Description
Automated code generation is rising, but the need for skilled software engineers is more critical than ever. Engineers must still understand, design, debug, and guide the systems they build. Modern Java continues to be one of the most reliable and widely used languages, capable of powering everything from small applications to large-scale enterprise systems.

This book follows a structured, step-by-step path and uses real-world scenarios to explain concepts beyond syntax. It begins with Java fundamentals, including IDE setup, versions, debugging, and object-oriented programming. It also explores building blocks such as exception handling, collections, and file management before moving to practical development. The book guides you through building CRUD applications from CLIs to GUIs. It also covers database operations using JDBC and ORM tools, automation tasks such as scheduling email processing, web scraping, API integration, and AI/ML services. It further introduces multithreading and building scalable applications using Spring Boot and Quarkus, followed by deployment.

By the end of this book, you will gain the skills and confidence to design and build real-world Java applications. You will also develop practical experience in automation, secure coding, API integration, deployment strategies, and modern DevOps practices.

Trust is the invisible force that determines whether a Service Integration and Management (SIAM) ecosystem thrives or fails. SIAM and Trust, part of the SIAM Body of Knowledge Compendium series, provides focused, practical guidance on how to build, sustain, and restore trust across complex, multi-provider environments.

Compendiums are designed to bridge the gap between theory and real-world application. This volume draws on the lived experience of global SIAM practitioners to explore how trust operates across cultural, procedural, contractual, and technological dimensions.

In modern SIAM environments, trust is constantly tested—whether onboarding new providers, managing shifting expectations, navigating contractual misalignment, or responding to changes in key personnel. When trust breaks down, collaboration becomes transactional, performance suffers, and integration challenges intensify. SIAM and Trust tackles these realities head-on, offering actionable insights to help organisations move beyond friction and towards alignment, transparency, and shared accountability.

You will learn how to:

• Establish trust during SIAM design and onboarding
• Strengthen relationships between customers, integrators, and providers
• Identify and address common trust breakdowns
• Embed trust into governance, performance management, and ways of working
• Create resilient ecosystems that deliver consistent, high-quality outcomes

Ideal for SIAM practitioners, service integrators, provider teams, and organisational leaders, this Compendium supports both those new to SIAM and those looking to mature their existing ecosystems. It equips readers with the tools and perspectives needed to turn trust into a measurable, manageable capability—driving better collaboration, improved performance, and long-term success.

Description
Data privacy has become a critical business and technology discipline in today’s digital economy. As organisations increasingly rely on cloud services, e-commerce platforms, social media, artificial intelligence, and data-driven decision-making, they must protect personal information while complying with evolving privacy regulations. Effective privacy governance is now essential for managing risk, maintaining customer trust, and enabling sustainable business growth.

This guidebook provides comprehensive coverage of the Certified Data Privacy Solutions Engineer (CDPSE) certification domains. Readers will learn how to integrate privacy requirements into business processes, systems, applications, and technologies. The book explains privacy governance, privacy architecture, data lifecycle management, privacy controls, risk assessment, and compliance requirements through a structured and practical approach. Drawing upon the CDPSE framework and real-world implementation practices, it bridges the gap between privacy concepts and operational execution.

By the end of this book, readers will have a strong understanding of how to design, implement, and manage privacy solutions within an organisation. They will be prepared for the CDPSE examination and equipped with practical skills to address privacy risks, support regulatory compliance, and contribute effectively to privacy and governance initiatives in diverse organisational environments.

Description
JavaScript nowadays is far beyond clicks. It is what drives big telemetry dashboards and the most innovative AI apps. If you want to be among those who know JavaScript by heart, get ready for an ultimate challenge. Building highly efficient web environments or dealing with system design on another level, whatever task you have, you can solve it using this technology.

In this book, you will be moving rapidly from syntax to actual engineering tasks in the field of professional programming in JavaScript. After ES6+ and the event loop, we will focus on applying the gained knowledge. We will work on creating real-world code examples, such as e-commerce code snippets, and familiarize ourselves with modern frameworks and libraries such as React and Angular. The journey will take you to the world of visualizations using Three.js. We will also cover A11Y practices and integration of external APIs.

By the end of this book, you will become an engineer prepared to make important technical choices and manage your project. You will leave this program with an industry-grade portfolio, an understanding of high-performance architecture, and the interpersonal skills required to succeed anywhere in the tech world.

AI Can Make You Smarter stands out for its practical focus and lasting value. It explains a wide range of real-world techniques while helping you build enduring skills in clear thinking, effective communication, and productive collaboration. Proficiency in these essential skills is the surest way to stay valuable as AI reshapes the workplace.

Work is changing fast, and efficiency alone is no longer enough. This book goes beyond productivity to show how AI can help you make better decisions, adapt to change, and build stronger professional relationships. You’ll learn to guide ChatGPT—and similar tools such as Gemini, Copilot, and Claude—with precise prompts, evaluate accuracy, and recognize bias and hallucinations, all without jargon or hype.

Through tested examples and easy-to-follow methods, you’ll see how AI can help you brainstorm, analyze, and communicate ideas with clarity. You’ll also learn to use it for serious writing—reports, proposals, and other high-value documents, where quality and credibility matter most.

AI Can Make You Smarter equips you to use AI confidently: to save time, deepen understanding, and grow your professional expertise. It’s a resource you’ll return to again and again.

Get updates, tools, and compatibility guides at agilethinking.com.

Description
Microsoft Excel 365 is a premier tool for managing and visualizing data, trusted globally for both personal and professional tasks. It simplifies complex calculations and organization while integrating modern AI and Python capabilities to accelerate workflows. These advancements empower users to process information faster and make more informed decisions.

This book provides a practical guide to the Excel 365 environment and its high-efficiency features. You will learn to import and transform data using Power Query while maintaining quality in tables. The content covers essential functions including math, statistical, date, and logical lookups. You will master modern tools like dynamic arrays alongside advanced data analysis features. It explains PivotTables, What-If Analysis, conditional formatting, and workbook protection. Practical Excel hacks, SmartArt, and charts are presented through real-world case studies. Finally, the book introduces Python in Excel and AI-powered tools to boost your productivity.

By the end of this book, you will be well-equipped to manage complex datasets and possess a practical understanding of the entire Excel 365 ecosystem. You will confidently apply professional automation and analysis skills to solve real-world challenges with speed and accuracy.

Cybersecurity is no longer an IT issue—it is a fiduciary responsibility.

The SEC’s cybersecurity disclosure rules require public companies to report material cyber incidents within four business days and disclose how boards oversee cyber risk and governance.

Cyberfiduciary is a concise, board-level guide for directors, executives, audit committees, and legal leaders navigating this new accountability. The book translates cyber risk into governance frameworks, disclosure-ready processes, and defensible oversight—helping boards protect enterprise value, investor trust, and regulatory credibility in an increasingly digital economy.

Description
Organizations can no longer depend on static strategies or one-off transformation programs in an era shaped by AI-driven disruption, relentless change, and growing uncertainty. Technology, leadership, culture, and operating models are deeply interconnected, and resilience has become the capability that separates organizations that merely survive from those that sustain advantage.

