Wydawca: Packt Publishing
AI for Anyone. The Beginner's Guide to AI
S. Huelswitt
Artificial intelligence is no longer limited to specialists. It is a practical tool that anyone can use to improve how they work, create, and solve problems. This book provides a clear path to understanding and applying AI tools without requiring technical expertise.You will start by learning how to access and navigate popular AI platforms, followed by a focused introduction to prompting techniques that turn vague requests into useful outputs. The book introduces structured methods such as goal definition, context setting, and iterative refinement to improve results.You will then explore practical applications, including drafting emails, summarizing content, generating visuals, brainstorming ideas, and organizing information. Each use case focuses on execution so you can apply AI immediately in real scenarios.The book also addresses responsible AI use. You will learn how to identify unreliable outputs, avoid common prompting mistakes, protect sensitive data, and apply ethical considerations.By the end, you will be able to use AI tools confidently, improve output quality through better prompts, and make informed decisions about when and how to use AI effectively.
Iain Anderson, Jeff Greenberg
AI for Creative Production is a practical, non-technical guide that helps digital creators, filmmakers, musicians, and writers embrace AI as a tool or collaborator—not a replacement.Beginning with a clear foundation in how modern AI works and its ethical implications, the book offers a hype-free perspective, showing where AI is genuinely useful and where it’s not. It breaks AI into three accessible categories. Starting with Utility AI, tools that help organize and enhance your work, identify the best shots, select image elements, transcribe and search videos, clean audio, and summarize text.You’ll then explore Generative AI, learning to create new text, images, video, and audio with creative control. GenAI doesn’t have to replace your work; you’ll discover tips for better prompting, tools for retouching, and fresh methods for brainstorming and ideation.Finally, you’ll uncover the potential of Automation AI to help edit videos, process photos, and build scripts that streamline your creative workflows.Packed with hands-on examples using accessible tools like Firefly, Runway, Sora, Photoshop, DaVinci Resolve, and ElevenLabs, this book equips you to integrate AI into your practice with clarity and confidence.By the end, you’ll know how to get the best from AI while preserving the unique value of human creativity in an AI-driven world.
AI for Everyday Automation. 7 AI workflows to save hours at work every week
Dipankar Sarkar
Most professionals spend their days juggling a constant flow of information, communication, and coordination. Individually, these tasks seem small. Together, they consume hours every week. AI for Everyday Automation shows you how to use AI to turn these recurring responsibilities into practical, repeatable workflows.Using tools like ChatGPT, Claude, and Perplexity, this book walks you through seven practical workflows for automating emails, meetings, research, reports, task tracking, spreadsheets, content creation, and professional communication. Each workflow includes prompts, templates, and step-by-step guidance that you can immediately apply to your own work.By the end of the book, you’ll have a set of repeatable AI-assisted systems that help you save time, reduce repetitive work, and get through your workday with far less friction.
Hemang Doshi
Turn AI governance principles, standards, and regulatory requirements into a practical program that operates across the AI lifecycle.This book shows you how to build responsible AI governance around ISO/IEC 42001, the NIST AI RMF, OECD AI Principles, the EU AI Act, and other frameworks. You’ll conduct AI risk and impact assessments, define governance roles and decision rights, establish policies and lifecycle controls, and create documentation for transparency, accountability, and AI compliance.You’ll apply governance through development, deployment, monitoring, and retirement; address AI security and safety; prepare for AI incidents; and use AI audits and monitoring findings to strengthen controls. Practical scenarios, templates, checklists, and step-by-step guidance turn frameworks into repeatable organizational practices.Written by Hemang Doshi, who has more than 20 years of experience in system audit, IT risk and compliance, internal audit, risk management, information security audit, third-party risk management, and operational risk management, this book connects governance frameworks with practical implementation. By the end, you’ll be able to build an accountable, audit-ready AI governance program and integrate AI risk management with existing compliance, security, privacy, and risk processes.
