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Lubanovic B: Introducing Python

Introducing Python

Modern Computing in Simple Packages

Build robust LLM-powered apps, chatbots, and agents while mastering AI engineering principles that will help you outlast the tools and the hype. Want to build an LLM-powered app but don't know where to begin?&nbsp;&nbsp;With this step-by-step guide, you can master the underlying principles of AI engineering by building an LLM-powered app from the ground up. Tame unpredictable models with prompt and context engineering. Use evals to keep them on track. Give chatbots the knowledge to answer anything a user wants to know. Equip agents with the tools and smarts to actually get the job done. By the end, you'll have the intuition and the confidence to build on top of LLMs in the real world. Fragmented documentation, obsolete tutorials, and frameworks that deliver a prototype but flop in production can make AI engineering feel overwhelming. But it doesn't have to be that way. With real-world code and step-by-step instructions as your guide, you can learn to build robust LLM-powered apps from the ground up while mastering both the how&nbsp;and why of the most crucial underlying concepts. Harness context engineering and retrieval systems to create AI assistants that understand your proprietary data. Create chatbots that answer organization-specific questions and help solve users' issues. Design agents that conduct research, make decisions, and take action in the real world. Level up your prompt engineering and get an LLM to do your bidding---not its own. Use automated evals to keep constant tabs on your app's quality while setting up guardrails to protect your users and organization. And implement observability systems that make it easy to debug your app when things do go wrong. With a systematic approach grounded in the core principles of building AI apps for real users, you'll easily evolve and adapt even as the hype and tools come and go.

Build Production-Ready LLM Applications

A Common-Sense Guide to AI Engineering

Dance with the Dragon “A must-read for any reverse engineer.” ­—Max “Libra” Kersten Developed through more than a decade of research within the NSA, Ghidra was created to address some of the most challenging reverse engineering problems faced by the US government. With its open source release, this formerly restricted tool suite is now freely available to cybersecurity practitioners, researchers, and students worldwide. The Ghidra Book provides a clear, practical guide to understanding and using this powerful platform. In addition to introducing core reverse engineering techniques for software and malware analysis, the book explains Ghidra’s key components, features, and support for extensibility and collaborative analysis. Beginning with the fundamentals and progressing to more advanced workflows, you’ll learn how to use Ghidra effectively and adapt it to new challenges. You’ll learn how to: <ul><li>Navigate and interpret a disassembly</li><li>Use Ghidra’s built-in decompiler to expedite analysis</li><li>Analyze unfamiliar and obfuscated binaries</li><li>Extend Ghidra to recognize new data types</li><li>Build custom analyzers, loaders, and processor support modules</li><li>Script Ghidra tasks to automate analysis tasks</li><li>Set up a collaborative reverse engineering environment</li></ul> This fully revised second edition reflects the modern Ghidra platform as it is used in practice, with updated tooling, improved workflows, and hands-on real-world examples. Designed for beginners and experienced users alike, The Ghidra Book prepares you to tackle real reverse engineering problems with confidence. New to this edition: <ul><li>Behavioral analysis with BSim</li><li>Full Python 3 support via PyGhidra</li><li>Enhanced debugging and graphing tools</li><li>Modern container-based deployment</li></ul>

The Definitive Guide

The Ghidra Book, 2nd Edition

Le guide complet du débutant Smartsheet Guide étape par étape pour la gestion de projet, l'automatisation des flux de travail, les tableaux de bord, les rapports, la collaboration en équipe et la productivité de l'entreprise Maîtrisez Smartsheet avec confiance, une étape à la fois Êtes-vous prêt à simplifier la gestion de projet, automatiser les tâches répétitives et collaborer plus efficacement avec Smartsheet ? Cette publication n'est pas affiliée, approuvée par, sponsorisée ou autorisée par Smartsheet Inc. Smartsheet est une marque déposée de Smartsheet Inc., et toutes les marques mentionnées appartiennent à leurs propriétaires respectifs. Bien que tous les efforts aient été faits pour garantir l'exactitude des informations présentées au moment de la publication, les fonctionnalités logicielles, interfaces et fonctionnalités peuvent évoluer au fur et à mesure de la publication des mises à jour. Les lecteurs sont invités à consulter la documentation officielle de Smartsheet pour obtenir les dernières informations sur les produits. L'auteur et l'éditeur n'assument aucune responsabilité pour toute perte ou dommage résultant de l'utilisation des informations contenues dans ce livre. Que vous soyez un débutant complet, un professionnel des affaires, un chef de projet, un freelance ou un chef d'équipe, The Complete Smartsheet Beginner's Guide est votre guide utilisateur pratique pour apprendre Smartsheet de zéro. Conçu pour les débutants, ce guide complet vous guide étape par étape à travers chaque fonctionnalité essentielle, vous aidant à développer des compétences concrètes qui améliorent la productivité et rationalisent votre flux de travail. Implémentez Smartsheet dans le marketing, les RH, la vente, la construction, la planification d'événements et d'autres environnements professionnels réels Évitez les erreurs courantes des débutants tout en développant les meilleures pratiques utilisées par des professionnels expérimentés de Smartsheet Que vous gériez des projets personnels, coordonniez les opérations commerciales, dirigiez une équipe en croissance ou amélioriez la productivité organisationnelle, ce livre vous apporte les connaissances pratiques et la confiance nécessaires pour que Smartsheet fonctionne à votre avantage. Si vous cherchez un guide utilisateur complet et adapté aux débutants qui explique tout dans un format logique et facile à suivre, c'est la ressource que vous cherchiez. Commencez dès aujourd'hui votre parcours Smartsheet et transformez votre façon de planifier, organiser, collaborer et gérer votre travail.

