable for learners with basic programming or technical knowledge, especially Python familiarity. The course progressively introduces LangChain concepts before moving into practical application development.

Q: Do I need Python to learn LangChain?

Basic Python knowledge is recommended because LangChain is commonly used for developing AI applications through Python. Familiarity with programming concepts can make it easier to build and customize LangChain workflows.

Q: What can I build with LangChain?

You can build applications such as AI chatbots, document question-answering systems, RAG applications, knowledge assistants, research tools, summarization systems, and AI workflows connected to external tools and APIs.

Q: What is LangChain RAG?

LangChain RAG combines document retrieval and language-model generation so an application can retrieve relevant information from a knowledge source and use that information to generate context-based responses.

Learn LangChain through practical training in LLM applications, chains, agents, RAG, vector stores, tools, APIs, workflows, and real-world AI projects.

5/5(4,890 Reviews)

Level

Advanced

Duration

4 weeks

About

Training Plan

Course Curriculum

New Batch

Projects

Certificate

Testimonials

FAQ

Interview FAQ

Placement Client

About LangChain

LangChain Course is a practical training program designed to help learners build and integrate LLM-powered applications using the LangChain framework.

The course covers LangChain architecture, chains, prompts, memory, tools, agents, APIs, document processing, embeddings, vector stores, RAG pipelines, and AI workflows. Learners explore how LangChain can be used to develop practical applications such as AI chatbots, knowledge assistants, document question-answering systems, and automated AI workflows.

The training focuses on hands-on implementation so learners can understand how to connect language models with external data, tools, APIs, and business workflows. It also introduces LangGraph and modern agent workflows as supporting concepts while keeping LangChain as the core learning focus.

Training Plan

About trainer

Working professional who is carrying more than 10 years of industry experience.

Decks & Updated Content

Access to updated presentation decks shared during live training sessions.

e-Book

Assignments & MCQs

Module-wise assignments and MCQs provided for practice.

Video Recording

Daily Session would be recorded and shared to the candidate.

Projects

Live projects will be provided for hands-on practice.

Resume Building

Expert-guided resume building with industry-focused content support.

Interview Preparation

Comprehensive interview preparation with real-time scenario practice.

LangChain Course Curriculum

Introduction to LangChainModule 1 — Introduction to LangChain

Understand LangChain fundamentals, its purpose, ecosystem, and role in developing applications powered by language models.

Introduction to LangChain

Why LangChain is used

LangChain and LLM Applications

LangChain Ecosystem

Core Capabilities

LangChain Use Cases

Basic Environment Setup

Module 2 — LangChain Architecture & Core Components

Explore the architecture and major building blocks used to create structured LangChain applications.

LangChain Architecture

Core Components

Models

Prompts

Output Parsers

Runnables

Chains

Workflows

Module 3 — Models, Prompts & Output Parsing

Learn how to connect language models with prompts and structure model outputs for reliable application workflows.

LLM Integration

Chat Models

Prompt Templates

System & User Messages

Dynamic Prompts

Output Parsers

Structured Outputs

Model Configuration

Module 4 — Chains & LangChain Workflows

Build structured workflows by connecting prompts, models, tools, and processing steps using LangChain components.

Chains

Sequential Workflows

Runnable Sequences

Runnable Components

Chain Composition

Conditional Workflows

Workflow Design

Error Handling

Module 5 — Memory & Context Management

Understand how LangChain applications can maintain conversation context and manage information across interactions.

Memory Fundamentals

Conversation History

Context Management

Short-Term Memory

Message History

State Management

Context-Aware Applications

Memory Use Cases

Module 6 — Tools, APIs & Function Integration

Learn how LangChain applications can interact with external tools, APIs, databases, and services.

LangChain Tools

Tool Calling

Function Integration

API Integration

REST APIs

External Services

Database Connectivity

Tool-Based Workflows

Module 7 — AI Agents with LangChain

Build AI agents that can select tools, execute tasks, and perform multi-step workflows using LangChain.

Agent Fundamentals

LangChain Agents

Agent Executors

Tool Selection

Agent Workflows

Multi-Step Tasks

Agent Decision Making

Agent Use Cases

Module 8 — Embeddings & Vector Stores

Understand how embeddings and vector stores support semantic search and knowledge-based AI applications.

Embedding Fundamentals

Text Embeddings

Semantic Similarity

Vector Stores

Pinecone

FAISS

Indexing

Similarity Search

Module 9 — RAG with LangChain

Build retrieval-augmented applications that retrieve relevant information from documents and knowledge sources before generating responses.