AI in UX Design. How UX Designers are Using AI in the Age of Artificial Intelligence
Lise Pilot
AI in UX Design helps practicing designers understand what changes when generative AI becomes part of everyday product work. Rather than treating AI as a shortcut or a threat, this updated and expanded edition shows how to use it as a teammate for framing problems, synthesizing research, drafting artifacts, and learning from users sooner.Explore how ChatGPT, Claude, Gemini, Figma, Lovable, Replit, v0.dev, Bolt.new, and Base44 fit into modern UX workflows. The book shows how AI can support discovery, personas, JTBD, user flows, requirements, accessibility checks, localization tests, and no-code prototyping.A real case study follows a marketplace idea from opportunity framing to personas, storyboards, UI flows, a functional prototype, and user validation, showing how designers can move from concept to evidence in hours or days rather than weeks.The book also addresses the expanding role of UX designers as orchestrators who guide intelligent systems, shape product direction, and collaborate closer to build. With guidance on responsible AI design, transparency, human control, fairness, safety, and accountability, it keeps human-centered design at the core of faster workflows.Designed for professionals who know UX fundamentals, this book offers a grounded path to working with AI confidently, critically, and creatively.
AI Networking Cookbook. Practical recipes for AI-assisted network automation and development
Eric Chou, John Capobianco
Transform your approach to network automation with the power of AI LLM assistants guided by hands-on recipes for building custom automation solutions quickly using artificial intelligence.You’ll learn tools and techniques such as Vibe coding for conversational development, OpenAI API scripts, prompt engineering for better outputs, local LLM fine-tuning, combining models with LangChain, and Streamlit-based frontends development. The book progresses from simple Python scripts to advanced AI-assisted automation techniques, including multi-vendor API integration, showing you how AI can enhance network configuration, monitoring, security, and troubleshooting.Each recipe presents realistic mock data, complete code examples, and step-by-step guidance, creating a safe environment for experimentation while building a solid foundation for future production use. Whether you want to automate routine configuration, implement AI-driven troubleshooting, or build compliance monitoring systems, this cookbook helps you connect your networking expertise with the capabilities of modern AI.
Nilesh Dhage
Most product frameworks were built for deterministic software, where the same input reliably produces the same output. AI products break that assumption. Outputs vary, models drift, data quality determines what's possible, and user trust decides whether people return. Conventional playbooks hit the same wall every time: they weren't built for probabilistic systems.This book closes that gap with 42 original frameworks spanning the product lifecycle. Learn to validate whether AI is the right solution, weigh value against cost, design feedback loops and metrics for probabilistic behavior, build trust and recovery paths, plan go-to-market strategy that earns confidence, and scale production without losing control of quality, cost, or drift. Frameworks including Pain-First AI-Second Discovery, the AI North Star Canvas, and the Trust-First GTM Framework turn abstract decisions into structured, repeatable actions. Case studies from Spotify, Netflix, Google NotebookLM, Notion AI, Microsoft, Duolingo, and OpenAI ChatGPT ground every framework in how leading products work. Written by Nilesh Dhage, a Fortune 500 firm's Director of Product Management with 23 years across engineering, product, and AI product management, this book connects strategy to execution and leaves you with a reusable toolkit for sharper AI decisions.
Irene Bratsis
AI is rapidly transforming product management, presenting new challenges and business opportunities. As AI-driven solutions become more complex, product managers must bridge the gap between technological capabilities and business needs. This audiobook provides a detailed roadmap for successfully building and maintaining AI-driven products, serving as an indispensable companion on your journey to becoming an effective AI product manager. In this second edition, you'll find fresh insights into generative AI, and responsible AI practices with the most relevant tools for building AI-powered products.Authored by a leading AI product expert with years of hands-on experience in developing and managing AI solutions, this guide translates complex AI concepts into actionable strategies. Whether you're an aspiring AI PM or an experienced professional, this audiobook offers a structured approach to defining AI product vision, leveraging data effectively, and aligning AI with business objectives. With new case studies and refined frameworks, this edition provides deeper insights into ethical AI, cross-functional collaboration, and deployment challenges.By the end of this audiobook, you’ll be equipped with the knowledge to drive AI product success with key techniques for identifying AI opportunities and managing risks in a rapidly evolving landscape.
