Generative AI & LLM Development Course

Generative AI & LLM Development

Learn to develop real-world AI solutions with OpenAI, Hugging Face, LangChain, Vector Databases, Fas

The Generative AI & LLM Development Course in Calicut is a comprehensive 4-month industry-focused program designed to equip learners with the skills to build intelligent AI applications using the latest Large Language Models (LLMs), Generative AI frameworks, and modern development tools. This course combines AI fundamentals with practical implementation, enabling students to create enterprise-ready AI solutions for real-world business challenges.

Students will gain hands-on experience in Prompt Engineering, OpenAI APIs, Hugging Face Transformers, LangChain, LangGraph, Retrieval-Augmented Generation (RAG), AI Agents, Vector Databases, FastAPI, and cloud deployment. The curriculum emphasizes building scalable AI-powered applications such as intelligent chatbots, AI assistants, document question-answering systems, recommendation engines, content generators, and workflow automation platforms.

Throughout the program, learners will work on multiple real-time projects, industry case studies, and capstone applications while following best practices in AI security, responsible AI, model optimization, and deployment. By the end of the course, students will have a professional AI portfolio and the practical expertise required for careers as Generative AI Developers, LLM Engineers, AI Application Developers, Prompt Engineers, AI Solution Architects, and Intelligent Automation Specialists.

Month 1 - Python Programming & AI Foundations

  • Python Fundamentals
  • Variables, Data Types & Operators
  • Control Statements
  • Functions & Modules
  • Object-Oriented Programming
  • Exception Handling
  • File Handling
  • Virtual Environment & Package Management
  • NumPy
  • Pandas
  • Matplotlib & Seaborn
  • Introduction to AI, ML & Deep Learning
  • Git & GitHub Essentials

Month 2 - NLP, Transformers & Prompt Engineering

  • Natural Language Processing Fundamentals
  • Text Cleaning & Tokenization
  • Word Embeddings (Word2Vec, GloVe)
  • Sentence Transformers
  • Attention Mechanism
  • Transformer Architecture
  • BERT, GPT, T5 Overview
  • Llama, Mistral, Gemma Models
  • Prompt Engineering Fundamentals
  • Zero-shot, One-shot & Few-shot Prompting
  • Chain of Thought Prompting
  • Role Prompting
  • Structured Output Prompting
  • Prompt Evaluation & Optimization

Month 3 - LLM Development & RAG Systems

  • OpenAI API
  • Azure OpenAI
  • Google Gemini API
  • Anthropic Claude API
  • Hugging Face Transformers
  • Model Inference
  • Embeddings
  • Vector Databases
  • FAISS
  • ChromaDB
  • Pinecone
  • Milvus
  • Document Processing
  • Chunking Strategies
  • Semantic Search
  • Retrieval-Augmented Generation (RAG)
  • Production RAG Architecture
  • Document Question Answering
  • Knowledge Base Systems

Month 4 - AI Agents, LangChain & Full Stack AI Development

  • LangChain Fundamentals
  • Prompt Templates
  • Chains & Sequential Chains
  • Memory Management
  • Output Parsers
  • LangGraph
  • AI Agents
  • Multi-Agent Systems
  • Tool Calling
  • Function Calling
  • Model Context Protocol (MCP)
  • FastAPI
  • REST API Development
  • Authentication & JWT
  • React.js for AI Applications
  • Chat UI Development
  • Streamlit
  • Gradio
  • Docker
  • Kubernetes Basics
  • Cloud Deployment (AWS/Azure/GCP)

Last 15 Days - Advanced Generative AI Projects

  1. Enterprise AI Chatbot using RAG
  2. PDF Chat Application
  3. AI Resume Analyzer
  4. Voice AI Assistant (Speech-to-Text & Text-to-Speech)
  5. Medical AI Assistant
  6. Legal Document Analysis System
  7. AI Code Generator & Debugger
  8. Multimodal AI Application (Text + Image)
  9. AI Email Automation System
  10. AI Customer Support Agent
  11. Research Paper Summarizer
  12. Knowledge Management System
  13. Autonomous AI Agent Workflow
  14. Capstone Industry Project
  15. Portfolio Development & Deployment

Career Preparation & Placement

  • System Design for AI Applications
  • LLM Interview Questions
  • Python Coding Practice
  • GitHub Portfolio Development
  • Resume Building
  • LinkedIn Profile Optimization
  • Mock Technical Interviews
  • AI Coding Challenges
  • Open Source Contributions
  • Placement Assistance



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