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Generative AI and Digital Forensics
In today’s world, cybersecurity attacks and security breaches are becoming the norm. Unfortunately, we are not immune to it, and any individual and entity is at dire risk. The best and only thing that we can do is to mitigate the risks as much as much as possible so that they do not happen at all. But even when a security breach does indeed happen, the immediate reaction is to contain it so that it does not penetrate further into the IT/Network Infrastructure. From there, mission-critical processes need to be restored, until the business can resume a normal state of operations, like it was before the security breach.But another key step here is to investigate how and why the security breach happened in the first place. The best to do this is through what is known as “Digital Forensics”. This is where specially trained Digital Forensics Investigators collect and comb through every piece of evidence to determine this. Eventually, the goal is then to use this evidence in a court of law so the cyberattacker can be made to answer to their crime and eventually be brought to justice.However, the area of digital forensics is a large one, and many topics around it can be covered. Also, generative AI is being used to not only help in the analysis of the evidence, but also to help automate the Digital Forensics software packages that are available today. Therefore, in this book, the following is covered:Examples of security breaches, and overview into Digital ForensicsHow Digital Forensics can be used to investigate the loss or theft of dataAn introduction to the SQL Server DatabaseA review of the SQL Injection AttackHow generative AI can be used in Digital Forensics
R 1,703.46
R 855.00
R 432.00
Impacts of Generative AI on the Future of Research and Education
Artificial Intelligence (AI), particularly Generative Pretrained Transformer (GPT) models, has become one of the most influential and transformative technologies of the 21st century. They have shown immense potential to revolutionize research and education by enabling more efficient data analysis, generating high-quality content, and facilitating personalized learning experiences. As AI continues to evolve, its integration into these fields promises to enhance productivity, foster innovation, and democratize access to knowledge on a global scale. Impacts of Generative AI on the Future of Research and Education provides an in-depth understanding of the implication of AI and GPT in the context of research and education. It comprehensively analyzes the potential, challenges, and ethical considerations of AI integration in these sectors. Covering topics such as academic integrity, ethics, and special education, this book is an excellent resource for educators, researchers, academicians, policymakers, administrators, and more.
R 10,487.61
R 305.00
Generative AI: Innovations and Applications Across Industries
This book explores Generative AI, covering its transformative applications and innovative technologies. Each chapter meticulously examines Generative AI's impact across diverse domains, including creative fields, healthcare, education, entertainment, finance, and more.The book begins by establishing the foundation for comprehending Generative AI, presenting fundamental concepts, tracing its historical progression, and analyzing key technologies like deep neural networks (DNNs), variational autoencoders (VAEs), and generative adversarial networks (GANs) in Chapter 1. In Chapter 2 we explore Generative AI's role in revolutionizing creative domains like writing, visual arts, and music composition. Chapter 3 delves into its impact on business and marketing, reshaping strategies and operations through AI-generated content and personalized experiences. In Chapter 4, we investigate Generative AI's influence on healthcare, accelerating drug discovery, personalized medicine, and medical imaging. Education is spotlighted in Chapter 5, showcasing Generative AI's contributions to personalized learning and interactive educational materials. Chapter 6 examines its impact on entertainment and media, while Chapters 7 through 11 delve into legal, financial, industrial, and environmental applications, addressing ethical considerations and future trends. Finally, Chapter 12 concludes with case studies and expert insights, offering readers a comprehensive understanding of Generative AI's potential and societal implications. Join us on this enlightening journey through the diverse landscapes of Generative AI, where innovation knows no bounds and the future is limited only by our imagination.In the end, readers will gain a comprehensive understanding of the transformative potential and societal implications of Generative AI.What you will learn:What are the foundational concepts and technological advancements behind Generative AI.What are large language modelsUnderstand Generative AI's role in reshaping business landscapes.What is the future of Generative AI and its potential impact. Who this book is for:AI Professionals, machine learning engineers and software professionals seeking a comprehensive understanding of Generative AI across various business domains.