Irene Bratsis
AI is rapidly transforming product management, presenting new challenges and business opportunities. As AI-driven solutions become more complex, product managers must bridge the gap between technological capabilities and business needs. This book provides a detailed roadmap for successfully building and maintaining AI-driven products, serving as an indispensable companion on your journey to becoming an effective AI product manager. In this second edition, you'll find fresh insights into generative AI, and responsible AI practices with the most relevant tools for building AI-powered products.Authored by a leading AI product expert with years of hands-on experience in developing and managing AI solutions, this guide translates complex AI concepts into actionable strategies. Whether you're an aspiring AI PM or an experienced professional, this book offers a structured approach to defining AI product vision, leveraging data effectively, and aligning AI with business objectives. With new case studies and refined frameworks, this edition provides deeper insights into ethical AI, cross-functional collaboration, and deployment challenges.By the end of this book, you’ll be equipped with the knowledge to drive AI product success with key techniques for identifying AI opportunities and managing risks in a rapidly evolving landscape.*Email sign-up and proof of purchase required
AI Side Hustle Playbook. Make real money with AI in 2026
Caio Incau
AI has opened up new ways to earn, but separating realistic opportunities from get-rich-quick promises isn't easy. The AI Side Hustle Playbook gives you an honest roadmap for turning AI into additional income, with realistic earning ranges, startup costs, and time commitments instead of overnight-success claims.You'll explore five AI-powered side hustles: freelancing, automation services for small businesses, building SaaS apps with vibe coding, content creation, and prompt engineering services. You'll learn how to assess your existing skills, choose the right opportunity, find a profitable niche, attract clients, price your services, and build toward recurring revenue. Most paths require no traditional coding experience.The book also covers the business fundamentals that turn a skill into a sustainable side hustle, including LinkedIn and cold outreach, case studies, referrals, income tracking, taxes, and business setup. Finally, a week-by-week 90-day launch plan takes you from choosing your path to finding customers and building repeatable revenue.
Anderson Soares Furtado Oliveira, Elijah Low, Marcelo...
If you’re a web developer looking to leverage the power of AI in your projects, then this book is for you. Written by an AI and ML expert with more than 15 years of experience, AI Strategies for Web Development takes you on a transformative journey through the dynamic intersection of AI and web development, offering a hands-on learning experience.The first part of the book focuses on uncovering the profound impact of AI on web projects, exploring fundamental concepts, and navigating popular frameworks and tools. As you progress, you’ll learn how to build smart AI applications with design intelligence, personalized user journeys, and coding assistants. Later, you’ll explore how to future-proof your web development projects using advanced AI strategies and understand AI’s impact on jobs. Toward the end, you’ll immerse yourself in AI-augmented development, crafting intelligent web applications and navigating the ethical landscape.Packed with insights into next-gen development environments, AI-augmented practices, emerging realities, interfaces, and security governance, this web development book acts as your roadmap to staying ahead in the AI and web development domain.
AI Under Attack. A Practical Guide to Threats, Defenses, and Governance for AI Systems
Kris Kimmerle, David Okeyode
Contrary to general AI texts or cybersecurity books with limited AI coverage, this guide offers a comprehensive dive into securing the generative AI ecosystem.It moves through four parts: Foundations establishes why AI security is fundamentally different, covering threat modeling, attack surfaces, and core defense principles. Attacks provides deep technical examination of prompt injection, memory and context abuse, RAG system vulnerabilities, agent exploitation techniques, training data poisoning, and AI red teaming methodology. Building Secure AI Systems covers infrastructure and MLOps hardening, secure application and API design, defensive prompt engineering, guardrails with human oversight, supply chain integrity, and Zero Trust architecture for agents. Running AI Security Programs addresses governance, risk and compliance frameworks, security engineering practices, security operations, and building sustainable organizational capabilities. Throughout, you will gain access to practical insights and structured approaches applicable to real-world scenarios.By the end, you will be able to design, implement, and maintain security programs for generative AI, defend against advanced threats, communicate risks to stakeholders, and establish governance ensuring secure, compliant operations across the lifecycle.
Christoffer Noring, Anjali Jain, Marina Fernandez, Ayşe...
