Generative AI is reshaping how the world creates content, builds products, and solves complex problems. This course is designed to take you on a comprehensive journey through the full stack of Generative AI systems β empowering you to become a job-ready AI developer capable of building and deploying large-scale AI applications.
Starting from the fundamentals of deep learning and modern transformer architectures, you will explore how cutting-edge models like GPT, LLaMA, Stable Diffusion, and other foundation models learn to generate language, images, audio, and code. You will gain hands-on experience with prompt engineering, fine-tuning, instruction tuning, Retrieval-Augmented Generation (RAG), and alignment techniques that make AI models more accurate, reliable, and domain-specific.
But we donβt stop at model development. You will learn full-stack implementation β integrating GenAI into real-world applications using backend frameworks, vector databases, scalable cloud infrastructure, and MLOps best practices. Youβll build chatbots, multimodal assistants, AI agents, and enterprise-grade solutions that can efficiently handle production workloads.
By the end of this course, youβll have the knowledge and confidence to design and deploy your own state-of-the-art generative AI systems, contributing to tomorrowβs intelligent innovations β today.
β Fundamentals of Generative AI and Transformer Architectures
β Prompt Engineering & LLM Behavior Optimization
β Fine-tuning & Domain Adaptation Techniques
β RAG (Retrieval-Augmented Generation) with Vector Databases
β Image, Text, and Multimodal Generation Tools
β Backend Integration using APIs and FastAPI
β Building Full-Scale AI Products & Agents
β Containerization, Deployment & MLOps workflows
β Security, Safety & Ethical considerations in GenAI
Develop and deploy a fully-featured Generative AI application β integrating custom-tuned models, vector search, and a production-ready UI.