R 1,368.00
R 486.00
Generative AI: Techniques, Models and Applications
This book unlocks the full potential of modern AI systems through a meticulously structured exploration of concepts, techniques, and practical applications. This comprehensive book bridges theoretical foundations with real-world implementations, offering readers a unique perspective on the rapidly evolving field of generative technologies. From computational foundations to ethical considerations, the book systematically covers essential topics including foundation models, large-scale architectures, prompt engineering, and practical applications. The content seamlessly integrates complex technical concepts with industry-relevant examples, making it an invaluable resource for researchers, academicians, and practitioners. Distinguished by its balanced approach to theory and practice, this book serves as both a learning tool and reference guide. Readers will benefit from:Clear explanations of advanced concepts.Practical implementation insights.Current industry applications.Ethical framework discussions.Whether you're conducting research, implementing solutions, or exploring the field, this book provides the knowledge necessary to understand and apply generative AI technologies effectively while considering crucial aspects of security, privacy, and fairness.
R 5,910.02
RAG-Driven Generative AI
Minimize AI hallucinations and build accurate, custom generative AI pipelines with RAG using embedded vector databases and integrated human feedbackGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey FeaturesImplement RAG’s traceable outputs, linking each response to its source document to build reliable multimodal conversational agentsDeliver accurate generative AI models in pipelines integrating RAG, real-time human feedback improvements, and knowledge graphsBalance cost and performance between dynamic retrieval datasets and fine-tuning static dataBook DescriptionRAG-Driven Generative AI provides a roadmap for building effective LLM, computer vision, and generative AI systems that balance performance and costs.This book offers a detailed exploration of RAG and how to design, manage, and control multimodal AI pipelines. By connecting outputs to traceable source documents, RAG improves output accuracy and contextual relevance, offering a dynamic approach to managing large volumes of information. This AI book shows you how to build a RAG framework, providing practical knowledge on vector stores, chunking, indexing, and ranking. You’ll discover techniques to optimize your project’s performance and better understand your data, including using adaptive RAG and human feedback to refine retrieval accuracy, balancing RAG with fine-tuning, implementing dynamic RAG to enhance real-time decision-making, and visualizing complex data with knowledge graphs.You’ll be exposed to a hands-on blend of frameworks like LlamaIndex and Deep Lake, vector databases such as Pinecone and Chroma, and models from Hugging Face and OpenAI. By the end of this book, you will have acquired the skills to implement intelligent solutions, keeping you competitive in fields from production to customer service across any project.What you will learnScale RAG pipelines to handle large datasets efficientlyEmploy techniques that minimize hallucinations and ensure accurate responsesImplement indexing techniques to improve AI accuracy with traceable and transparent outputsCustomize and scale RAG-driven generative AI systems across domainsFind out how to use Deep Lake and Pinecone for efficient and fast data retrievalControl and build robust generative AI systems grounded in real-world dataCombine text and image data for richer, more informative AI responsesWho this book is forThis book is ideal for data scientists, AI engineers, machine learning engineers, and MLOps engineers. If you are a solutions architect, software developer, product manager, or project manager looking to enhance the decision-making process of building RAG applications, then you’ll find this book useful.
R 1,433.00
Diffusions in Architecture: Artificial Intelligence and Image Generators
DIFFUSIONS IN ARCHITECTURE A guide to diffusion models and their impact on design, with insight on how this novel artificial intelligence technology may disrupt the industry Diffusions in Architecture: Artificial Intelligence and Image Generators delves into the impact of Generative AI models and their effect on architecture design and aesthetics. The book presents an in-depth analysis of how these new technologies are revolutionizing the field of architecture and changing the way architects approach their work. The architects presented in the book focus on the application of specific AI techniques and tools used in generative design, such as Diffusion models, Dall-E2, Stable Diffusion, and MidJourney. It discusses how these techniques can generate synthetic images that are both realistic and imaginative, creating new possibilities for architectural design and aesthetics. Twenty-two leading designers and theorists offer their insights, providing disciplinary depth by covering the full impact of these learning tools on architecture.
