Computer und IT
Procedural Content Generation for Games
Learn to procedurally generate 3D content for your next game or simulation using the Blender Python API and geometry nodes. Automate parts of your asset creation pipeline while producing a starter library of environments, weapons, and other objects ready to use in your next Unreal project. You will start by getting comfortable with generating geometry in Blender Python by automating hand modeling basics, like blocking out weapon meshes by combining primitives and manipulating them with your favorite operators and modifiers. After that you’ll take a deep dive in geometry nodes and tackle projects such as adding Voronoi cracks and creating sliceform versions of any mesh. Building on your Blender Python skills, you’ll progress to fractal methods for generating realistic terrain, followed by grammar-based approaches such as L-systems for producing lifelike plants. Prefer environments based on real-world locations? Find out how to generate 3D contents based on GIS data, such as city skylines from building footprints, and 3D terrain from Digital Elevation Models (DEM). Along the way, you will also learn techniques for incorporating parametric modeling into your procedural system to optionally control chosen aspects of the generation process, to ensure that only meaningful variations coherent with the overall design are produced. Whether you are looking to generate stylized content that aligns with your artistic vision, or realistic environments true to their real-world counterparts, this book will add a variety of practical (and fun) techniques to your procedural generation arsenal. What You Will Learn ● Automate 3D modeling steps traditionally done by hand with the Blender Python API and geometry nodes ● Access Blender features such as nodes, modifiers, and operators from scripts ● Programmatically generate stylized as well as realistic game assets and environments ● Combine parametric modeling with procedural generation to control chosen aspects of the creative process and influence the types of variations in the output Who Is This Book For This book is for software developers who want to procedurally generate 3D assets and environments for their game or simulation project. Readers with high-level understanding of the 3D content pipeline and either already using Blender or are interested in learning the basics on their own would benefit from the book. In addition, the ideal readers will already know some Python basics or are motivated to pick them up along the way from resources outside the book. Chapter 1: Overview of Procedural Content Generation Methods.- Chapter 2: Blender Python Game Weapon Generator: Part 1.- Chapter 3: Blender Python Game Weapon Generator: Part 2.- Chapter 4: Generating Materials with Geometry Nodes, Python, and Shader Nodes.- Chapter 5: Editing and Generating Meshes with Geometry Nodes.- Chapter 6: Fractal Terrain Generation.- Chapter 7: L-Systems for Plant Generation.- Chapter 8: GIS Based Generation Part 1 - Skylines from Building Footprints.- Chapter 9: GIS Based Generation Part 2 - Terrain from Digital Elevation Models (DEM).- Chapter 10: Import Generated Geometry Into Unreal.
Cyberresilienz in der Praxis
Das Essential bietet einen praxisnahen Leitfaden für Unternehmen, die ihre Cyberresilienz systematisch aufbauen wollen. In sechs Schritten werden zentrale Aufgaben wie Risikoanalyse, Maßnahmenplanung, Einhaltung von Anforderungen, Einbindung von Beteiligten, Fortschrittskontrolle und langfristige Verankerung behandelt. Ziel ist es, technische und organisatorische Schutzmaßnahmen nachvollziehbar zu strukturieren und die Widerstandsfähigkeit gegenüber Cyberangriffen zu stärken. Das Buch richtet sich an IT-Verantwortliche, angehende Informationssicherheitsbeauftragte und Entscheider:innen im Mittelstand, die eine tragfähige Grundlage für den Umgang mit digitalen Bedrohungen schaffen wollen. Grundlagen.- Weg zur Cyberresilienz in sechs Schritten.- Beispielhafte Exkurse für die Praxis.
Pro Azure Governance and Security
Pro Azure Governance and Security will be an indispensable guide for IT professionals, cloud architects, and security engineers aiming to master the latest governance and security practices within Microsoft Azure. This updated edition will build on the foundational elements of the original book, integrating cutting-edge technologies and tools that have emerged in recent years. The book will provide a comprehensive understanding of how to effectively utilize Azure Policy, Blueprints, Security Center, and Sentinel, while also introducing new topics such as Azure AI, Copilot, Copilot Studio, and other advanced governance and security tools. In an era where digital transformation is accelerating, organizations are increasingly moving their workloads to the cloud. Effective governance and security practices are crucial to ensure that these cloud environments are compliant, secure, and resilient. With the continuous evolution of cloud technologies, it is essential to stay updated with the latest tools and methodologies. This book will address these needs by providing comprehensive coverage of both foundational and advanced topics, making it a vital resource for anyone responsible for managing and securing Azure environments. The integration of AI, machine learning, and automation tools like Azure Copilot will further enhance the ability to proactively manage and secure cloud resources. By incorporating these cutting-edge technologies, the book will ensure that readers are equipped with the knowledge and skills required to navigate the complexities of modern cloud governance and security effectively. What You'll Learn Modern Governance in the Cloud Advanced Azure Scaffold for Enterprise Architecture Contemporary Azure Naming Conventions and Standards Comprehensive Azure Policy Implementation Enhanced Security with Azure Security Center Leveraging Azure Monitor and Log Analytics for Operations Scaling Governance with Azure Blueprints and DevOps Azure Sentinel: Next-Generation SIEM Integrating AI and Machine Learning in Cloud Security Implementing Zero Trust Architecture in Azure Multi-Cloud and Hybrid Cloud Governance Future Directions in Cloud Governance and Security Harnessing Azure AI and Copilot for Governance and Security Additional Azure Governance and Security Tools Who This Book Is For Technical engineers, consultants, solution and cloud architects, IT managers, and SecOps teams who need to understand how to integrate governance, security, and compliance in hybrid and Azure environments. A basic understanding of Azure or other public cloud platforms is beneficial, but not required. Chapter 1: Modern Governance in the Cloud.- Chapter 2: Advanced Azure Scaffold for Enterprise Architecture.- Chapter 3: Contemporary Azure Naming Conventions and Standards.- Chapter 4: Comprehensive Azure Policy Implementation.- Chapter 5: Enhanced Security with Azure Security Center.- Chapter 6: Leveraging Azure Monitor and Log Analytics for Operations.- Chapter 7: Scaling Governance with Azure Blueprints and DevOps.- Chapter 8: Azure Sentinel: Next-Generation SIEM.- Chapter 9: AI and Machine Learning in Cloud Security.- Chapter 10: Implementing Zero Trust Architecture in Azure.- Chapter 11: Multi-Cloud Environment.- Chapter 12: Future Directions in Cloud Governance and Security.- Chapter 13: Harnessing Azure AI and Copilot for Governance and Security.- Chapter 14: Elevating Skills in Azure Governance and Security.
