Course Objectives
Q1. Why should I learn LlamaIndex and LangGraph?
LlamaIndex and LangGraph are among the most popular frameworks for building intelligent AI applications powered by Large Language Models. Learning these technologies enables you to develop enterprise-grade AI assistants, RAG systems, and autonomous AI workflows used in modern businesses.
Q2. What practical skills will I gain from this course?
You will learn to build Retrieval-Augmented Generation (RAG) applications, create AI agents, integrate vector databases, connect Large Language Models, design intelligent workflows, and deploy production-ready Generative AI applications using industry-standard frameworks.
Q3. How does this course support my AI career?
This course develops practical skills in Generative AI application development and AI workflow automation. It prepares you to work on enterprise AI projects involving intelligent assistants, document intelligence, knowledge retrieval, and AI-powered business solutions.
Q4. Is this course suitable for beginners?
Yes. The course starts with Python and Generative AI fundamentals before progressing to advanced concepts such as RAG pipelines, AI agents, LangGraph workflows, and enterprise AI architecture. Step-by-step practical sessions make learning simple for beginners.
Q5. What will I achieve after completing this training?
By the end of the course, you will be able to design, develop, deploy, and optimize enterprise-grade AI applications using LlamaIndex, LangGraph, vector databases, and modern Large Language Models. You will also complete real-world AI projects that strengthen your technical portfolio.
Popular Techniques Covered in This Course
LlamaIndex
LangGraph
RAG Development
AI Agents
Prompt Engineering
Vector Databases
LLM Integration
Workflow Automation
Knowledge Retrieval
AI Application Deployment
Get Hands-on Knowledge about Real-Time Projects
Project 1
Enterprise AI Knowledge Assistant
Build an intelligent enterprise knowledge assistant using LlamaIndex and Retrieval-Augmented Generation (RAG). Integrate company documents, create searchable knowledge bases, and generate context-aware responses using Large Language Models.
Project 2
AI Customer Support Chatbot
Develop a production-ready AI chatbot capable of answering customer queries using vector databases, document retrieval, prompt engineering, and LangGraph workflow orchestration. Implement conversation memory and intelligent response generation.
Project 3
Multi-Agent Business Workflow Automation
Create a multi-agent AI system using LangGraph where specialized AI agents collaborate to perform document analysis, task planning, report generation, and business workflow automation with intelligent decision-making capabilities.
Project 4
AI Document Intelligence Platform
Build a document intelligence application capable of processing PDFs, extracting information, performing semantic search, summarizing documents, and answering contextual questions using LlamaIndex and enterprise RAG architecture.
Project 5
AI Research & Recommendation System
Develop an AI-powered research assistant that retrieves information from multiple data sources, performs intelligent document retrieval, ranks search results, generates summaries, and provides context-aware recommendations using LlamaIndex and LangGraph.
Key Features
Edubrights offers LlamaIndex & LangGraph Training in virtual mode with expert trainers. Here are the key features,
40 Hours Course Duration
100% Job Oriented Training
Industry Expert Faculties
Free Demo Class Available
Completed 500+ Batches
Certification Guidance
Curriculum
Module 1: Introduction to Generative AI
- Fundamentals of Generative AI
- Large Language Models (LLMs)
- AI Application Architecture
- LlamaIndex Overview
- LangGraph Overview
- Environment Setup
Module 2: Python for AI Development
- Python Essentials
- Virtual Environments
- Package Management
- API Basics
- File Handling
- Project Structure
Module 3: LlamaIndex Fundamentals
- Data Connectors
- Document Loaders
- Index Creation
- Query Engine
- Retrieval Concepts
- Best Practices
Module 4: Retrieval-Augmented Generation (RAG)
- RAG Architecture
- Embeddings
- Semantic Search
- Context Retrieval
- Chunking Strategies
- Response Generation
Module 5: Vector Databases
- Vector Embeddings
- Similarity Search
- ChromaDB
- FAISS
- Pinecone Basics
- Data Indexing
Module 6: LangGraph Fundamentals
- Graph-Based Workflows
- State Management
- Nodes & Edges
- Conditional Routing
- Workflow Execution
- Debugging
Module 7: AI Agent Development
- Single AI Agents
- Multi-Agent Systems
- Agent Collaboration
- Memory Management
- Tool Integration
- Autonomous Workflows
Module 8: Prompt Engineering
- Prompt Design
- System Prompts
- Prompt Templates
- Context Optimization
- Output Control
- Prompt Testing
Module 9: LLM Integration
- OpenAI APIs
- Local LLMs
- Model Selection
- API Authentication
- Response Optimization
- Error Handling
Module 10: Enterprise AI Applications
- Document Intelligence
- Knowledge Base Systems
- Chatbots
- AI Assistants
- Workflow Automation
- Business Use Cases
Module 11: Deployment & Monitoring
- Application Deployment
- Docker Basics
- Cloud Deployment
- Performance Monitoring
- Security Best Practices
- Scalability
Module 12: Real-Time Projects & Certification Preparation
- Enterprise AI Project
- Multi-Agent Workflow
- RAG Chatbot
- Knowledge Assistant
- Mock Interviews
- Project Presentation
Receive Training From Our Skilled and Effective Trainers
Industry-Experienced LlamaIndex & LangGraph Trainers
Learn from experienced Generative AI professionals with hands-on expertise in LlamaIndex, LangGraph, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), AI agents, vector databases, and enterprise AI application development. Gain practical knowledge through real-world projects involving intelligent assistants, document intelligence, and AI workflow automation.