R 1,627.00
R 811.00
R 1,221.00
Generative AI: Current Trends and Applications
This comprehensive volume focuses on the latest advancements in Generative AI, including state-of-the-art techniques and models that are pushing the boundaries of what is possible. It covers recent developments in areas such as Generative AI models, transfer learning and Natural Language Processing (NLP) highlighting their potential to revolutionize content generation and creative applications including OpenAI, LangChain, NLTK and their practical implementations across diverse domains. The volume provides insights into emerging research areas, novel architectures, and innovative approaches in Generative AI, giving searchers a glimpse into the exciting future of the field. The aim is to offer readers a deep understanding of Generative AI and how it can be harnessed to tackle complex real-world challenges.
R 9,534.46
Generative AI and Digital Forensics
In today’s world, cybersecurity attacks and security breaches are becoming the norm. Unfortunately, we are not immune to it, and any individual and entity is at dire risk. The best and only thing that we can do is to mitigate the risks as much as much as possible so that they do not happen at all. But even when a security breach does indeed happen, the immediate reaction is to contain it so that it does not penetrate further into the IT/Network Infrastructure. From there, mission-critical processes need to be restored, until the business can resume a normal state of operations, like it was before the security breach.But another key step here is to investigate how and why the security breach happened in the first place. The best to do this is through what is known as “Digital Forensics”. This is where specially trained Digital Forensics Investigators collect and comb through every piece of evidence to determine this. Eventually, the goal is then to use this evidence in a court of law so the cyberattacker can be made to answer to their crime and eventually be brought to justice.However, the area of digital forensics is a large one, and many topics around it can be covered. Also, generative AI is being used to not only help in the analysis of the evidence, but also to help automate the Digital Forensics software packages that are available today. Therefore, in this book, the following is covered:Examples of security breaches, and overview into Digital ForensicsHow Digital Forensics can be used to investigate the loss or theft of dataAn introduction to the SQL Server DatabaseA review of the SQL Injection AttackHow generative AI can be used in Digital Forensics
R 6,641.53
AI Powered Digital Twins
Build secure, effective digital twins using proven engineering principles and AI foundations AI Powered Digital Twins: A Guide for Humans, Engineers, and Enterprises provides a unified framework for implementing digital twin systems where AI agents reason, act, and remain governed. Hala Nelson lays out a 12-layer engineering architecture spanning raw data ingestion, semantic spine, event, native core, agent reasoning loops, simulation, Zero Trust security, and governance lifecycle. The architecture targets systems that must perform in critical infrastructure rather than demonstrations. The book delivers a human-centered Standard of Care framework alongside real-world case studies from critical infrastructure and system engineering. Readers gain practical guidance on integrating AI, data engineering, asset tagging, knowledge graphs and quantum computing within digital twin environments. Coverage includes accountability frameworks modeled on the rigor of aviation, healthcare, and civil engineering, plus an AI and data strategy designed to translate directly into measurable business value. The book stresses engineering discipline to bridge the gap between AI investment and real-world delivery. The book contains: How AI agents reason, act, and stay governed within digital twins using Zero Trust security and governance controlsA modular architecture for blending physical and virtual worlds while protecting safety across operational technology environmentsAccountability frameworks modeled on aviation, healthcare, and civil engineering that hold AI systems to a standard of careCase studies demonstrating implementation strategies for manufacturing and integrated system engineeringAn AI and data strategy that translates into measurable business value rather than a policy document on a shelf 17 chapters. One architecture. Zero handwaving about security. A must-read for engineers, architects, technical leaders, strategists, and the policymakers who depend on their judgment.