Practical Microservices Architectural Patterns
Upgrade your distributed applications with microservices. This practical guide bridges core concepts and advanced patterns to help you build resilient, scalable and high performing microservices, whether you're transitioning from monolithic architectures or starting fresh with microservices. Fully updated for Spring Boot 3 and Spring Cloud, The Second covers modern capabilities, like reactive programming, enhanced observability, advanced security and streamlined configuration management. Learn to solve common architectural challenges in cloud-native development, including service discovery, inter-service communication, distributed transactions, configuration management and fault tolerance mechanisms like retries, timeouts and circuit breakers. You’ll also implement real-world patterns using powerful frameworks like Axon for event sourcing and command handling, and Atomikos for managing distributed transactions with XA protocols. This book provides a hands-on introduction to building modern cloud-native applications from scratch, building up to in-depth discussions on advanced topics, such as CQRS and event-driven architecture. What You Will Learn: Explore the latest features in Spring Boot 3 and Spring Cloud 2024 Build and manage microservices with, routing, security and interservice communication Apply proven patterns for real-world microservices problems Design event-driven architectures and implement CQRS Enable service discovery, centralized configuration, and resilience with Spring Cloud Handle distributed transactions using XA, and Saga patterns Leverage Axon Framework for event sourcing and command handling Secure services with OAuth2.0 and JWT Learn best practices for testing, fault tolerance and observability Who This Book Is For Java developers and software architects who have a foundational understanding of distributed multi-threaded application architecture. No prior experience with Spring Boot or Spring Cloud is required. 1. Distributed Computing Architecture Landscape. - 2. Introducing Microservices.- 3. Microservices in Depth.- 4. Microservices Architecture Principles.- 5. Core Architecture Patterns for Microservices.- 6. Asynchronous Messaging in Microservices.- 7. Getting started with Spring Boot for Microservices.- 8. Building Cloud-Native Microservices with Spring Cloud.- 9. Designing for High Availability in Microservices.- 10. Microservices Performance Tuning and Optimization.- 11. Events, Eventual Consistency and Data Integrity.- 12. Implementing CQRS with Axon Framework.- 13. Distributed Transactions.- 14. Managing Transactions in Microservices.- 15. Optimizing Transaction Strategies for Microservices.- 16. Designing Scalable and Highly Available Microservices.- 17. Building an E-Commerce System based on CQRS with Axon.- 18. Security Best Practices for Microservices.- 19. BASE Transactions and Eventual Consistency with Axon.- Appendices.
Decision-Making Techniques and Methods for Sustainable Technological Innovation
This book is an essential guide for anyone looking to drive sustainable technological innovation, providing a comprehensive toolkit of decision-making methods and real-world applications to effectively manage technology in the era of Industry 5.0. Sustainable technological innovation is critical for building a more sustainable future. As the world faces increasing environmental challenges, there is a pressing need for new and innovative technologies that can reduce resource consumption, mitigate environmental impacts, and promote sustainable development. This book focuses on the vital role of decision-making processes in achieving sustainability through technological innovation in the context of Industry 5.0. By delving into various decision-making methods and approaches employed to facilitate sustainable technological innovation across essential industries such as manufacturing, agriculture, and energy, the book will present both theoretical and applied research on managing technology, including decision-making connected to Industry 4.0 and 5.0, artificial intelligence, and other revolutionary techniques. The book covers a wide range of topics, including multiple attribute decision theory, multiple objective decision-making, patent mining, big data analytics, and other decision-making methods and techniques, and features case studies and reviews that highlight real-world applications of sustainable technological innovation in different industries. The exploration of various decision-making methods and approaches for sustainable technological innovation makes this book an essential guide for those looking toward a sustainable Industry 5.0. Readers will find the book: Emphasizes the role of decision-making processes in enabling sustainable technological innovation, providing a unique perspective on the subject;Covers a wide range of topics related to decision-making for sustainable technological innovation, including decision theory, multiple attribute and objective decision-making, patent mining, big data analytics, and case studies;Provides real-world examples and case studies that demonstrate the effectiveness of decision-making processes in promoting sustainable technological innovation across various industries;Features the latest research and developments in the field, ensuring that readers are up-to-date on the most current thinking on decision-making for sustainable technological innovation. Audience Researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics, specifically interested in decision analytics and machine learning algorithms. Kanak Kalita, PhD is an associate professor in the Department of Mechanical Engineering, Rajalakshmi Institute of Technology, Chennai, India. He has authored over 75 research articles, edited eight books, and given over 20 expert lectures. His research interests include machine learning, fuzzy decision making, metamodeling, process optimization, the finite element method, and composites. J.V.N. Ramesh, PhD is an assistant professor in the Department of Computer Science and Engineering at Koneru Lakshmaiah University with over 18 years of teaching experience. He published several papers in national and international conferences and journals, as well as six textbooks. His research interests include wireless sensor networks, computer networks, deep learning, machine learning, and artificial intelligence. M. Elangovan, PhD is currently working as a visiting professor at the Applied Science Research Centre, Applied Science Private University, Amman, Jordan. He has published over 90 articles in international journals and conferences and completed a number of consultancy projects. His research focuses on hydrodynamics, design, underwater marine vehicles, and industrial robots. S. Balamurugan, PhD is the Director of Research and Development at Intelligent Research Consultancy Services. He has published 45 books, over 200 articles in international journals and conferences, and 35 patents. His research interests include artificial intelligence, soft computing, augmented reality, Internet of Things, big data analytics, cloud computing, and wearable computing.
