Applied Generative AI

By: Ajit Singh

Narrated by: Virtual Voice

"Applied Generative AI" is a comprehensive, student-centric textbook designed to navigate the dynamic and transformative world of Generative Artificial Intelligence. Authored for B.Tech and M.Tech students in computer science, information technology, and related engineering disciplines, this book serves as a one-stop resource that bridges the gap between foundational theory and hands-on application.


Key Features:


1. Practical-First Approach: Every theoretical concept is paired with simple, easy-to-understand code snippets and practical examples using popular Python libraries like PyTorch, TensorFlow, and Hugging Face.
2. Structured & Progressive Learning: The 11 chapters are logically sequenced to build knowledge from the ground up, ensuring a smooth learning curve from basic concepts to advanced, state-of-the-art models.
3. Focus on Foundational Architectures: In-depth, intuitive explanations of the key architectures—GANs, VAEs, Diffusion Models, and especially the Transformer—that are critical for a deep understanding of the field.
4. Dedicated Ethics Chapter: A full chapter on Responsible AI addresses crucial topics like bias, fairness, misinformation, and environmental impact, preparing students to be conscientious innovators.
5. End-to-End Capstone Project: The final chapter is a complete, hands-on project that integrates all the concepts learned, guiding the student from idea to a working application.
6. Coverage of Latest Topics: Includes up-to-date content on Large Language Models (LLMs), prompt engineering techniques like Chain-of-Thought, and Retrieval-Augmented Generation (RAG).
7. Multidisciplinary Applications: Features a wide range of case studies showing how Generative AI is applied across various domains, including software engineering, art, business, and science.



The book culminates in a capstone project that challenges students to integrate their learning into a single, cohesive, full-stack Generative AI application. This project-based learning approach ensures that by the end of this book, the reader will have transitioned from a student of AI to a practitioner, equipped with the confidence and competence to build the next generation of intelligent systems.