Guide étape par étape pour la gestion de projet, l'automatisation des flux de travail, les tableaux de bord, les rapports, la collaboration en équipe et la productivité de l'entreprise

LE GUIDE COMPLET DU DÉBUTANT SMARTSHEET

Independently published

Automation sounds powerful-until you run into APIs, webhooks, JSON, credentials, expressions, AI agents, and dozens of unfamiliar technical terms.Automating Smarter with n8n was written to make that learning curve manageable.You do not need a programming background or previous experience with workflow automation. This practical, beginner-friendly guide takes you from your very first n8n workflow to reliable business automations that connect applications, process data, call APIs, handle failures, and even use AI where it genuinely adds value.Instead of overwhelming you with theory, the book teaches one concept at a time through clear explanations, practical exercises, and an evolving real-world Smart Lead-to-Client Automation System.Mistakes are part of the process. A webhook may fail. An expression may reference the wrong field. An API may reject a request. Rather than treating these moments as setbacks, this book shows you how to inspect what happened, fix the problem, and build confidence one successful workflow at a time.Key Features- Beginner-friendly explanations with no prior coding experience required - Hands-on n8n workflows that build progressively - Practical business process automation examples - Real-world API, webhook, JSON, and data-mapping skills - AI-powered workflows, AI agents, tools, memory, MCP, and human approval - Testing, debugging, security, monitoring, and error recovery - Docker self-hosting, PostgreSQL, backups, scaling, and production guidance - A complete lead-to-client automation project that brings everything togetherWhat You Will Learn- Build and test n8n workflows from scratch - Understand nodes, triggers, executions, JSON, expressions, and data mapping - Connect external services with REST APIs and webhooks - Create branching logic, loops, reusable sub-workflows, and scheduled automations - Automate leads, customer follow-ups, tasks, reports, forms, and business data - Protect credentials and design safer production workflows - Debug failed executions and recover from partial failures - Build practical AI-powered automations and controlled AI agents - Deploy and maintain a self-hosted n8n environment with Docker - Design automations that remain understandable, reliable, and maintainableWho This Book Is ForThis book is ideal for complete beginners, self-learners, entrepreneurs, freelancers, operations professionals, aspiring automation builders, and anyone who wants to reduce repetitive work using practical workflow automation.If you can use a computer and are willing to learn step by step, you can follow this book.Table of ContentsChapter 1: Getting Started with n8n and Thinking in Workflows Chapter 2: Working with Data, JSON, Mapping, and Expressions Chapter 3: Triggers, Webhooks, APIs, and External Services Chapter 4: Building Logic, Control Flow, and Reusable Workflows Chapter 5: Automating Everyday Business Processes Chapter 6: Testing, Debugging, Security, and Workflow Reliability Chapter 7: Building AI-Powered Workflows and Practical AI Agents Chapter 8: Building the Smart Lead-to-Client Automation System Chapter 9: Deployment, Self-Hosting, Scaling, and MaintenanceYou do not have to master everything at once. Start with one workflow, understand why it works, celebrate each small win, and build from there.Start your n8n automation journey today and turn repetitive work into clear, practical, reliable systems you can confidently build and improve.

A Beginner-Friendly Roadmap to Reliable Workflows, AI Agents, and Everyday Business Automation