Green Computational Intelligence
Transform your approach to technology and sustainability with this comprehensive guide to green computing and computational intelligence. The global pursuit of sustainability has placed an urgent emphasis on developing innovative and eco-friendly technological solutions. Green computing has the potential to revolutionize the way we evaluate sustainability with the use of energy-efficient algorithms for resource optimization, sustainable hardware design, and smart resource management. Recognizing the intersection of computational intelligence and environmental stewardship, this book seeks to address the pressing challenges of integrating green practices into the realm of computational intelligence and aligning them with global sustainable development goals. Through global expertise from researchers and industry professionals, this book comprehensively covers the many applications of these innovative new technologies, as well as the challenges surrounding their implementation. Readers will find the book: Explores the convergence of environmental sustainability and advanced computational techniques, addressing the global call for energy-efficient and eco-friendly technological solutions;Integrates perspectives from computer science, engineering, environmental science, and artificial intelligence, providing a holistic view of green computing;Examines sustainable practices across diverse topics, including energy-efficient algorithms and resource optimization, sustainable hardware design, green software engineering, eco-friendly data centers, and smart resource management;Offers practical strategies for implementing sustainable computing practices while addressing theoretical and practical challenges;Highlights the role of computational intelligence in promoting sustainability, bridging the gap between technology development and environmental conservation. Audience Researchers, students, educators, and industry professionals working towards sustainable practices in and using green technology. Nitish Pathak, PhD is an associate professor in the Department of Computer Science and Engineering, the Bhagwan Parshuram Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India with over 19 years of teaching experience. He has authored and edited over ten books and published over 125 articles in international journals, conferences, patents, and book chapters. His research interests include intelligent computing techniques, empirical software engineering, trusted operating systems, cloud computing, the IoT, and artificial intelligence. Neelam Sharma, PhD is a senior assistant professor in the Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India with over 19 years of teaching experience. She has published over 95 papers in international journals, conferences, patents, and book chapters. Her research focuses on wireless sensor networks, wireless body area networks, mobile communications, AI, IoT, information security, and computer graphics. Moolchand Sharma, PhD is an assistant professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, Guru Gobind Singh Indraprastha University, New Delhi, India. He has published four books and several book chapters, as well as numerous scientific research publications in reputed international journals and conferences. His research areas include artificial intelligence, nature-inspired computing, security in cloud computing, machine learning, and search engine optimization. Dac-Nhuong Le, PhD is an associate professor of Computer Science and Dean of the Faculty of Information Technology at Haiphong University, Vietnam with over 20 years of teaching experience. He has authored and edited over 35 books and numerous articles in international journals and conferences. His areas of research include soft computing, network communication, security and vulnerability, network performance analysis and simulation, cloud computing, IoT, and image processing for biomedicine.
Path to Stellar Business Performance Analysis
Business performance analysis is central to any business, as it helps to make or mend products, services, and processes. This book provides several blueprints for setting up business performance analytics (BPA) shops, from process layout for performance measures to tracking the underlying metrics of them using website tools such as Google Analytics and Looker Studio. Delivering satisfying user experiences in the context of overarching business objectives is key to delivering elevated business performance. This book transcends the topic of tracking user behaviors in websites from generic to specific KPI scenario-based tracking using Google Analytics/Google Tag Manager. Business Performance Analysis stands out by helping you create fit-for-purpose and coherent performance analysis blueprints by integrating performance measure creation and website analytics of BPA together. What You Will Learn Design a Business Performance Analysis function Analyze performance metrics with website analytics tools Identify business performance metrics for common product scenarios Who This Book is For Senior leaders, product managers, product owners, UX and web analytics professionals Chapter 1: Vision, Goal, Objectives & Pursuit of Product Innovation.- Chapter 2: Setting up Performance Measures.- Chapter 3: Setting up Performance Frameworks and Creating Blueprints for Success.- Chapter 4: Analysing Business Performance using Website Analytics.- Chapter 5: Improving Business Performance Using Smart User Experience Design.
Kotlin Mastery
Enhance your programming toolkit and build robust applications by mastering Kotlin. This book connects Java and Kotlin through side-by-side code samples and practical demonstrations. Java programmers and up-and-coming developers seeking to learn Kotlin need to do so with confidence. Starting with the fundamentals of basic syntax, this book will cover data types, variables, control flow statements. From there move on to advanced topics like object-oriented programming concepts with null safety, lambdas, functions, inheritance and coroutines. Additionally, you’ll delve into practical applications such as designing custom domain-specific languages, working with Kotlin Multiplatform, and leveraging reactive extensions. With numerous hands-on exercises and real-world examples, you'll gain the expertise needed to explore advanced projects. What You Will Learn Explore object-oriented and functional programming with Kotlin to create modular code. Review Kotlin’s techniques for error handling and exception management. Implement Kotlin coroutines for efficient concurrency and asynchronous task management. Design custom domain-specific languages and use the Kotlin standard library for string manipulation and file handling. Who This Book is for Java developers and programmers looking to master Kotlin. 1. Introduction to Kotlin Programming.- 2. Fundamentals of Kotlin Programming.- 3. Functions in Kotlin.- 4. Object-Oriented Programming with Kotlin.- 5. Error Handling and Exceptions.- 6. Collections and Generics.- 7. Kotlin Coroutines.- 8. Kotlin DSL (Domain-Specific Language).- 9. Kotlin Standard Library.- 10. Testing in Kotlin.- 11. Kotlin Reactive Extensions (Rx).- 12. Working with APIs and Networking.- 13. Advanced Kotlin Programming.- 14. Data Analysis with Kotlin.- 15. Kotlin Multiplatform.
Large Language Models Ops for Finance
Explore emerging technologies and the evolving role of AI in finance. Geared toward finance professionals, this book will equip you with the knowledge and tools to harness the power of Large Language Models (LLMs), ensuring you stay ahead in an increasingly AI-driven industry. Highlighting the benefits and challenges of LLMs in financial contexts, the book starts with the necessary infrastructure setup, covering both hardware and software requirements. It offers a balanced discussion on cloud versus on-premises solutions, enabling you to make informed decisions based on their specific needs. Training and fine-tuning LLMs are critical components of effective deployment, and this book offers best practices, from data preparation to advanced fine-tuning techniques. It also delves into deployment strategies, with practical advice on building deployment pipelines, monitoring performance, and optimizing operations. Ensuring data privacy and security is paramount in finance, so you’ll take a close look at maintaining compliance with regulations while safeguarding sensitive information. You’ll also examine the integration of LLMs into existing financial systems, with real-world case studies and strategies for API development and real-time data processing. Monitoring and maintenance are crucial for long-term success, and the book outlines how to manage performance metrics, handle model drift, and ensure regular updates. Large Language Models Ops for Finance is your essential guide to discovering the transformative potential of LLMs in the finance industry. What You Will Learn ● Review LLMs and their applications in finance. ● Set up the infrastructure for training and deploying LLMs. ● Apply best practices for fine-tuning and maintaining LLMs. ● Employ techniques for integrating LLMs into existing financial systems Who This Book Is For AI and ML engineers, data scientists, and finance professionals interested in implementing and managing large language models within the finance industry. Chapter 1: Introduction to Large Language Models in Finance.- Chapter 2: Infrastructure Setup for LLMs.- Chapter 3: Training and Fine-Tuning LLMs.- Chapter 4: Deployment Strategies for LLMs.- Chapter 5: Ensuring Data Privacy and Security.- Chapter 6: Integrating LLMs into Financial Systems.- Chapter 7: Monitoring and Maintenance of LLMs.- Chapter 8: Future Trends in LLM Ops for Finance.