R 711.00
R 916.00
Practical Generative AI with ChatGPT
Transform your professional world with ChatGPT and OpenAI—master prompt design to revolutionize development, marketing, research, and enterprise implementationKey FeaturesTurn ChatGPT into your companion for marketing, research, personal productivity, art and codingLearn prompt engineering techniques that deliver consistent, relevant, and ethical AI-powered resultsBuild custom GPTs and assistants tailored to your specific business needs and workflowsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionPractical Generative AI with ChatGPT is your hands-on guide to unlocking the full potential of ChatGPT. From building AI assistants and mastering prompt engineering to analyzing documents and images and even generating code, this book equips you with the skills to integrate generative AI into your workflow.Written by a technical architect specializing in AI and intelligent applications, this book provides the tools and knowledge you need to streamline tasks, enhance productivity, and create intelligent solutions. You’ll learn how to craft precise prompts, leverage ChatGPT for daily efficiency, and develop custom AI assistants tailored to your needs.The chapters show you how to use ChatGPT’s multimodal capabilities to generate images with DALL·E and even transform images into code. This ChatGPT book goes beyond basic interactions by showing you how to design custom GPTs and integrate OpenAI’s APIs into your applications. You’ll explore how businesses use OpenAI models, from building AI applications, including semantic search, to creating an AI roadmap. Each chapter is packed with practical examples, ensuring you can apply the techniques right away.By the end of this book, you’ll be well equipped to leverage OpenAI's technology for competitive advantage.What you will learnExplore the fundamentals of generative AI and GPT modelsMaster prompt engineering to consistently get relevant and reliable outputs from ChatGPTDevelop marketing strategies and conduct meaningful A/B testing with AI assistanceBoost your coding with code generation, review, and optimizationEnhance research with real-time knowledge miningEnhance your visual creativity with image generation, image understanding, and style transferDesign custom GPTs and assistants tailored to specific business functionsDiscover how enterprises are leveraging large language models for their AI appsWho this book is forThis book is ideal for business professionals, developers, marketers, researchers, and decision-makers who want to leverage AI to enhance productivity. No advanced technical background is required for the foundational sections, making the content accessible to beginners, while later chapters provide depth for technical professionals implementing enterprise solutions. If you’re seeking practical applications of generative AI in business contexts, you’ll find immediate, actionable value in this book.
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R 611.00
Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices
The rapid advancement of generative artificial intelligence (AI) has brought about significant ethical challenges. As machines become more adept at creating human-like content, concerns about misuse, bias, privacy, and accountability have emerged. Without clear guidelines and regulations, there is a risk of unethical use, such as creating deepfake videos or disseminating misinformation, which could have severe societal consequences. Additionally, questions about intellectual property rights and the ownership of AI-generated creations still need to be solved, further complicating the ethical landscape. The book, Generative Artificial Intelligence and Ethics: Standards, Guidelines, and Best Practices , comprehensively solves these ethical challenges. By providing insights into the historical development and key milestones of Generative AI, the book lays a foundation for understanding its complex ethical implications. It examines existing ethical frameworks and proposes new ones tailored to AI's unique characteristics, helping readers apply traditional ethics to AI development and deployment. The book equips readers with the knowledge and tools needed to address these ethical considerations in AI development through in-depth discussions on bias, fairness, privacy, and security. It also explores the role of education in fostering responsible AI practices. It offers practical guidelines for ethical decision-making throughout the AI lifecycle. By promoting ethical awareness and providing actionable solutions, this book empowers readers to navigate the moral challenges of Generative AI, ensuring its responsible and beneficial use for society.
R 8,122.59
Advancements in Human–Agent Teaming Research Infrastructure
As modern military operations become more complex, the need for rapid, coordinated decision-making across multiple domains—air, land, maritime, space, and cyberspace—has never been greater. The U.S. Department of War has identified artificial intelligence (AI) as a critical tool in overcoming these challenges, enabling faster and more efficient responses in high-stakes environments. However, for AI to be effective, it must function well within human teams and organizational structures. This book explores the evolving role of AI in military and defense operations, with a focus on how human-AI teams can be optimized for success.This title offers a practical guide to the next generation of human-AI teaming. Built on the findings of a major research initiative led by the National Academies Board on Human-Systems Integration, this book compiles key insights into the infrastructure, metrics, and conceptual frameworks essential for advancing human-AI collaboration. Readers will gain an understanding of the latest testbed research, validated performance metrics, and novel but critical concepts for evaluating human-AI teams. This book provides a foundation for improving decision-making and coordination in complex operational settings.Advancements in Human Agent Teaming Research Infrastructure: Testbeds, Metrics, and Concepts is an essential resource for researchers, engineers, and policymakers working in AI development, human factors, and defense strategy. It will also benefit military professionals and industry leaders seeking to understand how AI can enhance operational effectiveness while maintaining human oversight and trust.