Corporate Training Expertise
Our trainers have delivered Generative AI, Machine Learning, Python, and AI Engineering training for leading multinational companies, including TCS, Infosys, HCLTech, Accenture, Cognizant, Wipro, Capgemini, IBM, and other top organizations. Learn enterprise AI development practices, RAG implementation strategies, and intelligent automation techniques used in modern software development.
Simple & Practical Learning Approach
Master LlamaIndex and LangGraph through easy-to-understand explanations, live coding demonstrations, interactive workshops, and practical AI development sessions. Our structured learning approach enables students, freshers, and working professionals to confidently build production-ready Generative AI applications.
Hands-On Project-Based Training
Develop practical expertise by building AI-powered chatbots, Retrieval-Augmented Generation (RAG) systems, multi-agent workflows, enterprise knowledge assistants, document intelligence platforms, vector search applications, and intelligent workflow automation solutions. Gain experience aligned with today's enterprise AI and Generative AI industry requirements.
Latest Generative AI Technologies & Best Practices
Stay updated with the latest LlamaIndex, LangGraph, OpenAI APIs, Retrieval-Augmented Generation (RAG), AI agents, vector databases, prompt engineering, workflow orchestration, cloud deployment, and enterprise Generative AI best practices. Our curriculum is continuously updated to match current industry trends and real-world AI application development.
Become a Certified LangChain – Building LLM Applications Professional
The LlamaIndex & LangGraph Course in Chennai is designed to help learners build practical expertise in developing enterprise-grade Generative AI applications using modern AI frameworks. This training covers LlamaIndex, LangGraph, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), AI agents, vector databases, prompt engineering, workflow orchestration, OpenAI API integration, cloud deployment, and intelligent automation through instructor-led practical sessions.
Course FAQs
1. What are LlamaIndex and LangGraph, and why should I learn them?
LlamaIndex and LangGraph are popular open-source frameworks used to build advanced Generative AI applications powered by Large Language Models (LLMs). They simplify the development of Retrieval-Augmented Generation (RAG) systems, AI agents, and intelligent workflows, making them valuable skills for modern AI development.
2. Who can join the LlamaIndex & LangGraph Course in Chennai?
This course is suitable for students, fresh graduates, Python developers, software engineers, AI engineers, machine learning professionals, data scientists, cloud engineers, automation developers, and IT professionals interested in building modern AI applications.
3. Are there any prerequisites for learning LlamaIndex and LangGraph?
Basic knowledge of Python programming is recommended. Familiarity with machine learning or AI concepts is helpful but not mandatory, as the course begins with Generative AI fundamentals before progressing to advanced AI application development.
4. How long does it take to complete the training?
The course duration depends on your selected learning mode and batch schedule. Most learners complete the training within a few weeks through instructor-led classes, practical labs, AI projects, coding exercises, and guided application development sessions.
5. Will I work on real-world AI projects during the course?
Yes. Practical learning is a core part of the training. You will develop enterprise AI assistants, RAG applications, document intelligence solutions, knowledge retrieval systems, AI agents, and workflow automation projects using LlamaIndex and LangGraph.
6. Which technologies are covered during this course?
The course covers LlamaIndex, LangGraph, Retrieval-Augmented Generation (RAG), Python, Large Language Models (LLMs), OpenAI APIs, vector databases, prompt engineering, AI agents, workflow automation, Docker, cloud deployment, and enterprise AI architecture.
7. What job roles can I pursue after completing this course?
After completing this course, learners can explore careers as AI Engineer, Generative AI Developer, Python Developer, Machine Learning Engineer, LLM Application Developer, AI Solutions Engineer, Data Scientist, Software Engineer, MLOps Engineer, and Intelligent Automation Developer.
8. Are LlamaIndex and LangGraph widely used in the AI industry?
Yes. Many startups and enterprise organizations use these frameworks to build intelligent chatbots, AI assistants, document processing systems, customer support automation, enterprise knowledge bases, and production-ready Generative AI applications.
9. Is this course suitable for beginners?
Absolutely. The course follows a structured learning path beginning with Python and Generative AI fundamentals before introducing advanced concepts such as AI agents, vector databases, RAG pipelines, and LangGraph workflow orchestration.
10. Why should I choose LlamaIndex & LangGraph Training in Chennai?
Chennai has a growing ecosystem of AI startups, software companies, and enterprise technology organizations adopting Generative AI solutions. This course provides practical, industry-oriented training that aligns with current AI development standards and real-world business applications.
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