Automating Smarter with n8n

What if you didn't need a huge startup, a large development team, or millions in funding to build a software business?The next generation of software entrepreneurs is being built around something much smaller: focused products that solve expensive, recurring problems for specific customers.The Micro-SaaS Goldmine shows you how to find those opportunities and turn the right one into a real business.Inside, you'll discover 50 AI-powered Micro-SaaS business concepts spanning different industries and business problems, along with a practical system for deciding which ideas deserve your time and which should be rejected before you waste months building them.But this isn't simply a list of startup ideas.You'll learn how to: - Identify painful problems people may actually pay to solve - Evaluate opportunities with a practical Opportunity Scorecard - Use the TRIGGER → DATA → AI/LOGIC → VALIDATION → ACTION → OUTCOME workflow to design useful AI-powered products - Test an idea before investing heavily in development - Run a 14-Day Validation Sprint - Use Concierge and Wizard-of-Oz MVPs to prove demand before building sophisticated software - Conduct a $100 Proof Test to distinguish curiosity from genuine buying intent - Choose pricing based on value, usage, costs, and customer economics - Find your first customers without relying on a massive audience - Build repeatable distribution instead of hoping people discover your product - Decide what to automate and what should remain human - Create defensibility through workflows, integrations, data, and customer dependence - Track the metrics that actually matter - Recognize when to kill, pivot, investigate, or double down - Navigate AI-related risks involving accuracy, privacy, confidential information, and high-stakes use cases - Move from your first customer toward your first $1,000 and beyondThe central idea is simple: AI isn't the business. The problem you solve is the business.AI can make a small software company dramatically more capable-but only when it is attached to a valuable workflow and a customer who cares about the outcome.Whether you're a developer, no-code builder, freelancer, consultant, professional, small-business owner, or aspiring entrepreneur, this book gives you a structured way to move from "I want to build something" to "I know what to test, who to sell to, and what to do next."You don't need to build everything.You need to find one problem worth solving, one customer worth serving, and one small product worth proving.The Micro-SaaS Goldmine gives you the ideas, frameworks, validation methods, and execution playbook to start.

50 AI-Powered Software Businesses You Can Build, Validate, Launch & Grow Without a Big Team

The Micro-SaaS Goldmine

Build Your Digital Empire Without Writing Code

Vibe Coding Mastery

Tcl/Tk: A Developer's Guide, Fourth Edition is an essential resource for computer professionals, from systems administrators to programmers. It covers new Tcl features, expanded Tcl-OO coverage, web technology using Rivet and SQLite, and AI integration with AWS. The book also delves into Tcl's standard tools, multi-faceted nature, and extensibility, making it ideal for developing GUIs, client/server middleware, and web applications. Readers will quickly learn to code in Tcl and extend its capabilities with the inclusion of numerous code examples and case studies. The updated edition includes over 150 pages on the latest Tcl extensions, proven techniques, and tools for effective programming. Extensive code snippets and online tutorials enhance understanding, while case studies provide practical insights. The book also discusses Tcl's role as the hidden "secret sauce" in commercial applications, highlighting its graphics and control infrastructure. With a vibrant user community and evolving API, Tcl/Tk remains a powerful and versatile programming platform for both beginners and experienced programmers.

A Developer's Guide

Tcl/Tk

AI is only as capable as the context it's given, and context is a data engineering problem before it's a model problem. As multimodal AI systems and applications become increasingly sophisticated and data-hungry, the infrastructure that produces and governs that context has to evolve to keep pace. Data Engineering for Multimodal AI is one of the first practical guides for data engineers, machine learning engineers, and MLOps specialists looking to rapidly master the skills needed to build robust, scalable data infrastructures that multimodal AI systems and applications depend on for effective context engineering. You'll follow the entire lifecycle of AI-driven data engineering, from conceptualizing data architectures to implementing data pipelines optimized for multimodal learning in both cloud-native and on-premises environments. And each chapter includes step-by-step guides and best practices for implementing key concepts. <ul><li>Design and implement cloud-native data architectures optimized for multimodal AI workloads</li> <li>Build efficient and scalable ETL processes for preparing diverse AI training data</li> <li>Implement real-time data processing pipelines for multimodal AI inference</li> <li>Develop and manage feature stores that support multiple data modalities</li> <li>Apply data governance and security practices specific to multimodal AI projects</li> <li>Optimize data storage and retrieval for various types of multimodal ML models</li> <li>Integrate data versioning and lineage tracking in multimodal AI workflows</li> <li>Implement data-quality frameworks to ensure reliable outcomes across data types</li> <li>Design data pipelines that support responsible AI practices in a multimodal context</li></ul>

Architecting Scalable Systems for Next-Generation AI Applications

Data Engineering for Multimodal AI

Build intelligent applications—no data science degree required. Your boss is pitching new AI features. Your team is buzzing about MCP servers. Job postings are asking for AI experience with RAG, vector databases, fine-tuning, and agents. You can feel the excitement. You see the potential. You may be wondering how to get started in AI without a data science degree. You’re in the right place. The Developer’s Guide to AI gives working developers a practical path through the terminology, tools, and implementation patterns that matter. It shows you how to build with AI using the tools you already know: JavaScript, Python, APIs, SDKs, and databases. By the end of this book, you’ll know how to: <ul><li>Call LLM APIs and stream intelligent responses directly to your UI.</li><li>Engineer prompts that produce reliable, production-ready results.</li><li>Build RAG pipelines using vector databases to give AI access to your private data.</li><li>Fine-tune models with LoRA for specialized tasks like classification.</li><li>Deploy AI agents using tool-calling and the Model Context Protocol (MCP) to reason and act inside real workflows.</li></ul> LLMs, RAG, LoRA, MCP, embeddings, and agents are not just intimidating buzzwords. They are the building blocks for the next generation of software. Grab your code editor, bring your engineering instincts, and let’s build what’s next!

