Master Program in Generative AI

🧠 Introduction

The Master’s Program in Generative AI offers in-depth training in building, training, and deploying generative models like Large Language Models (LLMs), GANs, Diffusion Models, and Transformer-based systems. Designed for the future of AI-driven content creation, automation, and intelligence, this program combines theory and hands-on development using cutting-edge technologies.

💼 Career Opportunities

Generative AI Engineer
LLM Developer / NLP Scientist
AI Research Scientist
Data Scientist (AI/ML focus)
Product Engineer – Conversational AI
AI Consultant / Prompt Engineer
Startup Founder in Creative AI / EdTech / HealthTech

🎯 Key Areas of Study

Transformer Architectures (GPT, BERT, T5)
Large Language Models & Fine-Tuning
Text, Image, Audio, and Video Generation
GANs and Diffusion Models
Ethics, Bias, and Explainability in Generative AI
Multimodal AI and Human-AI Interaction
Prompt Engineering and Retrieval-Augmented Generation (RAG)

📘 Semester-wise Syllabus

Semester 1: Core Concepts of Generative AI

Subject	Subtopics
Introduction to Deep Learning	ANNs, CNNs, RNNs, PyTorch/TensorFlow basics
Transformers & Attention Mechanisms	Encoder-decoder, self-attention, positional encoding
Natural Language Processing	Tokenization, word embeddings, BERT, GPT architecture
Generative Adversarial Networks (GANs)	Generator-discriminator models, DCGANs, conditional GANs
Practical Lab I	Text generation, GAN image synthesis, HuggingFace fine-tuning

Semester 2: Advanced Generative Systems & Applications

Subject	Subtopics
Large Language Models & Fine-Tuning	LLM APIs, parameter-efficient fine-tuning, instruction tuning
Diffusion & Multimodal Models	Denoising models, DALL·E, Stable Diffusion, CLIP, Whisper
Prompt Engineering & RAG Systems	Prompt types, chaining, vector databases, LangChain
Ethics and Safety in GenAI	Bias, hallucinations, responsible deployment, governance
Capstone Project	Build a GenAI app (chatbot, image AI, audio assistant, etc.)