This book blends practical frameworks with experiential storytelling, following a central character navigating real-world transformation challenges. Readers will step into these scenarios, reflect on parallels within their own organizations, and apply the tools, questions, and approaches introduced throughout the book. It examines how organizations respond to change and how to reveal the true current state, beyond surface-level metrics, and concludes by addressing how to design sustainable operating models guided by an infinite mindset, recognizing that transformation is not a destination, but a continuous journey.

By bringing together less-discussed yet critical perspectives often scattered across disciplines, this book offers an integrated, pragmatic approach to resilience. After reading it, leaders, managers, and change practitioners will be equipped to design organizations that adapt, learn, and thrive, no matter what the future holds.

The future of AI will be shaped less by what machines can do than by what humans choose to become.

In Remaining Human in the Age of AI, Dr. Michael Edmondson examines how individuals and organizations can thrive while intelligent technologies reshape the modern world. Rather than focusing only on the capabilities of machines, the book explores the human qualities required to navigate disruption, uncertainty, and constant change.

Edmondson introduces a practical framework built around eight essential human traits: serendipity, openness, agility, resilience, ambition, self-care, equanimity, and empathy. These traits help individuals interpret complex environments, remain grounded during periods of rapid change, and lead others with clarity and purpose.

After reading this book, you will be able to:

• Understand how artificial intelligence reshapes work, identity, and leadership.
• Apply the eight human traits as a framework for navigating technological change.Improve leadership, decision making, and professional growth in an AI-enabled world.
• Implement strategies that strengthen human judgment alongside intelligent tools.

Description
The Internet of Things (IoT) is transforming our world by connecting everyday objects to the digital world, making mastering this technology essential for modern engineers and innovators. This book bridges the gap between theoretical frameworks and hands-on physical computing to help you build smart, hyperconnected systems.

The book discusses IoT building blocks, architectural layers, and communication protocols like MQTT and CoAP before studying design standards from IETF and ETSI. The journey continues through digital sensors, actuators, and RFID, alongside industrial IoT and vehicle-to-infrastructure technology. You will gain practical experience with Arduino, Raspberry Pi, and BeagleBone while mastering MAC protocols and node discovery. The book transitions into C programming for the Arduino IDE, teaching you to interface with DHT11 sensors and OLED displays while integrating with ThingSpeak cloud, MQTT brokers, and MySQL databases.

This book equips readers with the technical confidence and strategic perspective needed to design, analyze, and deploy intelligent IoT systems in their respective job roles. It inspires readers to think critically, innovate effectively, and contribute meaningfully to the evolving IoT ecosystem.

Description
Synthetic data generation has rapidly become a necessary strategy for modern AI training, and mastering it is essential for anyone looking to build robust machine learning models without compromising data privacy. This book will help you understand the foundational AI data workflows while maintaining strict regulatory compliance.

This book systematically covers everything from foundational probability distributions and rule-based simulations to advanced architectures like GANs, VAEs, diffusion models, and LLMs. It maps out practical production pipelines using Train on Synthetic, Test on Real (TSTR) evaluation workflows alongside industry use cases, differential privacy, and global compliance frameworks. Every topic combines mathematical theory with hands-on Python exercises, enabling readers to confidently generate, evaluate, and deploy high-utility, privacy-safe datasets.

By the end of this book, you will be well-equipped to confidently deploy clean synthetic data workflows and possess a practical understanding of deep generative modeling, ready to apply these high-impact skills in real-world engineering scenarios.

Description
AI That Thinks is a visionary yet technically grounded exploration of how we move from narrow artificial intelligence to truly intelligent systems. AI shapes how intelligent systems are designed and understood. Understanding intelligence has become increasingly important.

This book traces the evolution of AI through symbolic reasoning, neural networks, computer vision, robotics, edge AI, and emerging quantum paradigms. It argues for a mechanism-agnostic definition of intelligence, the one based not on how a system is built, but on what it demonstrably does, which is to perceive, predict, learn, adapt, collaborate, and act under uncertainty. By connecting philosophy with engineering and theory with implementation, the book provides a rigorous yet accessible foundation for understanding what it would take to build machines that genuinely think.

By the end of this book, the readers will gain an understanding of intelligent systems and AI applications. The central thesis is that the future of AI will not belong to single paradigms, but to hybrid, embodied, distributed systems that integrate learning with reasoning, autonomy with accountability, and intelligence with physical reality. More than a reflection on current technology, this book offers a forward-looking blueprint for engineers, researchers, leaders, and innovators who seek to design the next era of intelligent systems.

Description
Hybrid and edge computing have become essential for organizations that need cloud innovation with local control, compliance, resilience, low latency, and data sovereignty. Azure Local, together with Azure Arc, extends the Azure operating model to data centers, remote sites, and edge environments, enabling consistent management, security, and governance wherever workloads run.

This book provides a comprehensive introduction to designing, deploying, and operating Azure Local as part of a modern hybrid strategy. It starts with adaptive cloud foundations, then explores sovereignty and compliance, and the key decisions for installation and configuration. Readers will learn how Azure Local supports virtual machines, Kubernetes, AVD and modern applications, and how Azure Arc simplifies operations through unified management, patching, security, policy, monitoring, and reporting.

By the end of this book, IT leaders, architects, platform engineers, and cloud professionals will be able to evaluate when Azure Local is the right choice, design sustainable hybrid architectures, and operate distributed environments with confidence and control.

Description
GenAI is changing how we build software, and learning to master these models with Python is essential for any modern developer. This book is a comprehensive guide to the intricate world of GenAI.

This book serves as a complete guide to GenAI, covering foundational concepts and advanced system design. It begins with core principles of generative modeling, explaining probabilistic approaches and how they differ from traditional machine learning methods. The journey then moves into GANs, including their architecture, variants, training challenges, and evaluation techniques. Readers are introduced to VAEs, focusing on latent space representation, probabilistic learning, and practical design strategies. It then explores transformer architectures and Vision Transformers, explaining how attention mechanisms enable modern generative and multimodal systems. Hybrid approaches combining VAEs and transformers are also covered to demonstrate real-world model design.

By the end of this book, you will master the math and engineering behind GANs and VAEs to build high-quality visual synthesis networks. You will gain hands-on expertise in Vision Transformers, diffusion models, and scalable MLOps infrastructure using vector and graph databases.

What you will learn
? Acquire practical skills in designing and implementing various generative AI models.
? Gain expertise in vector databases and image embeddings, crucial for image search and data retrieval.
? Generate images and text with VAEs, GANs, LLMs, and vector databases.
? Focus on both traditional and cutting-edge techniques in generative AI.

IN THIS EDITION, YOU WILL LEARN HOW TO:
? Master generative math to stabilize adversarial and stochastic vision networks.
? Build hybrid attention systems using transformers and diffusion architectures.

Who this book is for
This book is designed for current and aspiring AI and deep learning professionals, architects, students, and anyone looking to begin a rewarding career in GenAI. It is ideal for those who want to build a strong foundation and progress from traditional generative models to modern, industry-grade GenAI systems and applications.