R 5,165.00
R 678.61
R 912.00
R 1,515.65
EAI International Conference on Computational Intelligence and Generative AI
The book presents the proceedings of the EAI International Conference on Computational Intelligence and Generative AI (ICCIGAI 2024), which took place March 8-9, 2024, in Guntur, India. The book explores the exciting and rapidly evolving field of artificial intelligence, with a specific focus on computational intelligence and generative models. The conference introduces cutting-edge techniques and methodologies that enable machines to simulate human-like intelligence and creativity. Readers can find a comprehensive overview of state-of-the-art AI methods, including neural networks, evolutionary algorithms, deep learning, and generative adversarial networks (GANs). The conference explores real-world applications in a range of areas, including computer vision, natural language processing, and the creation of original content.
R 8,795.47
R 550.00
Hands-On Generative AI with Transformers and Diffusion Models
Learn how to use generative media techniques with AI to create novel images or music in this practical, hands-on guide. Data scientists and software engineers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to your needs, and how to combine existing building blocks to create new models and creative applications in different domains.This book introduces theoretical concepts in an intuitive way, with extensive code samples and illustrations that you can run on services such as Google Colaboratory, Kaggle, or Hugging Face Spaces with minimal setup. You'll learn how to use open source libraries such as Transformers and Diffusers, conduct code exploration, and study several existing projects to help guide your work.Learn the fundamentals of classic and modern generative AI techniquesBuild and customize models that can generate text, images, and soundExplore trade-offs between training from scratch and using large, pretrained modelsCreate models that can modify images by transferring the style of other imagesTweak and bend transformers and diffusion models for creative purposesTrain a model that can write text based on your styleDeploy models as interactive demos or services
R 1,824.00
Applied Generative AI for Beginners
This book provides a deep dive into the world of generative AI, covering everything from the basics of neural networks to the intricacies of large language models like ChatGPT and Google Bard. It serves as a one-stop resource for anyone interested in understanding and applying this transformative technology and is particularly aimed at those just getting started with generative AI.Applied Generative AI for Beginners is structured around detailed chapters that will guide you from foundational knowledge to practical implementation. It starts with an introduction to generative AI and its current landscape, followed by an exploration of how the evolution of neural networks led to the development of large language models. The book then delves into specific architectures like ChatGPT and Google Bard, offering hands-on demonstrations for implementation using tools like Sklearn. You’ll also gain insight into the strategic aspects of implementing generative AI in an enterprise setting, with the authors covering crucial topics such as LLMOps, technology stack selection, and in-context learning. The latter part of the book explores generative AI for images and provides industry-specific use cases, making it a comprehensive guide for practical application in various domains.Whether you're a data scientist looking to implement advanced models, a business leader aiming to leverage AI for enterprise growth, or an academic interested in cutting-edge advancements, this book offers a concise yet thorough guide to mastering generative AI, balancing theoretical knowledge with practical insights.What You Will LearnGain a solid understanding of generative AI, starting from the basics of neural networks and progressing to complex architectures like ChatGPT and Google BardImplement large language models using Sklearn, complete with code examples and best practices for real-world applicationLearn how to integrate LLM’s in enterprises, including aspects like LLMOps and technology stack selectionUnderstand how generative AI can be applied across various industries, from healthcare and marketing to legal compliance through detailed use cases and actionable insightsWho This Book Is ForData scientists, AI practitioners, Researchers and software engineers interested in generative AI and LLMs.