Mastering LangChain
This book provides a comprehensive exploration of LangChain, empowering you to effectively harness large language models (LLMs) for Gen AI applications. It focuses on practical implementation and techniques, making it a valuable resource for learning LangChain. The book starts with foundational topics such as environment setup and building basic chains, then delves into key components such as prompt templates, tool integration, and memory management. You will also explore practical topics such as output parsing, embedding models, and developing chatbots and retrieval-augmented generation (RAG) systems. Additional chapters focus on integrating LangChain with other AI tools and deploying applications while emphasizing best practices for AI ethics and performance. By the time you finish this book, you’ll have the know-how to confidently build Generative AI solutions using LangChain. Whether you're exploring practical applications or curious about the latest trends, this guide gives you the tools and insights to solve real-world AI problems. You’ll be ready to design smart, data-driven applications—and rethink how you approach Generative AI. What You Will Learn Understand the core ideas, architecture, and essential features of the LangChain framework Create advanced LLM-driven workflows and applications that address real-world challenges Develop robust Retrieval-Augmented Generation (RAG) systems using LangChain, vector databases, and proven best practices for retrieving and generating high-quality responses Who This Book Is For Data scientists and AI enthusiasts with basic Python skills who want to use LangChain for advanced development, and Python developers interested in building data-responsive applications with large language models (LLMs) Chapter 1: Introduction to LangChain.- Chapter 2: Core Components of LangChain.- Chapter 3: Advanced Components and Integrations.- Chapter 4: Building Chatbots.- Chapter 5: Building Retrieval-Augmented Generation (RAG) Systems.- Chapter 6: LangServe, LangSmith, and LangGraph: Deploying, Optimizing, and Designing Language Model Workflows.- Chapter 7: LangChain and NLP.- Chapter 8: Building AI Agents with LangGraph.- Chapter 9: LangChain Framework Integration.- Chapter 10: Deploying LangChain Applications.- Chapter 11: Best Practices and Practical Aspects.
Nanobiotechnology
Explore the integration of nanotechnology with artificial intelligence (AI) and the Internet of Things (IoT), focusing on advancements, applications, and future prospects in the field. This book highlights the fusion of cutting-edge technologies with biological and nanomaterials, emphasizing their role in transforming industries such as medicine, environmental science, and manufacturing. This book delves into the fundamentals of Nano-Biotechnology, starting with its historical evolution and foundational concepts. It explores the various types of nanomaterials, such as quantum dots, polymeric nanoparticles, and metal nanoparticles, detailing their properties and applications in fields such as drug delivery, diagnostics, and catalysis. Cellular nanostructures, biomolecular motors, and bio-inspired nanostructures are discussed, alongside methods for nanomaterial synthesis, including physical, chemical, and biological approaches. A focus on AI and IoT integration is woven throughout, highlighting their roles in optimizing nanomaterial properties, synthesis processes, and applications. The book further explores nanomaterial characterization techniques, nanomedicine, water remediation, MEMS/NEMS, and nanocatalysis, while also addressing crucial topics such as environmental impact, ecotoxicology, and regulatory frameworks. Each chapter presents advanced technological insights, from nanobiocatalysts to thin films and self-assembled nanostructures, all within the context of AI and IoT-driven advancements. You will gain a deep understanding of the interdisciplinary nature of Nano-Biotechnology, the implications of AI and IoT integration, and the ethical, environmental, and societal considerations shaping the future of this rapidly evolving field. The book offers valuable perspectives on emerging trends and equips readers with insights necessary for both academic and practical applications of Nano-Biotechnology. You Will Understand the key concepts, classification, properties, and applications of various nanomaterials in fields like medicine, diagnostics, and catalysis Gain insights into the physical, chemical, and biological methods of nanomaterial synthesis as well as advanced techniques Discover how Nano-Biotechnology is being applied to multiple sectors and MEMS/NEMS systems, and learn about the challenges and future trends Who Is This Book For Readers with a basic to intermediate understanding of nanotechnology, biotechnology, or related fields will benefit from this book. A general familiarity with concepts like AI, IoT, and their applications in scientific disciplines will also be helpful. Chapter 1: Introduction to Nano-Biotechnology.- Chapter 2: Types of Nanomaterials and Their Properties.- Chapter 3: Cellular Nanostructures and Biomolecular Motors.- Chapter 4: Synthesis of Nanomaterials.- Chapter 5: Characterization of Nanomaterials.- Chapter 6: Thin Films and Colloidal Nanostructures.- Chapter 7: Self-Assembly and Nanovesicles.- Chapter 8: Nanoparticles for Drug Delivery.- Chapter 9: Nanoparticles for Diagnostics and Imaging.- Chapter 10: Nanobiocatalysts and Their Applications.- Chapter 11: Environmental and Health Impacts of Nanomaterials.- Chapter 12: Ecotoxicology and Life Cycle Assessment.- Chapter 13: Nanomaterials in Catalysis.- Chapter 14: Nanotechnology in Medicine.- Chapter 15: Nanotechnology in Food Science.- Chapter 16: Nanotechnology for Water Remediation and Purification.- Chapter 17: MEMS and NEMS Based on Nanomaterials.- Chapter 18: Safety and Regulation of Nanomaterials.- Chapter 19: Genotoxicity and Cytotoxicity of Nanomaterials.- Chapter 20: Future Directions in Nano-Biotechnology.