Table of Contents
1. Introducing Generative AI
2. Designing Generative Adversarial Networks
3. Training and Developing Generative Adversarial Networks
4. Architecting Autoencoder for Generative Artificial Intelligence
5. Building and Training Generative Autoencoders
6. Designing Generative Variational Autoencoder
7. Building Variational Autoencoders for Generative AI
8. Fundamentals of Designing New Age Generative Vision Transformer
9. Implementing Generative Vision VAE Transformer
10. Architectural Refactoring for Generative Modeling
11. Major Technical Roadblocks in Generative AI and Way Forward
12. Overview and Application of Generative AI Models
13. Generative AI and LLM Extended
14. Generative AI and LLM Advanced
15. Finetuning LLMs
16. Mixture-of-Experts
17. Diffusion Models
18. Practical Finetuning of LLM

Description
Ubuntu Server is one of the most widely used Linux server platforms for system administration, cloud computing, DevOps, virtualization, containers, and enterprise infrastructure. This book is designed to build real-world Ubuntu Server skills, from initial deployment and daily administration to automation, cloud platforms, and security hardening.

This book follows a structured learning path covering Ubuntu Server installation, GRUB configuration, and core Linux administration. It then introduces system management, storage, package administration, troubleshooting, and log analysis. Readers will explore networking services, remote access, file sharing, and database administration, followed by web servers and cloud technologies. The book also covers infrastructure as code, automation, version control, virtualization, containers, and Kubernetes. It concludes with Linux security, vulnerability management, encryption, system hardening, and certification preparation.

By the end of this book, you will be able to deploy, manage, troubleshoot, automate, secure, and scale Ubuntu Server environments with confidence. Whether your goal is Linux system administration, cloud engineering, DevOps, or infrastructure automation, this guide provides the practical knowledge needed to work effectively with Ubuntu Server in modern IT environments.

Description
Critical infrastructure is no longer isolated. As IT, OT, and IoT converge, the systems that power energy, transportation, healthcare, and smart cities have become interconnected and increasingly exposed. In today’s landscape, cyber threats are not limited to data breaches; they can disrupt physical operations, economies, and even human safety. With nation-states and cybercriminals leveraging advanced technologies such as AI and automation, cybersecurity has become a critical pillar of operational resilience and national security.

This book provides a comprehensive journey into the modern digital battlefield. It begins with the fundamentals of OT, IoT, and critical industries, then explores real-world threats, including ransomware, supply chain attacks, and nation-state cyber operations. Readers will gain insights into how cyber is used alongside traditional warfare, the role of emerging technologies like AI, and the evolving tactics of adversaries. The book further introduces practical frameworks, Zero Trust principles, and modern security strategies to help organizations secure converged IT/OT environments, manage risk, and build resilience in complex industrial ecosystems.

By the end of this book, readers will have a clear understanding of the risks facing critical infrastructure and the strategies required to defend it. They will be equipped with practical knowledge to bridge IT and OT security, strengthen cyber resilience, and implement effective controls, enabling them to protect mission-critical systems with confidence in an increasingly complex threat landscape.

Description
Mastering programming logic and computational thinking is the essential foundation for coding. Written in learner-friendly language with real-life analogies, this book systematically guides you step-by-step through core principles without overwhelming complexity, building a strong foundation for your future programming skills.

This book begins with computer architecture, memory hierarchy, and number systems, then introduces logic design using variables, data types, operators, flowcharts, and algorithms. You will explore selection structures for decision making, starting with simple if-else logic and progressing to advanced nested structures, else-if ladders, and switch-case branching. The text deepens your skills with core looping mechanics, entry- and exit-controlled repetition, tracing methods, mathematical applications, and nested loop patterns. Finally, you will learn program structuring through modular programming, data organization using one-dimensional and multi-dimensional arrays, and persistent file handling operations.

By the end of this book, you will be well-equipped to transition from logic design to programming languages like C, Python, or Java and possess a solid foundation ready for advanced programming courses.

Description
Start your SQL Server and T-SQL journey with a clear, simple, and step-by-step guide that helps you build practical database skills from the ground up. You will learn DDL to create databases, schemas, tables, constraints, and indexes, and DML to retrieve and modify data. You will build advanced querying and analytical skills with joins, subqueries, CTEs, built-in functions, pivot, unpivot, rollup, and ranking and window functions.

You will use T-SQL features including temporary tables, cursors, WHILE loops, CASE expressions, IF...ELSE statements, transactions, error handling, concurrency controls, and isolation levels. You will create stored procedures, views, functions, and triggers; process XML and JSON; improve performance through indexing and tuning; troubleshoot issues; and deploy database solutions.

Updated for SQL Server 2022, this edition covers relevant features and practical topics without promising exhaustive coverage. It expands coverage of built-in functions, pivot, unpivot, rollup, cursors, concurrency concepts, isolation levels, performance tuning, and tips for writing efficient stored procedures.

What you will learn
? Create database objects and retrieve and modify data.
? Perform advanced querying and analysis with joins, subqueries, CTEs, pivot, unpivot, rollup, and window functions.
? Use T-SQL features, transactions, error handling, concurrency controls, and isolation levels.
? Develop stored procedures, views, functions, and triggers.
? Process XML and JSON data.
? Optimize, troubleshoot, and deploy database solutions.

Who this book is for
SQL for All is the core idea behind this book. Whether you are a student, fresher, aspiring database developer, data analyst, data engineer, or data enthusiast, this book is designed to make T-SQL and data literacy accessible, practical, and easy to learn. No prior experience is required—just a willingness to learn and explore the world of data.

Table of Contents
1. Getting Started
2. Tables
3. Indexes
4. DML
5. Built-In Functions - Part 1
6. Join, Apply, and Subquery
7. Built-In Functions – Part 2
8. Pivot and Unpivot
9. Dealing with XML and JSON
10. Variables and Control Flow Statements
11. Temporary Tables, CTE, and MERGE Statement
12. Cursors
13. Performance Tuning Essentials
14. Error Handling and Transaction Management
15. Data Conversion, Cross-Database, and Cross-Server Data Access
16. Programmability
17. Tips for Efficient Stored Procedures
18. Deployment

Description
Application programming interfaces are a key part of software development, enabling communication between applications and services. This book provides a practical understanding of API concepts, covering API design, API styles, API tools, microservices, security, and practical implementation approaches.

The book introduces transmission model approaches, including pull model, push model, and streaming, along with legacy system issues. It also covers endpoint design, URI, URL, HTTP methods, and status codes. Readers will explore SOAP-based API, REST API, GraphQL, RPC, WebSocket, Webhooks, and API tools such as Swagger, SDKs, stubs, Postman, and Karate Labs. The book further explores microservices architecture, covering service communication, data modelling, resilience, governance, management, and platform concepts. It introduces advanced patterns including CQRS, SAGA pattern, BFF, and service mesh, along with API performance and security concepts such as Basic Auth, OAuth 2.0, JWT, API keys, and Transport Layer Security.