R 1,832.00
Metaverse, Generative AI, and Brain-Computer Interfaces
This compelling exploration delves into the heart of cutting-edge technologies, specifically the Metaverse, Brain-Computer Interfaces (BCI), and generative artificial intelligence (AI). The authors unravel their transformative applications in shaping the future and contemplate how the next generation of virtual environments will manifest, as well as how the digital landscape can be affected.The book encompasses various examples of the Metaverse, brain-computer interfaces, and generative AI across diverse fields, including education, engineering, and medical science. In the dynamic realm of the Metaverse, where virtual realities converge, the book showcases how these innovations can transform the way we learn, interact, and build. Through Brain-Computer Interfaces (BCIs), users can directly interface with technology using neural signals, opening up new avenues for communication and control. Additionally, generative AI algorithms empower us to create immersive virtual environments and generate content with unprecedented creativity.Whether you're a student, educator, or industry professional, this book is your ticket to understanding and harnessing the power of the future. It provides a pathway for those who believe in the limitless possibilities that the Metaverse, BCI, and generative AI can bring to our daily experiences.
R 5,165.00
R 763.00
Google Machine Learning and Generative AI for Solutions Architects
Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectivelyKey FeaturesUnderstand key concepts, from fundamentals through to complex topics, via a methodical approachBuild real-world end-to-end MLOps solutions and generative AI applications on Google CloudGet your hands on a code repository with over 20 hands-on projects for all stages of the ML model development lifecyclePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionNearly all companies nowadays either already use or are trying to incorporate AI/ML into their businesses. While AI/ML research is undoubtedly complex, the building and running of apps that utilize AI/ML effectively is tougher. This book shows you exactly how to design and run AI/ML workloads successfully using years of experience some of the world’s leading tech companies have to offer.You’ll begin by gaining a clear understanding of essential fundamental AI/ML concepts, before moving on to grasp complex topics with the help of examples and hands-on activities. This will help you eventually explore advanced, cutting-edge AI/ML applications that address real-world use cases in today’s market. As you advance, you’ll recognize the common challenges that companies face when implementing AI/ML workloads, and discover industry-proven best practices to overcome these challenges. The chapters also teach you about the vast AI/ML landscape on Google Cloud and how to implement all the steps needed in a typical AI/ML project. You’ll use services such as BigQuery to prepare data; Vertex AI to train, deploy, monitor, and scale models in production; as well as MLOps to automate the entire process.By the end of this book, you will be able to unlock the full potential of Google Cloud's AI/ML offerings.What you will learnBuild solutions with open-source offerings on Google Cloud, such as TensorFlow, PyTorch, and SparkSource, understand, and prepare data for ML workloadsBuild, train, and deploy ML models on Google CloudCreate an effective MLOps strategy and implement MLOps workloads on Google CloudDiscover common challenges in typical AI/ML projects and get solutions from expertsExplore vector databases and their importance in Generative AI applicationsUncover new Gen AI patterns such as Retrieval Augmented Generation (RAG), agents, and agentic workflowsWho this book is forThis book is for aspiring solutions architects looking to design and implement AI/ML solutions on Google Cloud. Although this book is suitable for both beginners and experienced practitioners, basic knowledge of Python and ML concepts is required. The book focuses on how AI/ML is used in the real world on Google Cloud. It briefly covers the basics at the beginning to establish a baseline for you, but it does not go into depth on the underlying mathematical concepts that are readily available in academic material.
R 1,693.00
Deep Swarm and Evolution for Generative Artificial Intelligence
This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the “emergence” concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of “emergence” and to explain the feasibility of AI. To this end, it focuses on human perceptions of “utility.” It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as “novelty search” for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc.