The Developer's Guide to AI

An accessible walkthrough of one of the world's most popular programming languages: C++ C++ For Dummies is your from-scratch guide that explains the essentials of what you need to know to understand the language and build your very first program in C++. Bradley Jones, experienced programmer and coding educator, packs this edition with examples and clear demonstrations that explain the "why" and the "how" of programming in C++, as well as the programming concepts that will form the foundation of your code, including classes, loops, classes, objects, inheritance, and more. C++ For Dummies provides easy-to-understand tutorials for the use of C++26 and explains the modern approach to printing and displaying information with the std::print method. It also discusses: <ul> <li>Explanations of features that make C++26 better including modules, smart pointers, concepts, and ranges</li> <li>Walkthroughs of updated libraries for the filesystem, ranges, formatting, time, printing, and more</li> <li>Testing and debugging techniques</li> </ul> Great for programmers, developers, students, or anyone interested in learning to code in C++ who are looking for a straightforward, hands-on approach to the language, C++ For Dummies is an accessible introduction to C++26 that offers readers a reliable head-start to a fun and rewarding skillset.

C++ For Dummies

A forward-looking primer on how AI models and systems work, the attacks that can disrupt them, and what security measures the industry uses to keep them safe. Artificial intelligence now underpins everything from chatbots to national infrastructure, but with new capability comes new risk. Attacks like prompt injection, data poisoning, and model theft are already targeting the systems we rely on. Practical AI Security is a comprehensive foundation to the field—a 0-to-60 guide to everything you need to know at the intersection of AI and cybersecurity. Drawing real-world experience securing deployed systems, Harriet Farlow demystifies how modern AI works, why it’s vulnerable, and how to protect it. You’ll learn how AI systems differ from machine learning models, why that matters for security, and how to defend both. Through clear explanations, real-world examples, and over 30 hands-on Python demos, you will: <ul><li>Understand how different kinds of machine learning models—from computer vision and language models to signal models—are built and how their architectures create unique vulnerabilities</li><li>Explore how these models are integrated into more autonomous, agentic AI systems, and why deployment introduces new weaknesses and risks</li><li>Identify, exploit, and defend against dozens of weaknesses and attacks across the AI lifecycle, including data poisoning, model theft, and prompt injection</li><li>Use industry frameworks such as OWASP and MITRE ATLAS to threat model different types of AI systems</li><li>Design and execute AI-specific red teaming campaigns, and understand what makes them distinct from traditional security tests</li><li>Examine how AI itself can be weaponized in cybersecurity, including cases where AI attacks other AI</li><li>Build robust frameworks for AI risk management, assurance, and testing</li><li>Bridge technical and policy perspectives to strengthen AI security culture across organizations</li></ul> Covering fundamentals through to advanced topics—from adversarial machine learning and red teaming to risk management, governance, and AI safety—this book turns theory into skill. Even if you don’t think you’re technical now, you’ll finish with practical confidence and a security mindset. Whether you use, build, deploy, or oversee AI, this isn’t niche knowledge—it’s the foundation for defending the technologies that will define the next era of human progress.

A Hands-on Guide to Attacking, Defending, and Securing Modern AI Systems

Practical AI Security

Whether they're building a startup or scaling an established org, engineering leaders know the real job is keeping chaos under control. In a world of shifting priorities, scarce resources, and rapid change, leadership means embracing the unknown, managing moving targets, and creating clarity where there's none. Sometimes, you're building the plane as you're flying it--writing the roadmap as you go, designing processes in real time. Engineering Leadership: The Hard Parts cuts through the noise, offering a guide for tackling these gritty, real-world challenges. Current and future leaders, this is your toolkit. It's packed with principles, techniques, and mental models for thriving in uncertainty. <ul><li>Navigate the full scope: Step into engineering leadership's complex, multifaceted role</li> <li>Build high-impact teams: Master advanced techniques to grow and lead your technical talent</li> <li>Align and execute: Connect strategy to business outcomes, scale effectively, and balance innovation with precision</li> <li>Lead with resilience: Adapt quickly and drive continuous improvement</li> <li>Accelerate your career: Develop your leadership edge and unlock new growth</li> </ul> Stay ahead. Lead with purpose.

Navigating Chaos to Build Teams That Deliver

Engineering Leadership: The Hard Parts

Introducing Python

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