A Beginner’s Guide to Generative AI: An Introductory Path to Diffusion Models, ChatGPT, and LLMs by Deepshikha Bhati, Fnu Neha, Angela Guercio, Md Amiruzzaman, Aloysius Bathi Kasturiarachi

A Beginner’s Guide to Generative AI: An Introductory Path to Diffusion Models, ChatGPT, and LLMs by Deepshikha Bhati, Fnu Neha, Angela Guercio, Md Amiruzzaman, Aloysius Bathi Kasturiarachi

The core philosophy of A Beginner's Guide to Generative AI is that understanding modern AI requires trace-level evolutionary context, not just simple interface prompting. The authors address a critical gap in contemporary tech education: while many entry-level guides focus exclusively on writing prompts inside a web browser, and advanced manuals jump straight into deep vector matrices, beginners are left without a firm grasp of underlying model mechanics. This textbook demystifies the technology by breaking down exactly how machines learn to generate coherent text and pixels, treating generative AI as a natural progression of neural networks.

Rather than limiting the discussion to a single tool or company, the book provides a sweeping overview of the modern generative spectrum. It takes readers from early probabilistic language approaches (like n-grams) up through Transformers, the multi-layered ChatGPT architecture, Google's Gemini ecosystem, and deep Diffusion Models for visual processing. By pairing clear architectural breakdowns with real-world industry case studies across healthcare, legal technology, and business analytics, the authors ensure readers build a solid conceptual foundation capable of adapting to rapid industry shifts.