By the end of this book, the readers will be able to evaluate API technologies confidently, design and evolve APIs with empathy for consumers, and create API ecosystems that scale with product needs and team maturity.

Description
Rule-Based NLP with NLP++ is a comprehensive guide to building accurate, transparent, and maintainable text analysis systems using NLP++, the only programming language created specifically for natural language processing. Authored by the creators of NLP++ and the VisualText IDE, this book guides readers through the full spectrum of rule-based NLP development, from foundational concepts to production-grade analyzers.

The book introduces the NLP++ pipeline architecture and its uniform, glass-box approach to text analysis, in contrast to opaque statistical and ML methods. Using the VisualText IDE, readers will learn to design and build multi-pass text analyzers, write grammar rules and functions, and manage hierarchical knowledge bases. Practical chapters explore example analyzers for date-time recognition, formatted text analysis, and named entity extraction with coreference resolution. An advanced English language analyzer is also documented in detail. Integration chapters cover calling NLP++ analyzers from Python, TypeScript, C++, and the HPCC Systems supercomputing platform.

Whether you are a computational linguist, software engineer, or student of NLP, this book equips you with the tools and thinking needed to build explainable, customizable, and high-performing text analysis systems that emulate human language processing.

Explore Angular's latest features, from signals and standalone components to SSR, SSG, AI tooling, and production-ready UI and data patterns, so you finish with skills and a portfolio that work on the job

Key Features

• Master a suite of hands-on solutions and leave with a hiring-ready portfolio that proves job-ready skills
• Deliver fast and ship with confidence; from SSR/SSG to performance gains and reliable UI stacks
• Add focused AI features like OCR, summaries, and assistants where they help most

Book Description

What you will learn

• Scaffold faster and refactor safely with AI-assisted workflows
• Design trustworthy forms users can complete without friction
• Add AI: summaries, and assistant-driven booking
• Integrate real services: Maps, email, Firebase, MongoDB
• Ship quickly with SSR/SSG and Core Web Vitals improvements
• Build maintainable UIs with PrimeNG, Material, Telerik

Who this book is for

This book is for developers with beginner-level Angular experience who want to become proficient in using essential tools and dealing with the various use cases in Angular. Beginner-level knowledge of web application development and basic experience of working with latest JavaScript or TypeScript is essential before you dive in. This book focuses on practical applications of Angular. If you want to deepen your understanding of this framework, we recommend that you also look at Learning Angular from the same author.

Build efficient systems software with the Zig programming language by creating UNIX tools, network services, asynchronous applications, and high-performance servers.

Key Features

• Build real-world systems software and UNIX programming tools through practical Zig projects
• Develop network programming skills through TCP, UDP, HTTP services, concurrent applications, and CLI tools
• Master memory management, I/O, and systems-level design with the Zig programming language

Book Description

What you will learn

• Build production-ready UNIX command-line tools with Zig
• Develop TCP, UDP, and HTTP network services and applications
• Apply systems programming techniques to memory, filesystems, and process management
• Manage memory and binary data safely and efficiently
• Implement multithreading, synchronization, and concurrent systems
• Create asynchronous I/O and event-driven network applications
• Integrate SQLite into real-world Zig applications
• Design and build a domain-specific language using parsing and comptime techniques

Who this book is for

Software developers, systems programmers, UNIX systems engineers, and backend engineers who already understand Zig fundamentals and want to build production-ready systems software. Familiarity with programming concepts and experience using languages such as C, C++, Rust, Go, or Python will help you get the most from this book.

Learn to manage security incidents, hunt advanced threats, and defend IT systems using Microsoft security tools, gaining hands-on expertise to ace the SC-200 exam and become a certified Microsoft Security Operations Analyst

Key Features

• Get expert guidance on detecting, investigating, and responding to cyber threats
• Develop practical skills through real-world scenarios and step-by-step security implementations
• Enhance your SOC expertise with automation and advanced incident response techniques
• Purchase of this book unlocks access to web-based exam prep resources including mock exams, flashcards, exam tips

Book Description

What you will learn

• Understand Microsoft security operations and threat protection in detail
• Configure and manage Microsoft Defender XDR for endpoint security
• Deploy Microsoft Sentinel and integrate various data connectors
• Investigate security incidents using Microsoft Defender tools
• Analyze alerts, incidents, and evidence in Microsoft security portals
• Implement Microsoft Defender for Cloud to secure cloud environments

Who this book is for

This book is for security analysts, SOC professionals, and cloud security engineers who want to master Microsoft security tools, investigate threats, and pass the SC-200 exam. A basic understanding of Microsoft technologies and security concepts is recommended.

Master data visualization with D3.js v7 using modern web standards and real-world projects to build interactive charts, maps, and visual narratives

Key Features

• Build dynamic, data-driven visualizations using D3.js v7 and ES2019+
• Create D3 data visualizations, including charts, maps, and networks
• Master data visualization with JavaScript through hands-on examples

Book Description

What you will learn

• Bind data to DOM elements and apply transitions and styles
• Build interactive bar, line, pie, scatter, tree, and animated network charts
• Implement interactive behaviors with zoom, drag, and tooltips
• Visualize hierarchical data, flows, and maps using D3 layouts and projections
• Use D3 with HTML5 Canvas for high-performance rendering
• Create thematic geographic maps using standard GeoJSON and TopoJSON shapefiles
• Complete 100+ exercises with commented templates and solutions
• Build full visualizations through 10 guided online exercises

Who this book is for

This book is for web developers, data journalists, designers, analysts, and anyone who wants to create interactive, web-based data visualizations. A basic understanding of HTML, CSS, and JavaScript is recommended. No prior knowledge of SVG or D3 is required.

Build, deploy, and monitor AI applications using Microsoft Foundry's unified portal, combining models, workflows, agents, and responsible AI practices into a single development experience.

Key Features

• Build, evaluate, and deploy AI solutions using Microsoft Foundry’s unified portal
• Implement guardrails, evaluations, and monitoring for production-ready AI systems
• Includes real-world use cases integrating Azure OpenAI and Databricks
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Select and deploy models for vision, language, and custom AI scenarios
• Use Prompt Flow to design and refine complex AI interactions
• Evaluate models using standard performance metrics
• Build assistants, copilots, and image-processing solutions with Azure OpenAI
• Design, deploy, and orchestrate multi-agent systems using Microsoft Foundry Agent Service
• Utilize Microsoft Foundry Observability for real-time monitoring and evaluation
• Apply Microsoft's Responsible AI principles to real applications

Who this book is for

This book is for developers, data professionals, and AI practitioners who want to build and deploy intelligent applications using Microsoft Foundry. Whether you're transitioning from Azure AI Studio or starting fresh, this guide will help you understand how to design real-world AI systems using modern tools and best practices. Basic knowledge of programming and data concepts will help you get the most out of this book.

Time series is far more than fit-predict forecasting. Real mastery comes from intuition and is built through experimentation. Walk the full range with two practitioners: forecasting, conformal prediction, transfer learning, and beyond.