GovOps with Microsoft Power Platform and Copilot
In an era of tightening budgets and rising citizen expectations, government agencies must modernize or risk obsolescence. This book provides a comprehensive, hands‑on roadmap for public sector leaders, architects, and developers to harness Microsoft Power Platform’s low‑code and AI capabilities with Power Apps, Power Automate, Power BI, Power Pages, AI Builder, Copilot, and Dataverse. This book lays out the case for low‑code modernization, demonstrates how to assess organizational readiness, and introduces governance and CoE best practices. Readers will walk away with repeatable frameworks, proven templates, and scripts to accelerate digital transformation in any government setting to foster transparency, efficiency, and citizen‑first service delivery. What You Will Learn Core Platform Deep Dive: Unpacks each Power Platform component with architecture patterns, step‑by‑step tutorials, and design guidelines using official Microsoft icons. Sector‑Specific Use Cases: Shares rich, real‑world examples from licensing and permitting to emergency response coordination, complete with workflows, code samples, and architecture diagrams. Advanced AI & Copilot Integrations: Shows how to train custom AI models, implement Copilot–powered natural‑language generation, and embed responsible AI with human‑in‑the‑loop designs. Operational Excellence, ALM & the Road Ahead: Covers CI/CD pipelines, environment management, security/DLP policy enforcement, accessibility, and next‑gen Copilot trends. Who This Book is For This book is for IT leaders, solution architects, citizen developers, line‑of‑business analysts, and public sector project managers looking to modernize government services. Readers should have some familiarity with Microsoft 365 or basic low-code. Chapter 1: Introduction to Government Modernization.- Chapter 2: Overview of Microsoft Power Platform.- Chapter 3: Planning a Government Low‑Code Strategy.- Chapter 4: Building End‑to‑End Solutions.- Chapter 5: Integrating AI and Co-Pilot.- Chapter 6: Deployment & Governance.- Chapter 7: Facilitating Government Modernization through Use Cases.- Chapter 8: Best Practices & Frameworks.- Chapter 9: The Road Ahead.- Chapter 10: Resources & Templates.- Chapter 11: Azure AI + AI Builder High-Level AI Model Development.- Chapter 12: Copilot Studio In-Depth Tutorial – Bots, Prompts & Custom Skills.- Chapter 13: Low-Code + Pro-Code Fusion – When to Extend with Azure Functions.- Chapter 14: Secure External API Integrations in Government Applications.- Chapter 15: Data Governance & Sovereignty with Dataverse and Azure.- Chapter 16: Making Power Platform Solutions Run Better.- Chapter 17: Monitoring & Logging with Azure Monitor and Power Platform Admin Center.- Chapter 18: Disaster Recovery & Business Continuity Planning.- Chapter 19: The Future of Digital Government – Trends to Watch.- Chapter 20: Developing a Culture of Low-Code Innovation in Government Sector.
Integration of Federated Learning and Blockchain for Smart Cities
Stay ahead of the curve in urban innovation with this essential guide that provides a comprehensive roadmap for federated learning and blockchain to build secure, intelligent, and efficient smart city ecosystems. As cities grow smarter, the demand for secure, decentralized, and privacy-preserving technologies is greater than ever. This book explores how federated learning and blockchain are transforming urban landscapes by enabling intelligent, secure, and efficient systems. By combining the power of decentralized machine learning with the transparency and security of blockchain, this book provides a roadmap for tackling challenges in urban mobility, energy management, public safety, and healthcare, delving into theoretical frameworks, architectural designs, security considerations, and real-world case studies to illustrate the impact of these technologies. This book serves as a comprehensive guide for researchers, industry professionals, and policymakers seeking to understand, implement, and innovate within smart city ecosystems. Readers will find the volume: Explores the synergy between federated learning and blockchain, offering cutting-edge solutions for smart city challenges;Addresses critical issues of data privacy, decentralized AI, and secure digital infrastructure in urban environments;Features practical case studies on smart transportation, energy management, healthcare, and governance;Provides a forward-looking perspective on how emerging technologies will shape the cities of tomorrow. Audience Academics, researchers, industry professionals, and policymakers working in the fields of artificial intelligence, machine learning, blockchain, IoT, cybersecurity, smart city planning, and urban technology development. Krishna Kant Singh, PhD is the Director at the Delhi Technical Campus, Greater Noida, India. He has authored 25 books and over 160 research papers in international journals. He is an associate editor of IEEE Transactions on Computational Social Systems, and Senior editor of IEEE Access. His research interests include machine vision, remote sensing, deep learning, and generative AI. Akansha Singh, PhD is a professor in the School of Computer Science, Engineering, and Technology at Bennett University, Greater Noida, India, with over 18 years of teaching and research experience. She has published over 100 research papers and authored over 30 books in advanced areas of computer science. Her expertise spans image processing, deep learning, machine learning, remote sensing, and IoT, with a strong focus on AI-driven solutions for healthcare and environmental sustainability. Mahesh T.R., PhD is the Program Head of the Department of Computer Science and Engineering in the School of Engineering and Technology, at Jain (Deemed-to-be University), Bengaluru, India. He has published over 180 research articles in international and edited several books. His research interests include image processing, machine learning, deep learning, artificial intelligence, IoT, and data science.