AI-Assisted Programming for Web and Machine Learning shows you how to build applications and machine learning models and automate repetitive tasks.Part 1 focuses on coding, from building a user interface to the backend. You’ll use prompts to create the appearance of an app using HTML, styling with CSS, adding behavior with JavaScript, and working with multiple viewports. Next, you’ll build a web API with Python and Flask and refactor the code to improve code readability. Part 1 ends with using GitHub Copilot to improve the maintainability and performance of existing code. Part 2 provides a prompting toolkit for data science from data checking (inspecting data and creating distribution graphs and correlation matrices) to building and optimizing a neural network. You’ll use different prompt strategies for data preprocessing, feature engineering, model selection, training, hyperparameter optimization, and model evaluation for various machine learning models and use cases. The book closes with chapters on advanced techniques on GitHub Copilot and software agents. There are tips on code generation, debugging, and troubleshooting code. You’ll see how simpler and AI-powered agents work and discover tool calling.
Alberto Acerbis, Alessandro Colla, Tobias Goeschel
Domain-Driven Design helps software architects and developers manage complexity by creating a shared understanding of business domains and translating that understanding into coherent software architecture. AI-Augmented Domain-Driven Design shows you how to extend that practice with generative AI and LLMs without handing architectural decisions over to AI.You’ll learn to use LLMs as structured reasoning partners for domain modeling, applying prompt engineering techniques, rulebooks, EventStorming patterns, and iterative refinement. Through practical case studies, you’ll use AI-assisted reasoning to identify and refine domain events, commands, aggregates, and bounded contexts while preserving human judgment and domain clarity.You’ll then advance from structured prompting to AI agents for domain discovery, storytelling, and context mapping. By orchestrating these agents into multi-agent systems, you’ll build repeatable Domain-Driven Design workflows that support complex software architecture work while reducing cognitive overload.By the end of the book, you’ll have a disciplined approach to integrating LLMs and AI agents into your DDD practice, helping you reason about complex domains, strengthen architecture decisions, and maintain conceptual consistency as software systems evolve.
AI-Native LLM Security. Threats, defenses, and best practices for building safe and trustworthy AI
Vaibhav Malik, Ken Huang, Ads Dawson
Adversarial AI attacks present a unique set of security challenges, exploiting the very foundation of how AI learns. This book explores these threats in depth, equipping cybersecurity professionals with the tools needed to secure generative AI and LLM applications. Rather than skimming the surface of emerging risks, it focuses on practical strategies, industry standards, and recent research to build a robust defense framework.Structured around actionable insights, the chapters introduce a secure-by-design methodology, integrating threat modeling and MLSecOps practices to fortify AI systems. You’ll discover how to leverage established taxonomies from OWASP, NIST, and MITRE to identify and mitigate vulnerabilities. Through real-world examples, the book highlights best practices for incorporating security controls into AI development life cycles, covering key areas such as CI/CD, MLOps, and open-access LLMs.Built on the expertise of its co-authors—pioneers in the OWASP Top 10 for LLM applications—this guide also addresses the ethical implications of AI security, contributing to the broader conversation on trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI technologies with confidence and clarity.*Email sign-up and proof of purchase required
Lance Rubin
Finance teams need faster reporting and sharper insight without compromising accuracy, control, or trust. AI-Powered Accounting with Excel and Power BI shows accountants and finance professionals how to apply generative AI to real-world accounting workflows while keeping human judgment at the center. Drawing on Lance Rubin’s experience as a CFO, financial modeling specialist, and founder of Model Citizn, this book uses tools such as the HACK Framework and Six Pillars to help you structure data, evaluate AI tools, write reliable prompts, and verify outputs. Ten practical modules cover Excel formulas, PDF extraction, reconciliation, financial controls, management accounting, account mapping, workbook restructuring, audit-ready validation, and dashboards in Excel and Power BI.This book will help you build AI-assisted accounting and financial reporting workflows, turn recurring tasks into reusable Skills, and identify hallucinations before they affect decisions. By the end, you’ll have a practical roadmap for safer finance automation and the confidence to know when to trust AI and when to step in.*Email sign-up and proof of purchase required