R 8,143.64
Generative AI for Software Developers
Master Generative AI in software development with hands-on guidance, from coding and debugging to testing and deployment, using GitHub Copilot, Amazon Q Developer, and OpenAI APIs to build scalable, AI-powered applicationsKey FeaturesHands-on guidance for mastering AI-powered coding, debugging, and deployment with real-world examplesComprehensive coverage of GenAI concepts, prompt engineering, fine-tuning, and SDLC integrationPractical strategies for architecting and scaling production-ready AI-driven applicationsBook DescriptionGenerative AI for Software Developers is your practical guide to mastering AI-powered development and staying ahead in a fast-changing industry. Through a structured, hands-on approach, this book helps you understand, implement, and optimize Generative AI in modern software engineering. From AI-assisted coding, debugging, and documentation to testing, deployment, and system design, it equips you with the skills to integrate AI seamlessly into your workflows.You’ll work with tools such as GitHub Copilot, Amazon Q Developer, and OpenAI APIs while learning strategies for prompt engineering, fine-tuning, and building scalable AI-powered applications. Featuring real-world use cases, best practices, and expert insights, this book bridges the gap between experimenting with AI and production deployment.Whether you’re an aspiring AI developer, experienced engineer, or solutions architect, this guide gives you the clarity, confidence, and tactical knowledge to thrive in the GenAI-driven future of software development. Armed with these insights, you’ll be ready to build, integrate, and scale intelligent solutions that enhance every stage of the software development lifecycle.What you will learnBuild a secure GenAI application with expert guidanceUnderstand the fundamentals of GenAI and its applications in software engineeringAutomate coding tasks with tools like GitHub Copilot, Amazon Q Developer, and OpenAI APIsApply AI for debugging, testing, documentation, and deployment workflowsGet to grips with prompt engineering and fine-tuning techniques to optimize AI outputsImplement best practices for architecting and scaling AI-powered applicationsBuild end-to-end GenAI projects, moving from experimentation to productionWho this book is forThis book is for software developers, engineers, architects, and tech professionals who want to understand the core concepts of Generative AI and its real-world applications, master AI-driven development workflows to improve efficiency and code quality, and leverage tools like GitHub Copilot, Amazon Q Developer, and OpenAI APIs to automate coding tasks.
R 1,791.00
R 519.00
Innovations for Sustainable and Resilient Infrastructure
This book aims to provide innovative solutions to the various problems faced during the infrastructural development across the globe. The book is highly focused on the following topics, but not limited to: innovative technologies in infrastructure, sustainable materials, smart cities, climate resilient infrastructures, and applications of AI and ML in infrastructure development. The contributions presented in this volume reflect the extensive research and innovative thinking of researchers and practitioners dedicated to shaping the future of sustainable infrastructure. It is anticipated that the knowledge shared through this conference proceedins book will inspire further advancements and collaborative efforts toward building sustainable and resilient infrastructure globally.
R 13,163.39
R 306.00
R 6,869.00
Integrating Generative AI in Education to Achieve Sustainable Development Goals
A new challenge has become present in the field of generative artificial intelligence (AI). The fundamental nature of education, a vital element for advancing the United Nations' Sustainable Development Goals (SDGs), now grapples with the transformative impact of AI technologies. As we stand at this intersection of progress and pedagogy, critical questions surface about the future roles of educators and the integrity of assessment processes. AI’s rapid progression prompts an exploration of the competencies our education systems must cultivate in a world where human and machine intelligence are becoming increasingly interconnected. Against this backdrop of transformative uncertainty, Integrating Generative AI in Education to Achieve Sustainable Development Goals addresses profound challenges and offers promising solutions at the crossroads of AI and education. This book assembles distinguished academics, researchers, and practitioners, forming a collective voice on the intersection of Generative AI and education. The three-part structure dissects the technical aspects of AI-powered innovations in educational design, explores multidisciplinary applications enhancing educational content, and highlights AI-driven solutions to address equality and inclusion concerns within educational systems. The book also underscores the importance of ethical considerations of generative AI to ensure a future where technology serves the broader goals of sustainability and equitable education. This book's primary objective is to serve as a resource for academicians, independent researchers, research scholars, students, scientists, libraries, and industry experts. Through a diverse range of topics, it investigates how generative AI can advance Sustainable Development Goals, making education more accessible, individualized, and effective. By harnessing the power of AI, the book argues, education can act as a catalyst for positive change, empowering individuals and fostering progress toward a sustainable and equitable future. The recommended topics within each part provide a structured framework for deepening the understanding of Generative AI's role in shaping the future of education, making this book a valuable reference for scholars and practitioners alike.
R 8,755.67
R 733.00