The Game Designer's Workbook
Praise for The GAME DESIGNER’S WORKBOOK “This book is a FANTASTIC way to start thinking like a game designer by solving the real problems that professional designers tackle every day. I love it!” —Jesse Schell, author of The Art of Game Design: A Book of Lenses “The Game Designer’s Workbook is a welcome addition to the small collection of books that address game design in meaningful ways. It is an indispensable reminder that while game design is hard work, it should also be joyful. It invites readers to discover core concepts through playful discovery, and will be a valuable resource for anyone teaching game design. My only regret is that this wasn’t available when I set out teaching game design. My students would have benefited from its insights.” —Scot Osterweil, Game Designer, MIT & Learning Games Network “At least as good a game design education as you can get in the average university program, with significantly less debt.” —Anna Anthropy, Award-Winning Game Designer, Educator, and Co-Author of A Game Design Vocabulary “The singular achievement of The Game Designer’s Workbook is that Lang and Lockhart dive deeply into the mysteries of games, while rendering them utterly approachable. A must-have living sketchbook for game creators of all ages, The Game Designer’s Workbook is valuable for aspiring young designers, university students, and working professionals alike. The fundamental insights of game design — how systems work, how to communicate stories, how to prototype and test ideas — are relevant to just about any creative person working today. I look forward to playing through this book. You should too.” —Eric Zimmerman, Arts Professor at the NYU Game Center, Co-Author of Rules of Play and Author of The Rules We Break Hands-on tools, exercises, walkthroughs, and resources for new game designers. All you need is a pencil! In The Game Designer's Workbook, two experienced game designers, Bobby Lockhart and Eric Lang, walk you through design tips and exercises you can apply immediately to take your next game to the next level. The authors draw on decades of combined experience in game design, helping you ideate, storyboard, create fun and challenging levels, and more. The book is structured as a set of practical exercises and examples to give budding game designers hands-on experience with the nuts and bolts of designing games. Equipped only with a pencil, you can level-up your skills in critical areas of game design. While you're free to use a computer, a pair of dice, or to team up with a group of friends, The Game Designer's Workbook lets you develop your skills whenever you've got something to write with and 10 minutes of spare time. The book includes reflection sections that allow you to think deeply about your future game design practice, challenges that prompt you to modify and improve an existing game, break down games into their component parts to better understand their inner workings, and discussions of concepts common to all sorts of games. You'll also find: A link to a companion website that includes additional resources, like printable resources, extra dot grid pages, papercraft exercises, random number generators, and scaffolded work pagesExplanations of cross-disciplinary skills useful for any aspiring game designersStand-alone chapters you can tackle beginning-to-end or one at a time The Game Designer's Workbook is an essential toolkit for aspiring and beginning game designers, as well as anyone interested in games and game design. BOBBY LOCKHART is a game designer specializing in learning games with more than 10 years’ experience designing games for all audiences, including children and adult professionals undertaking career training. ERIC LANG is a human-centered designer who makes whimsical, award-winning, educational video games played by millions of kids around the world. He is the Art Director at the Field Day Lab based out of the University of Wisconsin-Madison.
The AI Product Playbook
A comprehensive guide for aspiring and practicing AI product managers The AI Product Playbook: Strategies, Skills, and Frameworks for the AI-Driven Product Manager, by Dr. Marily Nika and Diego Granados, is a practical guide designed to empower product managers to effectively build, launch, and manage successful AI-powered products. This playbook bridges the gap between complex AI concepts and real-world product management, offering actionable frameworks and strategic insights tailored to non-technical professionals. Drawing on their extensive industry experience, the authors guide you in understanding the three essential AI Product Manager personas: AI Experiences PM, AI Builder PM, and AI-Enhanced PM. This framework empowers you to identify your own strengths, focus your skill development, and chart a clear career path in the evolving AI job market. The AI Product Playbook demystifies the full spectrum of AI product development, with a special focus on today’s most transformative technologies like Generative AI and Large Language Models (LLMs). Alongside this modern focus, you will build a strong foundation in the core paradigms of traditional machine learning, understand the complete data science lifecycle, and grasp the operational realities of MLOps. The book also provides actionable frameworks for ethical AI implementation, grounding these concepts in real-world case studies and practical examples. An essential, strategic guide for aspiring and experienced product managers, The AI Product Playbook delivers an effective roadmap to AI-driven product management and career advancement in the AI era. A comprehensive guide for aspiring and current AI product managers The AI Product Playbook: Strategies, Skills, and Frameworks for the AI-Driven Product Manager, by Dr. Marily Nika and Diego Granados, is a practical resource designed to empower product managers to effectively build, launch, and manage successful AI-powered products. This playbook bridges the gap between artificial intelligence theory and real-world product management, offering actionable learnings tailored to non-technical professionals. Drawing from extensive industry experience, Dr. Nika and Granados introduce the three essential AI product manager roles: AI Experiences PM, AI Builder PM, and AI-Enhanced PM. They offer guidance on developing skills crucial for each role and navigating common challenges in the workplace. Readers will also find valuable strategies for career growth, lifelong learning, and crafting a distinctive AI portfolio. Inside the book: Practical frameworks for discovering AI opportunities and aligning AI capabilities with business goalsA deep technical dive with clear explanations of foundational AI and machine learning concepts, including supervised learning, unsupervised learning, reinforcement learning, and generative AIGuidelines for ethical AI implementation, addressing bias, fairness, and compliance with AI regulationsStrategies for effective collaboration with cross-functional teams and enhancing productivity through AIInteractive exercises, action plans, checklists, templates, and quizzes designed to reinforce learning and build real-world skills Essential reading for aspiring and experienced product managers alike, The AI Product Playbook provides a roadmap to mastering AI-driven product management and advancing your career in the dynamic field of artificial intelligence. Dr. Marily Nika is an award-winning GenAI Product Leader at Google and one of the world's foremost AI educators, with over 13 years of experience building AI products at Google and Meta. She holds a PhD in machine learning and is an author, TED AI speaker, Harvard Business School fellow and co-founder of the AI Product Hub (www.aiproduct.com) which offers AI product management certifications. Diego Granados is a Product Leader with more than 6 years of experience bringing AI products to life in top tech companies in Silicon Valley. He holds an MBA from Duke University and an M.S. in C.S. focused on AI & ML from Georgia Tech and is co-founder of the AI Product Hub (www.aiproduct.com) which offers AI product management certifications.