Key Features

• Grasp core concepts through clear explanations that build genuine understanding rather than surface familiarity
• Work with realistic datasets and develop the judgement to choose the right approach for your problem
• Progress from neural network fundamentals to advanced techniques across a full range of time series challenges.

Book Description

What you will learn

• Build, train, and evaluate neural networks for time series using PyTorch and PyTorch Lightning. Tune models with Bayesian optimisation and validate them with suitable metrics and strategies.
• Progress from feedforward and recurrent networks to transformers and models such as N-BEATS, N-HiTS, and TFT.
• Learn how global models use cross- and transfer learning across many series.
• Generate synthetic series and representations with diffusion and self-supervised methods.
• Apply modern approaches to classification, clustering, and anomaly detection.

Who this book is for

This book is for data analysts, scientists, and students who want to know how to apply deep learning methods to time-series forecasting problems with PyTorch for real-world business problems. While the book assumes some understanding of statistics and modeling, you won’t need in-depth knowledge of time series to follow along. Some familiarity with Python is important, but we do not assume any prior knowledge of PyTorch. The main goal of this book is to be accessible to those with little or no experience with deep learning methods in time series.

Build and deploy AI-powered Angular apps using Gemini, Genkit, multimodal AI, MCP, and RAG to create intelligent UIs, generate images or video, and turn concepts into scalable cloud solutions

Key Features

• Integrate cutting-edge AI such as Gemini and multimodal capabilities into Angular apps
• Build intelligent features such as image and video generation, MCP, RAG
• Deploy robust, scalable AI solutions to the cloud
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

What you will learn

• Integrate LLMs and Gemini multimodal AI into Angular
• Build dynamic text generation and interactive chat interfaces
• Create AI-driven image and video generation tools
• Implement RAG with Firestore for grounded LLM responses
• Develop robust Angular SSR apps with advanced AI-powered features
• Master testing, security, and deployment for AI solutions
• Understand ethical AI practices in web development
• Strategize AI for growth and innovation in Angular products

Who this book is for

This book is for mid-level to senior Angular developers who want to integrate advanced AI capabilities into their applications. It's also ideal for team leads and C-level executives looking to understand and implement AI strategies for driving innovation and growth within their Angular-based products. A solid grasp of Angular fundamentals and TypeScript is assumed. While not strictly required, familiarity with fundamental AI/ML concepts like LLMs and APIs will be helpful, as the book provides comprehensive context necessary for AI integration.

Master algorithmic short selling with Python by learning practical techniques, coding trading signals, and applying robust risk management to generate alpha in any market condition.

Key Features

• Build and test algorithmic short-selling strategies in Python
• Apply advanced trade execution, position sizing, and risk controls
• Harness idea generation, regime detection, position sizing, pairs trading, portfolio management, and asset allocation

Book Description

What you will learn

• Generate long and short ideas across all types of markets
• Systematically classify securities as bullish or bearish
• Detect sector rotation ahead of consensus
• Apply risk-adjusted position sizing tailored to short selling
• Avoid crowded trades, go long short squeezes, and navigate high dividend yield value traps
• Manage a long/short portfolio with four exposures: gross, net, Beta, and concentration
• Combine uncorrelated strategies to generate a smoother equity curve
• Use an AI-powered trading journal to elicit subconscious beliefs that drive your trading decisions

Who this book is for

This book is for quantitative traders, portfolio managers, algorithmic trading developers, and advanced retail traders who want to master the short side using Python. A working knowledge of Python and basic trading concepts is assumed. Readers will gain not just coding skills, but also the strategic and risk management frameworks needed to build profitable short strategies.

Zephyr RTOS Cookbook delivers hands-on recipes for tackling real-world challenges in portable, scalable Zephyr application development Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*

Key Features

• Build and organize Zephyr applications using West to enable clean, reproducible, multi-repo workflows
• Configure features with Kconfig and describe hardware with DeviceTree
• Develop portable, scalable systems for industrial and IoT devices using Zephyr subsystems and the device driver model

Book Description

What you will learn

• Set up a reproducible Zephyr development environment and West workspace
• Structure apps and modules
• Navigate the Zephyr build flow and inspect key generated outputs
• Configure features with Kconfig
• Describe and customize hardware using devicetree
• Use common subsystems: GPIO, I2C, ADC, logging, and shell
• Apply user mode to enforce security
• Control peripherals from applications using drivers

Who this book is for

This book is for embedded developers and engineers transitioning to Zephyr from traditional RTOSes, bare-metal environments, or embedded Linux. It is aimed at readers with experience in embedded C who want to adopt Zephyr as a scalable platform for building portable systems that can be deployed consistently across multiple boards and development teams.

Understand data analysis pipelines using Python Data Analysis, machine learning, pandas, scikit-learn, and data visualization techniques. Build scalable workflows for time series, NLP, image analytics, and big data processing.

Key Features

• Prepare, clean, and transform data with Python, pandas, and exploratory data analysis techniques
• Apply machine learning with Python using regression, classification, clustering, PCA, and Bayesian methods
• Scale analytics workflows using Dask, Ray, Modin, and PySpark

Book Description

What you will learn

• Prepare, clean, and transform data for exploratory data analysis and data wrangling
• Analyze and visualize data using Python and pandas
• Perform time series analysis, forecasting, and signal processing
• Apply machine learning with Python using scikit-learn techniques
• Use regression, classification, clustering, PCA, and Bayesian methods
• Perform sentiment analysis, NLP, graph analytics, and image analytics
• Accelerate workflows using Dask, Modin, and Ray
• Build scalable big data analytics pipelines with PySpark

Who this book is for

This book is for data analysts, data scientists, business analysts, statisticians, students, and academic professionals who want to strengthen their Python Data Analysis skills. It is ideal for readers looking to apply data science with Python to real-world problems involving data preparation, visualization, machine learning, NLP, image analytics, and big data processing. A basic understanding of mathematics and working knowledge of Python will help you get the most from this book.

Most books teach you how to build LLMs from scratch or deploy them via APIs. This book uses guided machine learning projects to teach you how to understand, visualize, and investigate LLMs including GPT and BERT.

Key Features

• Each project is built around three learning goals: machine learning techniques, LLM mechanisms, and Python coding with data visualization.
• This is not a dense theoretical textbook; it's hands-on, practical, and project-oriented.
• You will learn how to measure, visualize, and manipulate the internal components of LLMs directly.

Book Description

What you will learn

• Tokenization schemes and their statistical properties
• Embedding spaces: cosine similarity, semantic axes, and analogy vectors
• Output logits, softmax distributions, perplexity, and language biases
• Layer-by-layer transformer dynamics and dimensionality
• Attention mechanisms: QKV weights, attention scores, head ablation, and activation patching
• MLP subblocks: neuron tuning, mutual information, subspace analysis, and statistics-based causal manipulations
• Logit lens, indirect object identification, and causal tracing

Who this book is for

This book is for data scientists, ML engineers, and researchers who want to go beyond surface-level understanding of LLMs. Prior Python experience is required. Familiarity with machine learning or deep learning is helpful but not required — techniques are introduced as they arise throughout the projects.

