Masterclass: AI Engineering & LLM Application Development

Build production-ready Generative AI software using large language models.

12 Weeks
Online / Offline
English & Tamil
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Course Overview

Generative AI has fundamentally shifted the software landscape. It is no longer enough to just use ChatGPT; modern engineers must know how to build software powered by Large Language Models. This masterclass bridges the gap between AI theory and production software engineering. You will construct highly advanced RAG (Retrieval-Augmented Generation) pipelines, implement autonomous agents that can call external APIs, utilize cutting-edge vector databases, and deploy secure, hallucination-resistant AI applications.

Skills You Will Master

LangChain Vector Databases (Pinecone) Retrieval-Augmented Gen (RAG) OpenAI API / Open-Source LLMs Model Fine-Tuning AI Agents

Course Curriculum

1. Introduction to Modern AI Engineering

  • The shift from traditional ML to Generative AI
  • Foundation Models vs Specialized Models
  • The AI Application Stack
  • Setting up the Python AI Environment

2. Working with Foundation Model APIs

  • OpenAI API, Anthropic, and Gemini integration
  • Prompt Engineering for Developers
  • Handling API limits and asynchronous calls
  • System prompts and context windows

3. LangChain Fundamentals

  • Chains, Prompts, and Memory
  • Output Parsers and structured responses
  • LangChain Expression Language (LCEL)
  • Debugging chains with LangSmith

4. Vector Databases & Embeddings

  • Understanding Text Embeddings
  • Introduction to Vector Databases (Pinecone, ChromaDB)
  • Similarity search algorithms (Cosine, Euclidean)
  • Indexing and querying vectors

5. Retrieval-Augmented Generation (RAG)

  • The RAG Architecture
  • Document loading and chunking strategies
  • Building a Q&A system on custom data
  • Evaluating retrieval performance

6. Advanced RAG Techniques

  • Query transformations and routing
  • Re-ranking retrieved documents
  • Handling tables and complex document layouts
  • Multi-modal retrieval

7. AI Agents & Tool Calling

  • Function Calling with LLMs
  • Building Autonomous Agents
  • Giving agents access to APIs and databases
  • Managing agent memory and execution loops

8. Open-Source Models & Local Execution

  • HuggingFace ecosystem overview
  • Running LLaMA / Mistral locally
  • Hardware constraints (VRAM, Quantization)
  • Ollama integration

9. Model Fine-Tuning Basics

  • When to fine-tune vs use RAG
  • Instruction tuning and PEFT (LoRA)
  • Preparing custom datasets
  • Deploying a fine-tuned model

10. Production Deployment & AI Safety

  • Deploying AI apps via FastAPI / Next.js
  • Prompt injection attacks and mitigation
  • Monitoring token usage and costs
  • Evaluating hallucination rates

Local Training Campuses & Placement Drives

Classroom & hybrid batches in Coimbatore & Chennai

Coimbatore • Training

AI Engineering & LLM Application Development
Chennai • Training

AI Engineering & LLM Application Development

Take the Next Step in Your Career

Join our comprehensive Masterclass: AI Engineering & LLM Application Development program and gain real-world skills that employers demand.

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