RAG Fundamentals

Document Loading

Text Splitting

Chunking Strategies

Embeddings

Vector Retrieval

Context Injection

LangChain RAG Pipeline

RAG Evaluation

Module 10 — Document & Knowledge Applications

Apply LangChain to practical document and knowledge-based applications such as question answering, summarization, and information retrieval.

Document Processing

PDF Processing

Document Question Answering

Knowledge Assistants

Document Summarization

Information Extraction

Semantic Search

Enterprise Knowledge Applications

Module 11 — LangGraph & Advanced Workflows

Understand how LangGraph can extend LangChain-based applications for stateful, multi-step, and controllable AI workflows.

Introduction to LangGraph

LangChain and LangGraph

Graph-Based Workflows

Nodes & Edges

State Management

Conditional Workflows

Multi-Step AI Workflows

Agent Orchestration

Module 12 — Testing, Deployment & Capstone Project

Apply LangChain knowledge to develop, test, and prepare practical AI applications for deployment.

Application Testing

Output Evaluation

Error Handling

Logging

Performance Considerations

Application Deployment

Project Documentation

Capstone Project

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Additional Program Highlights

Comprehensive study materials and resources

Professional resume building session

Master your interview skills

Real-world project demonstrations

Upcoming Batches

✓ Selected

Weekdays

📅 02 Sept 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

Weekends

📅 05 Sept 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

Weekdays

📅 07 Sept 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

Weekdays

📅 08 Sept 2026

⏰ Time

07:00 AM11:00 AM

02:00 PM09:00 PM

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Who Should Take LangChain Training?

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Working Professionals

Ops/Administrators/HR

Developers

BA/QA Engineers

Cloud / Infra

IT Professionals

Non-IT Career Switchers

Fresh Graduates

Career Opportunities After Learning LangChain

LangChain Developer

AI Application Developer

LLM Application Developer

AI Engineer

Generative AI Developer

RAG Developer

AI Solutions Engineer

AI Automation Engineer

LangChain Developer

AI Application Developer

LLM Application Developer

Key Projects

LangChain

Infosys – AI Customer Support Automation using LangChain

Scenario: Build a LangChain chatbot that uses conversation context, company FAQs, and product information to provide relevant customer support responses.

Live Work:

Build LangChain chatbot
Connect knowledge sources
Test responses

Outcome: Context-aware AI support chatbot

Deloitte – Document Q&A Assistant

Scenario: Develop a LangChain-based document assistant that processes business documents, retrieves relevant information, and generates context-based answers.

Live Work:

Process business documents
Build retrieval pipeline
Test Q&A responses

Outcome: AI-powered document assistant

Cognizant – Enterprise Knowledge Search

Scenario: Create a LangChain knowledge-search application using embeddings and vector retrieval to help users find relevant information from internal business content.

Live Work:

Create document index
Implement semantic search
Generate contextual answers

Outcome: Enterprise AI knowledge search

Capgemini – Automated AI Workflow

Scenario: Develop a LangChain workflow that connects AI models with external tools and APIs to automate a multi-step business process.

Live Work:

Design AI workflow
Integrate external tools
Test automated tasks

Outcome: Automated LangChain workflow

Placement Process

Live Class with Industry Use Cases

Interactive learning
Real-world examples
Expert guidance
Doubt resolution

Daily Assignment & Weekly Assessments

Hands-on practice
Concept reinforcement
Weekly evaluation
Timely feedback

Project Testing & Deployment

Project development
Testing practice
Deployment exposure
Portfolio creation

Interview Preparation (Mock, PD, Alumni Session)

Mock interviews
Personal development
Alumni guidance
Confidence building

Resume Building

Resume crafting
Industry-focused format
Skills highlighting
Professional presentation

Placement

Job assistance
Interview support
Career guidance
Opportunity access

Latest Hiring

No hiring posts

Recently Placed Candidates

No placements available

Latest Hiring

No hiring posts

Our Success Mantra

Commitment

Ensuring quality training every day

Fulfillment

Meeting learning goals with confidence

Accomplishment

Students achieving industry-ready expertise

Our Learner Voice

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Beyond Courses:

Additional Support We Provide

24/7 Support

LinkedIn Profile

Resume Writing

Alumni Sessions

Interview Preparation

Live Projects

What Makes TechPratham Training Different?

Feature

TechPratham Advantage

Industry Standard Institutes

Real-World Implementation

Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.

Restricted or simulation-based access that lacks real-world complexity.

Subject Matter Experts

Mentorship from certified professionals with 15+ years of global industry experience.

Generic instructors with no hands-on implementation background.

2026 Ready Curriculum

AI-driven curriculum with advanced platform integrations and real-world configurations.