Learn how to integrate AI into Linux environments with real-world automation, observability, and scalable deployment techniques for modern infrastructure teams

Key Features

• Apply AI to Linux, from core concepts to production-ready deployments at scale
• Build intelligent automation using LLMs, RAG, and AI agents for monitoring, troubleshooting, and system administration
• Deploy secure, scalable AI workloads with Docker, Kubernetes, and cloud-native best practices

Book Description

What you will learn

• Optimize Linux kernels and GPUs for AI workloads
• Orchestrate LLM pipelines across distributed systems
• Design agentic workflows for autonomous operations
• Implement RAG over logs and internal knowledge graphs
• Embed AI into observability and incident triage
• Deploy scalable AI microservices on Kubernetes
• Enforce security, isolation, and model guardrails

Who this book is for

This book is for Linux engineers, system administrators, DevOps professionals, SREs, and platform engineers who want to integrate AI into real-world infrastructure and operations. Prior hands-on experience with Linux, the command line, and basic system administration is expected. Some familiarity with containers (Docker), Kubernetes, and scripting (Bash or Python) would be helpful. Prior AI or machine learning knowledge is beneficial but not required, as core concepts are explained in practical Linux terms.

Learn to design, implement, and scale distributed observability in Rust using OpenTelemetry, with practical examples for tracing, logging, and metrics.

Key Features

• Implement end-to-end observability in Rust using OpenTelemetry APIs and Collector
• Correlate logs, traces, and metrics across async, multithreaded Rust applications
• Build and deploy an observable Rust microservice with Actix, Redis, and Prometheus
• Configure dashboards, alerts, and trace views in Grafana using real telemetry data

Book Description

What you will learn

• Understand the three pillars of observability in Rust
• Apply tracing and logging using the Tokio and OpenTelemetry crates
• Export telemetry to backends like Prometheus, Jaeger, and Grafana
• Use the OpenTelemetry Collector to manage telemetry pipelines
• Correlate metrics, logs, and traces for faster debugging
• Implement structured logging, redaction, and context propagation
• Optimize telemetry costs with sampling strategies
• Build and deploy an observability-first Rust microservice

Who this book is for

Rust developers building backend systems, DevOps engineers, and SREs deploying Rust in production will benefit from this book. Ideal for readers experienced in Rust development who want to implement end-to-end observability using OpenTelemetry and tools like Grafana, Prometheus, and Jaeger.

Master Blazor's evolving render modes, hosting models, and observability features with practical projects and real-world architecture. Build confidently for production with .NET 10 and C# 14

Key Features

• Dedicated, side-by-side coverage of Blazor render modes without forcing them into a single project
• Updated for .NET 10 LTS with first-class coverage of .NET Aspire and modern observability
• Project structures and examples designed around real production constraints, not demos

Book Description

What you will learn

• Understand how Blazor works and when to use each render mode
• Build simple and advanced Blazor components with confidence
• Structure applications to separate concerns and support multiple hosting models
• Implement authentication and authorization using modern .NET patterns
• Improve performance with caching and rendering optimizations
• Use OpenTelemetry to gain insights into application behavior and performance
• Build, run, and manage applications using Aspire

Who this book is for

This book is for .NET web developers and software developers who want to use their existing C# skills to build interactive web applications running in the browser with Blazor WebAssembly, on the server with Blazor Server, or using a combination of both. You’ll need a basic understanding of C# and some prior exposure to .NET web development. The book will guide you through the rest.

Description
Golang, which is created and maintained by Google, is one of the most powerful programming languages used to build cloud-native applications and distributed systems. The simplicity, concurrency model, and efficient runtime of the programming language make it a preferred choice for modern cloud and microservices.

The Golang Crash Course is a comprehensive and structured guide that covers all the necessary concepts to become a Golang expert, including concurrency, microservices architecture, and scalable API development. The book begins with the basics of Golang’s syntax, data structures, functions, and error handling. It then explores Golang’s powerful concurrency model using goroutines and channels, which helps readers design highly efficient parallel programs. In the final section, readers will learn how to build real-world microservices, develop REST APIs, secure services, deploy applications using Docker and Kubernetes, and finally manage data in distributed systems.

By the end of this book, readers will be able to design, build, secure, and deploy production-ready Golang applications. They will gain practical experience in building scalable backend services and cloud-native systems using modern development tools and best practices.

Description
As digital ecosystems grow more complex and customer expectations reach new heights, the convergence of site reliability engineering (SRE) and artificial intelligence for IT operations (AIOps) is redefining how modern enterprises ensure resilience, performance, and reliability at scale. Intelligent automation and data-driven operations are no longer optional; they are the foundation of competitive advantage. This book is your essential guide to merging these two powerful disciplines to build faster, smarter, and more resilient operations.

This book begins with the foundational principles of SRE: SLOs, SLIs, error budgets, and toil reduction, before progressing through AIOps tooling, observability, and the unified knowledge base. Readers explore intelligent incident management, change and problem management, advanced anomaly detection using autoencoders and isolation forests, causal inference for root cause analysis, and the AIOps-powered SRE assistant. The book also explores chaos engineering, generative AI-powered SRE chatbots, and enterprise-scale AIOps adoption, culminating in a strategic roadmap for autonomous operations, predictive governance, and the role of LLMs and agentic AI in the future of reliability engineering.

By the end of this book, readers will possess both the strategic mindset and the technical depth to architect, lead, and scale intelligent operations. Whether you are an SRE practitioner, IT architect, or technology leader, you will be equipped to move from reactive firefighting to proactive, self-healing operations, delivering measurable reliability and business impact.

What you will learn
? Apply SRE principles, SLOs, SLIs, and error budgets effectively.
? Evaluate and operationalize AIOps platforms for SRE goals.
? Build unified observability models from logs, metrics, and traces.
? Automate incident triage, correlation, and postmortem workflows.
? Deploy advanced anomaly detection using ML models.
? Design chaos engineering experiments to validate SLOs.
? Architect generative AI chatbots for incident and runbook automation.
? Scale AIOps across enterprise teams with measurable outcomes.

Who this book is for
This book is for SREs, IT operations managers, cloud architects, and technology leaders who want to evolve from traditional operations to intelligent, AI-driven reliability practices. Readers should have intermediate experience in DevOps, SRE, or IT operations and a working familiarity with monitoring tools and cloud infrastructure.

