A Beginner’s Guide to Generative AI

A Beginner’s Guide to Generative AI: An Introductory Path to Diffusion Models, ChatGPT, and LLMs

Architect your creative logic and master the high-performance protocols of modern intelligence engineering. A Beginner’s Guide to Generative AI provides a definitive, practitioner-first roadmap to the most significant shift in artificial intelligence since the digital revolution. Learn how to move beyond basic automation to high-velocity, generative discovery—bridging the gap between a standalone prompt and a sophisticated, AI-integrated ecosystem—ensuring your technical projects are resilient, scalable, and ready for the 2026 global technology landscape.

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What You Will Learn:

Foundations of Generative Architecture: Master the core principles of how machines learn to create text and images, requiring no prior AI knowledge to maintain peak operational integrity.

Modern Model Workflows: Step-by-step guidance on the intricate workings of Transformers, ChatGPT, and Google Bard to ensure the structural integrity of your AI-driven applications.

Scalable Modeling Patterns: Discover a spectrum of techniques—including Diffusion Models, Variational Autoencoders, and LLMs—to maintain the technical agility of your development in a rapidly evolving landscape.

Strategic Security & Industry Integrity: Learn advanced techniques for maintaining information security while exploring real-world applications in healthcare, business analytics, and legal tech—ensuring the technical agility of your evidence-based AI delivery.

Who This Book is For: This professional-grade guide is essential for Students, Working Professionals, and AI Hobbyists. It is an invaluable resource for any technical lead—including those building highly advanced, AI-integrated graduation projects like Smart Guard—aiming to master the structural integrity and technical agility required for modern, evidence-based software and system delivery.

Product Details:

Format: Digital PDF Download

Authors: Deepshikha Bhati; Fnu Neha; Angela Guercio; Amiruzzaman Md; Aloysius Bathi Kasturiarachi

Publisher: Springer Nature (Synthesis Lectures on Computer Science)

Release Date: July 2025 / 2026 Edition

ISBN-13: 9783031847240

ISBN-10: 3031847245