Basic, outdated syllabus that misses key technical integrations.

Daily & Weekly assignments

Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.

Self-paced learning with no accountability or progress tracking.

End-to-End Lifecycle

Hands-on project testing and deployment with portfolio-ready real-world exposure.

Basic lab exercises without any deployment or testing practice.

Interview Readiness

Structured interview preparation including mock interviews, PD sessions, and alumni guidance.

Minimal support limited to a generic certificate of completion.

Placement Support

Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.

Basic career tips with no direct industry connections.

Training Support

24/7 technical doubt resolution and personalized mentoring support.

Limited mentor availability and no support after class hours.

Affordable Fees

Competitive fixed pricing with flexible payment options and transparent fee structure.

Inflated fees with hidden costs and low return on investment.

Real-World Implementation

Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.

Restricted or simulation-based access that lacks real-world complexity.

Subject Matter Experts

Mentorship from certified professionals with 15+ years of global industry experience.

Generic instructors with no hands-on implementation background.

2026 Ready Curriculum

AI-driven curriculum with advanced platform integrations and real-world configurations.

Basic, outdated syllabus that misses key technical integrations.

Daily & Weekly assignments

Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.

Self-paced learning with no accountability or progress tracking.

End-to-End Lifecycle

Hands-on project testing and deployment with portfolio-ready real-world exposure.

Basic lab exercises without any deployment or testing practice.

Interview Readiness

Structured interview preparation including mock interviews, PD sessions, and alumni guidance.

Minimal support limited to a generic certificate of completion.

Placement Support

Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.

Basic career tips with no direct industry connections.

Training Support

24/7 technical doubt resolution and personalized mentoring support.

Limited mentor availability and no support after class hours.

Affordable Fees

Competitive fixed pricing with flexible payment options and transparent fee structure.

Inflated fees with hidden costs and low return on investment.

What is LangChain and why is it used?

What will I learn in a LangChain course?

Is LangChain training suitable for beginners?

Do I need Python to learn LangChain?

What can I build with LangChain?

What is LangChain RAG?

Industry-Recognized Certification

LangChain Course

News Highlights

TechPratham Introduces Hire-Train-Deploy Model to Transform HR & ERP Talent in the AI Era

TechPratham Empowering Future Professionals Through AI-Focused HR & ERP Training

Featured In

TechPratham Gains Recognition for Bridging the HR & ERP Skills Gap with Hire-Train-Deploy

TechPratham's Hire-Train-Deploy Approach Reshaping HR & ERP Careers in the AI-Driven Industry

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LangChain

Enquire This Course

Placement Client

About LangChain

Training Plan

About trainer

Decks & Updated Content

e-Book

Assignments & MCQs

Video Recording

Projects

Resume Building

Interview Preparation

LangChain Course Curriculum

Introduction to LangChainModule 1 — Introduction to LangChain

Module 2 — LangChain Architecture & Core Components

Module 3 — Models, Prompts & Output Parsing

Module 4 — Chains & LangChain Workflows

Module 5 — Memory & Context Management

Module 6 — Tools, APIs & Function Integration

Module 7 — AI Agents with LangChain

Module 8 — Embeddings & Vector Stores

Module 9 — RAG with LangChain

Module 10 — Document & Knowledge Applications

Module 11 — LangGraph & Advanced Workflows

Module 12 — Testing, Deployment & Capstone Project

AI Courses Courses

Additional Program Highlights

Upcoming Batches

Who Should Take LangChain Training?

Career Opportunities After Learning LangChain

Key Projects

LangChain

Infosys – AI Customer Support Automation using LangChain

Live Work:

Deloitte – Document Q&A Assistant

Live Work:

Cognizant – Enterprise Knowledge Search

Live Work:

Capgemini – Automated AI Workflow

Live Work:

Placement Process

Live Class with Industry Use Cases

Daily Assignment & Weekly Assessments

Project Testing & Deployment

Interview Preparation (Mock, PD, Alumni Session)

Resume Building

Placement

Latest Hiring

Recently Placed Candidates

Latest Hiring

Our Success Mantra

Commitment

Fulfillment

Accomplishment

Our Learner Voice

Beyond Courses:

What Makes TechPratham Training Different?

What is LangChain and why is it used?

What will I learn in a LangChain course?

Is LangChain training suitable for beginners?

Do I need Python to learn LangChain?

What can I build with LangChain?

What is LangChain RAG?

What is LangChain?

What are the core components of LangChain?

What is a LangChain chain?

What are LangChain agents?

What is RAG in LangChain?

What is a vector store?

LangChain Certification

Industry-Recognized Certification

News Highlights

Featured In