Table of Contents
1. SRE Principles Driving Modern Operations
2. AIOps Tools for SRE
3. AIOps Knowledgebase
4. Intelligent Incident Management for SREs
5. Streamlining Change and Problem Management
6. Path to Productivity and Reliability
7. Advanced Anomaly Detection
8. Causal Inference and Efficient Root Cause Analysis
9. Intelligent SRE Assistant
10. Chaos Engineering and Reliability Testing
11. Generative AI-powered SRE Chatbot
12. Scaling AIOps Across the Enterprise
13. Future Trends in SRE and AIOps

Description
Data science is the engine driving modern innovation, making Python mastery essential for anyone looking to turn raw information into actionable strategy. This book serves as your streamlined roadmap, bridging the gap between basic data literacy and professional-grade analytical execution. This book provides a solid foundation in Python programming, including loops and conditional statements, before advancing to high-performance libraries like NumPy, Pandas, Matplotlib, and SciPy. You will master the data analysis process, from cleaning missing values to advanced visualization with Seaborn and geospatial mapping. It concludes with the mathematical foundations of supervised and unsupervised learning, predictive mining, and building recommender systems through real-world case studies in healthcare, finance, and retail analytics. By the end of the book, you will be well-equipped to handle complex datasets and deploy predictive models with confidence. You will possess a practical understanding of data science principles and a professional project portfolio, ready to apply these skills to solve real-world problems in any industry.

Description
With technology changing rapidly and businesses becoming more competitive, adopting the latest technology is no longer just a desire; it has become essential for businesses. Technology is helping organizations not only reinvent and redefine themselves but also create new business models that were previously not possible.

This book offers a practical journey through business transformation using emerging technologies. It provides references to use cases and applications that can be developed across industries using a combination of emerging technologies. It explains how Industry 4.0 is helping organizations become more productive and examines sectors such as BFSI, media and entertainment, defense, and education, which are undergoing major transformation through technology. The book suggests a basic process for carrying out a transformation journey, including business risk management and technology architecture. It also highlights the importance of explainable AI and ethics in AI to ensure proper regulations, while addressing challenges, risk management, and concepts such as artificial general intelligence (AGI).

By the end of this book, you will be equipped to handle real-world projects and confidently apply your knowledge to solve complex problems and create innovative solutions.

What you will learn
? Emerging technology trends and their applications in different business verticals.
? Future trends in agriculture to meet the growing food requirements.
? Using healthcare data for new age innovations in healthcare.
? Movement to customer and employee-centric manufacturing, Industry 6.0.
? Smart city and models to aggregate systems for a smarter country.

Who this book is for
This comprehensive guide helps beginners and C-suite executives navigate business and emerging tech. It offers actionable digital transformation steps for leaders, academics, professionals, entrepreneurs, and compliance experts.

Table of Contents
1. Emerging Technologies and Augmented Intelligence
2. Augmented Intelligence with IoT for Agriculture and Sustainability
3. Technology Disrupting Healthcare
4. Industry 4.0/5.0 Impacting Manufacturing
5. Making Cities Smarter
6. Transforming Banking, Financial Services, and Insurance
7. Augmented IoT in Retail, Transportation, Logistics, and Service Industry
8. Defense Intelligence Internet of Things
9. Democratizing Education and Skilling Using Technology
10. Reshaping the Entertainment Industry
11. Industrial Digital Transformation Journey
12. New-age Skilling for Digital Transformation
13. Core Technology Frameworks Required for Digital Transformations
14. Summary and Future Directions Appendix A: References

Description
Digital forensics identifies and preserves digital evidence for legal use. By recovering data from diverse sources, investigators track trails vital for solving cybercrimes, managing network intrusions, and ensuring compliance. It is a key pillar of modern security and data recovery.

This book systematically guides you through enterprise readiness, legal compliance, and setting up forensic environments using Python and PowerShell. You will master evidence acquisition across Windows, Linux, and macOS, while exploring network analysis, memory forensics, and malware dissection with Sysinternals and VirusTotal. The book also explores case management with Autopsy, mobile forensics for Android and iOS, and bit-for-bit disk imaging. Featuring over 100 practical recipes, you will learn professional DFIR reporting and cloud-native evidence collection within AWS and Azure.

By the end of this book, readers will have the essential digital forensics skills to investigate, respond to, and recover from cyberattacks while preserving evidence for legal, regulatory, or internal use. Existing cybersecurity professionals will find it easy to acquire these skills, helping them achieve their digital forensics career goals.

Learn to transform LLM capabilities into production-ready agent systems using practical patterns and domain-driven approaches, guided by Imran Ahmad, author of 50 Algorithms Every Programmer Should Know Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*

Key Features

• Design and implement 30 proven agent architectures used in real-world production environments
• Build scalable, secure, and resilient agent workflows that move beyond simple chat interfaces
• Master core agentic principles—perception, memory, reasoning, and planning—to create truly autonomous systems

Book Description

What you will learn

• Deploy production-ready agent systems that scale securely and reliably
• Use LangChain and LangGraph to build autonomous agents with modular architectures
• Implement agents with sophisticated memory, planning, and reasoning capabilities
• Seamlessly integrate tools, APIs, and external data into agent workflows
• Establish robust evaluation frameworks to measure and optimize agent performance
• Implement guardrails and explainability features to ensure ethical and safe deployment
• Build multi-agent systems for complex, collaborative task orchestration
• Apply specific agent architectures across healthcare, finance, and legal domains

Who this book is for

This book is designed for AI engineers, software developers, machine learning researchers, and technical leaders who are building intelligent systems or deploying LLM-powered applications. It is particularly beneficial for professionals transitioning from traditional machine learning to agent-based architectures or those solving complex automation challenges. Python experience and basic machine learning knowledge are recommended to get the most out of the code implementations.

Description
Cloud computing has become the essential foundation for modern digital transformation, enabling businesses to scale rapidly and innovate through on-demand technology. This book is an all-encompassing guide designed to empower IT professionals and beginners alike with the knowledge and skills needed to master cloud computing.

This book offers a user-friendly approach to learning, covering everything from fundamental concepts to advanced techniques across major cloud platforms like AWS, Azure, and Google Cloud. You will master core infrastructure like EC2 and Kubernetes while exploring advanced security, data management, and automated machine learning pipelines specifically within the Azure ecosystem. It further addresses multi-cloud strategies, hybrid infrastructure, and real-world projects essential for enterprise environments. Every chapter combines technical knowledge with certification guidance, offering a complete roadmap to success in the evolving cloud landscape.

By the end of this book, you will possess a professional-grade understanding of the global cloud market and the technical competence to deploy secure, AI-enhanced solutions. You will be fully prepared to navigate complex cloud architectures and advance your career in this high-growth industry.

Description
Microsoft security is the essential foundation for protecting modern businesses, and mastering its architecture is vital for any cybersecurity professional. The SC-100 Microsoft Cybersecurity Architect exam focuses on how security solutions are designed across identity, data, applications, and infrastructure using Microsoft technologies.

This book follows the SC-100 skills measured, aligned to the January 2026 exam update. It explores Zero Trust, identity, security operations, data protection, network design, and governance, focusing on how these pieces fit together as the exam expects. You will learn to architect resiliency with the Cloud Adoption Framework, manage identities through Entra ID, and secure privileged access using PIM. The book also discusses hardening endpoints, IoT, and OT systems while mastering cloud workload protection and network security via Entra Private Access. Finally, you will design robust data governance across Microsoft 365, APIs, and Azure databases using Purview and Defender for Cloud.