Adaptive Artificial Intelligence
Master the next frontier of technology with this book, which provides an in-depth guide to adaptive artificial intelligence and its ability to create flexible, self-governed systems in dynamic industries. Adaptive artificial intelligence represents a significant advancement in the development of AI systems, particularly within various industries that require robust, flexible, and responsive technologies. Unlike traditional AI, which operates based on pre-defined models and static data, adaptive AI is designed to learn and evolve in real time, making it particularly valuable in dynamic and unpredictable environments. This capability is increasingly important in disciplines such as autonomous systems, healthcare, finance, and industrial automation, where the ability to adapt to new information and changing conditions is crucial. In industry development, adaptive AI drives innovation by enabling systems that can continuously improve their performance and decision-making processes without the need for constant human intervention. This leads to more efficient operations, reduced downtime, and enhanced outcomes across sectors. As industries increasingly rely on AI for critical functions, the adaptive capability of these systems becomes a cornerstone for achieving higher levels of automation, reliability, and intelligence in technological solutions. Readers will find the book: Introduces the emerging concept of adaptive artificial intelligence;Explores the many applications of adaptive artificial intelligence across various industries;Provides comprehensive coverage of reinforcement learning for different domains. Audience Research scholars, IT professionals, engineering students, network administrators, artificial intelligence and deep learning experts, and government research agencies looking to innovate with the power of artificial intelligence. P. Pavan Kumar, PhD is an associate professor in the Department of Artificial Intelligence and Data Science at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India. He has published more than 20 scholarly peer-reviewed research articles in international journals and two Indian patents. His research interests include real-time systems, multi-core systems, high-performance systems, and computer vision. Grandhi Suresh Kumar, PhD is an associate professor and Associate Dean of Academics in the School of Science and Technology at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India with more than ten years of experience. He has published one authored book, one edited book, one book chapter, and more than 15 articles. His research interests include intelligent manufacturing, robotics, sustainable energy solutions, CO2 capture, and applications of AI in mechanical engineering. Ajay Kumar Jena, PhD is an assistant professor and Associate Dean in the School of Computer Engineering at the Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India. He has published three books, seven book chapters, and 61 research papers in various international journals and conferences. His research interests include blockchain, object-oriented software testing, software engineering, data science, soft computing, and machine learning. Sandeep Kumar Panda, PhD is a professor and an Associate Dean in the School of Science and Technology at the ICFAI Foundation for Higher Education, Hyderabad, Telangana, India. He has published six books, several book chapters, and 80 articles in international journals and conferences. His research interests include blockchain technology, W3, metaverse, the Internet of Things, AI, and cloud computing. S. Balamurugan, PhD is the Director of Research, iRCS, an Indian technological research and consulting firm. He has published more than 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of research experience using various cutting-edge technologies, he provides expert guidance in technology forecasting and decision-making for leading companies and startups.
Protecting Artificial Intelligence-generated Works in Indonesia
This book examines the legal challenges posed by generative artificial intelligence (AI) in copyright law, focusing on Indonesia while using the European Union (EU) as a benchmark. It explores whether AI-generated works should qualify for copyright protection, how rights over these works should be allocated, and which stakeholders should be recognised in the process. By addressing these critical issues, the book provides a framework for balancing legal protection with public interests, offering insights for policymakers, legal scholars, and intellectual property practitioners. Adopting a comparative and socio-legal approach, this book analyses Indonesia’s evolving copyright landscape alongside the EU’s response to AI-generated works. While Indonesia prioritizes AI development, its copyright law remains rooted in human authorship, creating legal uncertainties for AI-generated works, despite the significant human contributions involved. This book offers a novel perspective on how middle-income countries can adapt their copyright systems in response to technological advancements. To address the gap in existing copyright law, potential protection models, including sui generis rights and neighbouring rights, are examined. These alternatives advocate for a balanced approach that fosters innovation while safeguarding human contributors. Through the comparative analysis and policy-driven recommendations, the book is an essential resource for academics, legal professionals, and policymakers seeking to navigate the evolving intersection of AI and copyright law. Laurensia Andrini is a Lecturer at the Business Law Department, Faculty of Law of the Universitas Gadjah Mada in Yogyakarta, Indonesia.
Modern CSS
Come on a tour of modern CSS. This example-driven book demonstrates the concepts by showing code examples, screenshots, and diagrams to help clearly communicate the information. You'll start with the very basics of CSS: box model, colors, selectors and combinators, and specificity. Then gradually move through more intermediate topics - styling text, positioning, Z-index and stacking contexts, gradients, borders, and then to more advanced topics such as transforms, transitions, animations, flexbox, and CSS grid. There is a lot of discussion about how hard CSS is, and how intimidated some people are by it, but it doesn’t have to be this way. Modern CSS uses a logical and understandable approach to break down and clearly explain the ins and outs of CSS. This new edition has been fully updated keeping in mind the changes that CSS has undergone in the last four years and the new features and APIs that have been introduced. The chapter on CSS grids has been updated extensively and now includes a section on CSS subgrids. The book will guide you through recent topics such as nested CSS rules, the :is and :has pseudo-classes, scroll-driven animations, container queries, and more. What You'll Learn: Work with the syntax of CSS selectors and calculate specificityUse styling techniques, fonts and text stylingReview custom properties (variables)Explore the different ways an element can be transformedUse animating elements with CSS transitions Position elements using Flexbox layoutUnderstand the basics of responsive design Who This Book Is For Anyone who has some experience with HTML, and some CSS, but might not be familiar with some of the newer concepts like flexbox or grid. Also, those looking for a refresher in those areas.
The Microsoft AI Human Resources Handbook
The world of HR is rapidly transforming, and Microsoft technologies are leading the charge. This book equips both HR professionals and IT specialists with a comprehensive guide to implementing and utilizing the Microsoft HR tech stack. We'll delve into the core solution, Dynamics 365 Human Resources, exploring its capabilities, and how to leverage it with Copilot. The book goes beyond Dynamics 365, exploring the powerful tools within the Microsoft 365 suite, Power Platform (apps, bots, reports, and automations), Microsoft Teams for seamless collaboration, and Viva Learning for fostering a culture of continuous learning. Additionally, we'll touch upon the strategic integration of LinkedIn for talent sourcing and employer branding. What Readers Will Learn HR Professionals: HR Solution Architecture: Understand the core components of the Microsoft HR tech stack and how they work together to support HR processes.Implementation Strategies: Learn best practices for implementing Microsoft HR solutions, including configuration, data migration, and user adoption strategies.In-Depth Knowledge of Specific Products: Gain expertise in utilizing Dynamics 365 Human Resources for talent management, performance management, and more.Leveraging Power Platform: Develop basic skills in building automated workflows, reports, and dashboards within Power Platform to enhance HR processes.Optimizing Communication & Collaboration: Learn how to leverage Microsoft Teams and Viva Learning to foster a more engaged and connected workforce.Strategic Use of LinkedIn: Understand how to integrate LinkedIn with Microsoft HR solutions for effective talent sourcing and employer branding. IT Professionals: Implementation & Management: Learn how to install, configure, and manage Microsoft HR solutions, including security and access controls.System Integration: Gain skills in integrating Microsoft HR solutions with existing HRIS systems and other enterprise applications.Data Management & Security: Understand best practices for data security, governance, and compliance within the Microsoft HR tech stack.Supporting HR Professionals: Gain insights into HR workflows and how to effectively support HR users in utilizing the solutions.Customization & Automation: Learn how to customize Microsoft HR solutions using Power Platform to meet specific organizational needs.
