Generative AI refers to a type of artificial intelligence that can create new content, such as text, images, music, or even video, based on patterns and data it has been trained on. Unlike traditional AI that typically performs tasks like classification or prediction, generative AI models are capable of generating novel outputs.
Week-1. Introduction to Generative AI
History, Applications, AI vs Generative AI
Week-2. Deep Learning Basics
Neural Networks, Backpropagation, Transformers
Week-3. Introduction to Large Language Models (LLMs)
GPT, BERT, LLaMA, Claude, Mistral
Week-4. Fine-Tuning LLMs
LoRA, PEFT, RLHF, Parameter Efficient Tuning
Week-5. Prompt Engineering
Zero-Shot, Few-Shot, Chain-of-Thought (CoT), RAG
Week-6. Generative Adversarial Networks (GANs)
DCGAN, StyleGAN, CycleGAN
Week-7. Variational Autoencoders (VAEs)
Latent Space Representations, Applications
Week-8. Stable Diffusion & DALL·E
Text-to-Image, Fine-Tuning with DreamBooth
Week-9.AI Video Generation
RunwayML, Sora AI, Text-to-Video Models
Week-10.Text-to-Speech & AI Voice Models
Whisper, ElevenLabs, Custom AI Voices
Week-11. AI Music Generation
Jukebox, Riffusion, AI Composers
Week-12. AI Agents & AutoGPT
LangChain, Autonomous Agents, Agentic AI
Week-13. Reinforcement Learning for Generative AI
RLHF, AI Alignment, Ethical Considerations
Week-14. Building Generative AI APIs
FastAPI, Hugging Face Spaces, Gradio
Week-15. Cloud Deployment
AWS, GCP, Hugging Face Inference APIs
Week-16. Capstone Project – Part 1
Data Collection, Model Selection
Week-17. Capstone Project – Part 2
Fine-Tuning, Optimization, Deployment