By the end of this book, you will be well-equipped to evaluate complex security requirements and design end-to-end solutions that meet global compliance standards. You will possess the practical skills needed to ace the SC-100 exam and excel as a professional Microsoft cybersecurity architect in real-world scenarios.

Description
Vibe coding is revolutionizing software development, allowing users to build and ship functional applications through conversational prompting rather than traditional coding. This emerging methodology accelerates prototyping and enables rapid creation of digital products.

This book explores the cutting-edge developments in the field of AI-powered software development from its foundational principles to the most advanced vibe coding techniques available today. We will discuss the paradigm shift from code-first to prompt-first development, examine how vibe coding is disrupting industries from healthcare to finance, and investigate the tools, platforms, and practices that make this methodology so powerful. Our journey will take us through the conversational development model, architectural considerations of AI-assisted applications, and ambitious real-world projects that demonstrate what is truly possible when you simply describe what you want and let AI figure out the rest.

By the end of this book, you will be a competent creator capable of moving fast and shipping products without getting bogged down in legacy engineering concepts. You will possess a holistic, hands-on understanding of vibe coding, ready to leverage AI to turn your creative visions into high-performance, real-world software.

Description
Modern web development requires more than building pages and APIs. Developers now need to create responsive frontends, secure backends, reliable database integrations, and automated deployment workflows. This book addresses that need by bringing React, Angular, Node.js, and DevOps into one practical learning path.

The book starts with HTML, CSS, advanced CSS, JavaScript, DOM, and core web technology fundamentals. It then moves into React and Angular, followed by hands-on frontend projects and framework comparison. On the backend side, it covers Node.js with Express.js, REST API development, authentication, MongoDB with Mongoose, PostgreSQL with Sequelize, web services, third-party APIs, Git and GitHub workflows, deployment strategies, and application security. The final part focuses on DevOps, including CI/CD, Docker, Docker Compose, Kubernetes, Jenkins, GitHub Actions, monitoring, and logging.

By the end of this book, readers will be able to design, build, secure, deploy, and maintain complete web applications with confidence. The practical projects, exercises, and real-world workflow focus make it suitable for both academic learning and professional upskilling.

Description
Linux networking is the backbone of modern IT infrastructure, powering everything from local servers to massive cloud environments. Linux offers robust support for networking technologies like switching, routing, firewalls, load balancing, VPNs, etc., making it a great platform for networking enthusiasts, administrators, and developers.

This book is structured to guide you from fundamental concepts to advanced configurations. You will start by understanding the basic concepts of switching and routing on Linux, progress into advanced topics of firewalls and load balancers, and explore traffic shaping and VPNs. Later chapters explore network monitoring, troubleshooting of network services, and networking in the cloud. Each chapter includes practical examples and best practices. Whether you are configuring a home network or setting up an enterprise system, this book provides the essential foundation for networking services on Linux. This book will equip you to handle real-world scenarios from providing connectivity, securing access using firewalls, VPNs, load balancing, and other essential network services on Linux.

By the time you finish this book, you will have developed a clear foundation in networking; you will understand how services like routing, firewalls, load balancers, etc., work and how to configure them on Linux. The concepts you learn in this book will help get a better insight into the internals of services that you use every day.

Description
Modern cyberattacks no longer rely on noisy exploits or obvious malware. Today’s adversaries abuse identity systems, cloud APIs, misconfigurations, CI/CD pipelines, and trusted infrastructure to move laterally, persist, and quietly exfiltrate data. Red Teaming has evolved from penetration testing into full adversary simulation, testing not just vulnerabilities but real organizational resilience.

This book provides a practical guide to modern red team operations. It covers reconnaissance, initial access, privilege escalation, lateral movement, command-and-control, persistence, cloud and Kubernetes attacks, CI/CD and supply-chain abuse, and real-world post-exploitation techniques. Defensive strategies are tightly integrated, including identity hardening, admission controls, policy as code, detection engineering, and incident response, with real case studies demonstrating how attacks succeed and how they are stopped.

After reading this book, readers will be able to model real attacker behavior, execute or defend against realistic red team engagements, and translate offensive findings into concrete security controls, detections, and operational improvements.

Description
Data Structures and Algorithms are important subjects in any university curriculum for the computer science stream. It provides a great tool in the hands of software engineers and plays a significant role in software design and development. It is also becoming a must-have skill for many competitions and job interviews in the software industry.

This book covers the topics useful for students and also for software developers working in the industry. The concepts are explained in a step-wise manner and illustrated with numerous figures, text, examples, and immediate code samples, which help in a better understanding of data structures and algorithms with their implementation. There are exercises at the end of the chapters that help students to explore more and build a better foundation of the subject. The book has more than 500 illustrations, code samples, and problems. Solutions for exercises are also available with the programs. Students can use it for self-learning, and developers can use this for providing efficient solutions for their day-to-day development problems.

After completion of this book, students will have a good understanding of Data Structures and Algorithms concepts and implementation. Software engineers will be able to provide better solutions with appropriate data structures and efficient algorithms.

Description
Unity is the world's leading engine for building interactive experiences, and connecting it to modern backend systems is the secret to creating successful, high-performance games. Developers must learn cloud-based tools that will help them create highly scalable applications and improve gameplay and interaction, while optimizing security and privacy.

This book guides you through the entire Unity Gaming Services ecosystem, starting with frontend-backend architecture and major cloud providers like AWS and Azure. You will learn to use the Unity Dashboard for deep data mining with SQL, manage player lifecycles, and implement global data privacy laws. The chapters provide hands-on instructions for cross-platform authentication, multiplayer server hosting with Docker, and real-time Vivox voice integration. You will also learn DevOps automation through Cloud Build and stabilize your projects using Cloud Diagnostics.

By the end of this book, readers will learn how to implement more scalable, reliable, secure, and engaging applications based on real data using Unity Gaming Services. You will be a competent developer capable of launching professional-grade games with robust backend systems.

Description
Excel is the backbone of business, but its limitations with complex data and repetitive manual tasks hinder productivity. Python, the world’s most versatile programming language, offers a powerful solution. By utilizing various tools, Excel users can move beyond basic spreadsheet functions and tap into Python's robust capabilities for advanced data analysis and automation.

This book offers a practical guide to Excel (not necessarily 365) and Python users to automate tedious tasks, analyze data, and create dynamic reports. It will help you use Python’s power as an engine to drive analytics and produce deliverables in Excel, as most stakeholders expect. The first section introduces Python, one of today’s most popular languages. Learning Python is a stepping stone to mastering other advanced libraries, transitioning smoothly into broader data and automation tools. The next section discusses Python’s robust and intelligent tools for handling data. The following two sections discuss versatile tools for Python-Excel integration, enabling you to manipulate, format, and protect Excel files to generate reports. It will also help you replace VBA with Python code, interacting with legacy macros, or developing custom Excel functions to simplify workflow.

Whether you are a data professional versed in Python or a seasoned Excel user, this book will arm you with tools to harness Python's potential and Excel’s convenience. Combining the strengths of both Python and Excel will allow you to build scalable workflows that are accessible to everyone, whether you start in Excel or Python.