Low-Code Development with Xomega.NET
Quickly build robust, data-driven .NET applications in Visual Studio using Xomega, an extensible low-code platform. Use simple but flexible Xomega model structures to model your application domain entities, services, UI objects, and views. Instead of spending your time writing boilerplate plumbing code, this platform enables you to stay focused on big-picture issues like your business domain and the structure of your application. Once you define your application models, Xomega allows you to generate all layers of your application, producing high-quality, customizable source code organized as per the best-practice architectures for multi-tier, enterprise-grade applications. Your application will leverage our powerful open-source Xomega Framework, which helps you write clean, reusable, and testable code. Coupled with code generation, it will guarantee consistent behavior and look-and-feel across your entire app, which can also reduce maintenance costs later on. What You Will Learn Create a Blazor solution pre-configured for the selected architecture and frameworks using industry best practices.Import initial domain model from a database and enrich it with static data, services and presentation models.Iteratively model services and UI views for a powerful list screen with flexible search criteria.Iteratively model CRUD services and presentation for a complex full-fledged details screen.Continuously generate application code from the models for all layers and add custom code as needed.Implement password authentication and multi-layer claims-based security for accessing app data and functionality. Who This Book Is For This book is for .NET developers who are looking to quickly and efficiently build .NET apps using low code.
Administering Microsoft Azure SQL Solutions
Ace the DP-300 Exam with this essential study companion, chock-full of insights and tips you cannot find online. This book will help you build a comprehensive understanding of Azure SQL systems and their role in supporting business solutions, and it will equip you with the mental models and technical knowledge needed to confidently answer exam questions. Structured to align with Microsoft’s published study guide, the book spans five major sections that correspond to the skills measured by the exam, covering topics vital to modern cloud operations and including HA/DR, security, compliance, performance, and scalability. You’ll also learn about the ways cloud operations have changed the focus of operating database systems from task execution to platform configuration—and how to configure your data platforms to meet this new reality. By the end of this book, you’ll be prepared to navigate exam scenarios with finesse, pass the exam with confidence, and advance in your career with a solid foundation of knowledge. What You Will Learn Maximize your ability to benefit from the online learning tools for Exam DP-300Gain depth and context for Azure SQL technical solutions relevant to Exam DP-300Boost your confidence in Azure SQL Database skillsExtend your on-premises SQL Server skill set into the Azure SQL cloudEnhance your overall understanding of Azure SQL administration and operationsDevelop your Azure SQL skill set to increase your value as an employee or contractorAdopt a new mindset for cloud-based solutions versus on-premises solutions Who This Book Is For Anyone planning to take the DP-300: Administering Microsoft Azure SQL Solutions exam, and those who wish to understand Azure SQL and how to successfully migrate and manage SQL solutions using all Azure SQL Technologies
Unlocking dbt
Master the art of data transformation with the second edition of this trusted guide to dbt. Building on the foundation of the first edition, this updated volume offers a deeper, more comprehensive exploration of dbt’s capabilities—whether you're new to the tool or looking to sharpen your skills. It dives into the latest features and techniques, equipping you with the tools to create scalable, maintainable, and production-ready data transformation pipelines. Unlocking dbt, Second Edition introduces key advancements, including the semantic layer, which allows you to define and manage metrics at scale, and dbt Mesh, empowering organizations to orchestrate decentralized data workflows with confidence. You’ll also explore more advanced testing capabilities, expanded CI/CD and deployment strategies, and enhancements in documentation—such as the newly introduced dbt Catalog. As in the first edition, you’ll learn how to harness dbt’s power to transform raw data into actionable insights, while incorporating software engineering best practices like code reusability, version control, and automated testing. From configuring projects with the dbt Platform or open source dbt to mastering advanced transformations using SQL and Jinja, this book provides everything you need to tackle real-world challenges effectively. What You Will Learn Understand dbt and its role in the modern data stackSet up projects using both the cloud-hosted dbt Platform and open source projectConnect dbt projects to cloud data warehousesBuild scalable models in SQL and PythonConfigure development, testing, and production environmentsCapture reusable logic with Jinja macrosIncorporate version control with your data transformation codeSeamlessly connect your projects using dbt MeshBuild and manage a semantic layer using dbtDeploy dbt using CI/CD best practices Who This Book Is For Current and aspiring data professionals, including architects, developers, analysts, engineers, data scientists, and consultants who are beginning the journey of using dbt as part of their data pipeline’s transformation layer. Readers should have a foundational knowledge of writing basic SQL statements, development best practices, and working with data in an analytical context such as a data warehouse.
Mastering PostgreSQL Administration
This book is your one-stop resource on PostgreSQL system architecture, installation, management, maintenance, and migration. It will help you address the critical needs driving successful database management today: reliability and availability, performance and scalability, security and compliance, cost-effectiveness and flexibility, disaster recovery, and real-time analytics—all in one volume. Each topic in the book is thoroughly explained by industry experts and includes step-by-step instructions for configuring the features, a discussion of common issues and their solutions, and an exploration of real-world scenarios and case studies that illustrate how concepts work in practice. You won't find the book's comprehensive coverage of advanced topics, including migration from Oracle to PostgreSQL, heterogeneous replication, and backup & recovery, in one place—online or anywhere else. What You Will Learn Install PostgreSQL using source code and yum installationBack up and recoverMigrate from Oracle database to PostgreSQL using ora2pg utilityReplicate from PostgreSQL to Oracle database and vice versa using Oracle GoldenGateMonitor using Grafana, PGAdmin, and command line toolsMaintain with VACUUM, REINDEX, etc. Who This Book Is For Intermediate and advanced PostgreSQL users, including PostgreSQL administrators, architects, developers, analysts, disaster recovery system engineers, high availability engineers, and migration engineers
Einführung in die Wirtschaftsinformatik
Das Buch gibt eine fundierte und praxisbezogene Einführung in das Gebiet der Wirtschaftsinformatik. Aufbauend auf den bewährten Vorgängerauflagen von Stahlknecht und Hasenkamp wurde die 14. Auflage überarbeitet, strukturell weiterentwickelt und aktualisiert. Die Schwerpunkte umfassen u.a. generative KI, rechtliche Neuerungen für KI, Anwendungsentwicklung mit Low-Code/No-Code, Rechnernetze und Computing. Zusatznutzen: Laden Sie die Springer Nature Flashcards-App kostenlos herunter und überprüfen Sie Ihr Wissen.