🤖 Generative AI Track

Generative AI Course in Chennai — Build Production LLM Apps

Master LangChain, RAG, vector databases, and LLM orchestration. Build ChatGPT-style apps, document Q&A systems, and AI copilots that companies hire for right now.

View Syllabus ↓

6 Modulescovered

5+ Projectsbuilt

LangChain + RAGtools

AI Developeroutcome

📚 Course Syllabus

Generative AI Skills You'll Master

Every module is outcome-driven — you build something real at the end of each one.

LLMsGPT-4ClaudeLLaMAGeminiTokenizationContext windowsAPI usage

Understand how LLMs generate text token by token

Compare GPT-4, Claude, LLaMA, and Gemini capabilities

Call and manage LLM APIs programmatically

Understand and use the most powerful AI models available today

LangChainChainsAgentsToolsMemoryPromptTemplatesLLMChainConversationChain

Build modular LLM applications with LangChain

Add persistent memory to AI conversations

Create AI agents that use external tools

Build modular, scalable GenAI workflows like a senior engineer

EmbeddingsSemantic searchFAISSPineconeChromaWeaviateCosine similarityANN

Convert documents into semantic vector embeddings

Build similarity search over millions of documents

Choose and deploy the right vector database

Build semantic search systems that understand meaning, not just keywords

RAG pipelineDocument loadingText splittingRetrieval chainsContext injectionHallucination reductionEvaluation

Build end-to-end RAG pipelines from scratch

Reduce hallucinations with retrieved context

Evaluate RAG quality with RAGAS framework

Build AI that answers accurately from your own documents — zero hallucinations

Multi-doc RAGConversational RAGSQL agentsAPI agentsFunction callingAutonomous agents

Build conversational agents that remember and reason

Create SQL-querying agents from natural language

Connect LLMs to external APIs and databases

Build 4 enterprise-grade GenAI applications for your portfolio

StreamlitFastAPIDockerCloud deployRate limitingCachingCost optimizationMonitoring

Deploy full-stack GenAI apps to production

Implement caching to reduce API costs by 70%

Monitor LLM usage and latency in real time

Deploy production GenAI systems that scale and stay reliable

🛠 Tech Stack

GenAI Tools & Frameworks

Industry-standard tools you'll use throughout this program — exactly what employers want.

🦜

LangChain

LLM orchestration

🤖

OpenAI API

GPT-4 / 3.5

📌

Pinecone

Vector DB

🔍

FAISS

Local vector search

🎯

Streamlit

App deploy

⚡

FastAPI

API layer

🐳

Docker

Containerization

☁️

AWS / GCP

Cloud hosting

💻 Real Projects

GenAI Applications You'll Build

Portfolio-ready projects that demonstrate your skills to recruiters from day one.

PROJECT 01

"Ask the PDF" Chatbot

Upload any PDF and chat with it — RAG pipeline with LangChain + FAISS, deployed as a Streamlit app.

LangChainFAISSOpenAIStreamlit

✅ Live document Q&A app — most impressive portfolio piece

PROJECT 02

AI Knowledge Assistant

Multi-document RAG system with conversation memory, topic routing, and source attribution.

LangChainPineconeOpenAIFastAPI

✅ Enterprise-grade knowledge management system

PROJECT 03

Natural Language → SQL Engine

Convert plain English questions into SQL queries and return results from real databases.

LangChainOpenAISQLiteFastAPI

✅ Deployed NL-to-SQL API for business intelligence

PROJECT 04

Model Comparator Dashboard

Benchmark GPT-4 vs Claude vs LLaMA on speed, cost, and quality across 50 test cases.

LangChainOpenAIAnthropicStreamlit

✅ Real data-driven LLM selection tool

PROJECT 05

Resume Screener with RAG

Embed job descriptions and resumes into vector space, rank and shortlist candidates automatically.

LangChainFAISSOpenAIPandas

✅ Automated hiring tool processing 100+ resumes

🎯 Transformation

GenAI Engineer Roles You'll Land

By the end of this program, you won't just have knowledge — you'll have career-changing proof.

🤖

GenAI Developer

₹12L–₹30L roles at top companies

🏗

System Builder

Design complete LLM-powered architectures

🔍

RAG Expert

Build hallucination-free AI from your data

🚀

Day-One Ready

Ship real AI products immediately after course

🏢 Placement Network

Our Students Work Here

Frequently Asked Questions

About the Generative AI Course in Chennai

The Generative AI course is 3 months long with live expert sessions covering LLMs, LangChain, RAG, vector databases and AI agent design.

You will learn OpenAI API, LangChain, LlamaIndex, Pinecone, FAISS, ChromaDB, HuggingFace and Streamlit to build and deploy LLM-powered applications.

You will build a ChatGPT-style assistant, a RAG-based document search system, an AI content generator, a multi-agent research tool and an LLM-powered coding assistant.

Generative AI engineers in India earn ₹10–25 LPA at entry to mid level. Senior LLM engineers with RAG and agent experience command ₹30 LPA and above.

Yes. Demand for Generative AI skills is exploding across product companies, IT services and startups in Chennai and across India.

Yes. AlgoAcademy provides resume building, mock interviews, portfolio guidance and referrals to help you land Generative AI engineer roles in Chennai and across India.

Yes. The course starts with Python fundamentals. No prior coding experience is required.