In the rapidly evolving landscape of software development, Quality Assurance (QA) plays a pivotal role in ensuring the reliability and performance of applications. "How to Develop a QA Strategy with Generative AI" provides a comprehensive guide to leveraging cutting-edge Generative AI technologies to enhance your QA processes. This ebook delves into the practical steps required to integrate AI into your existing QA workflows, from selecting the right tools to implementing automated testing and predictive analytics. Through detailed case studies, real-world examples, and step-by-step instructions, you’ll learn how to automate repetitive tasks, improve test accuracy, and significantly reduce testing cycles. Whether you’re a QA manager, software engineer, or tech enthusiast, this guide offers valuable insights into the future of QA. Discover how AI-driven tools can transform your approach to software quality, leading to better products and satisfied customers.
From fundamentals and design patterns to the latest techniques such as generative AI, machine learning and cloud native architecture, gain all you need to be a pro Solutions Architect crafting secure and reliable AWS architecture. Key Features Hits all the key areas -Rajesh Sheth, VP, Elastic Block Store, AWS Offers the knowledge you need to succeed in the evolving landscape of tech architecture - Luis Lopez Soria, Senior Specialist Solutions Architect, Google A valuable resource for enterprise strategists looking to build resilient applications - Cher Simon, Principal Solutions Architect, AWS Book DescriptionMaster the art of solution architecture and excel as a Solutions Architect with the Solutions Architect's Handbook. Authored by seasoned AWS technology leaders Saurabh Shrivastav and Neelanjali Srivastav, this book goes beyond traditional certification guides, offering in-depth insights and advanced techniques to meet the specific needs and challenges of solutions architects today. This edition introduces exciting new features that keep you at the forefront of this evolving field. Large language models, generative AI, and innovations in deep learning are cutting-edge advancements shaping the future of technology. Topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient and secure architectures remain important in today's landscape. This book provides coverage of these emerging and key technologies and walks you through solution architecture design from key principles, providing you with the knowledge you need to succeed as a Solutions Architect. It will also level up your soft skills, providing career-accelerating techniques to help you get ahead. Unlock the potential of cutting-edge technologies, gain practical insights from real-world scenarios, and enhance your solution architecture skills with the Solutions Architect's Handbook.What you will learn Explore various roles of a solutions architect in the enterprise Apply design principles for high-performance, cost-effective solutions Choose the best strategies to secure your architectures and boost availability Develop a DevOps and CloudOps mindset for collaboration, operational efficiency, and streamlined production Apply machine learning, data engineering, LLMs, and generative AI for improved security and performance Modernize legacy systems into cloud-native architectures with proven real-world strategies Master key solutions architect soft skills Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders who already work in the IT industry and aspire to become solutions architect professionals. Solutions architects who want to expand their skillset or get a better understanding of new technologies will also learn valuable new skills. To get started, you'll need a good understanding of the real-world software development process and some awareness of cloud technology.
2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.
Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS Purchase of the print or Kindle book includes a free PDF eBook Key Features Go in-depth into the ML lifecycle, from ideation and data management to deployment and scaling Apply risk management techniques in the ML lifecycle and design architectural patterns for various ML platforms and solutions Understand the generative AI lifecycle, its core technologies, and implementation risks Book DescriptionDavid Ping, Head of GenAI and ML Solution Architecture for global industries at AWS, provides expert insights and practical examples to help you become a proficient ML solutions architect, linking technical architecture to business-related skills. You'll learn about ML algorithms, cloud infrastructure, system design, MLOps , and how to apply ML to solve real-world business problems. David explains the generative AI project lifecycle and examines Retrieval Augmented Generation (RAG), an effective architecture pattern for generative AI applications. You’ll also learn about open-source technologies, such as Kubernetes/Kubeflow, for building a data science environment and ML pipelines before building an enterprise ML architecture using AWS. As well as ML risk management and the different stages of AI/ML adoption, the biggest new addition to the handbook is the deep exploration of generative AI. By the end of this book , you’ll have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, real-world solution architecture, risk management, and governance. You’ll possess the skills to design and construct ML solutions that effectively cater to common use cases and follow established ML architecture patterns, enabling you to excel as a true professional in the field.What you will learn Apply ML methodologies to solve business problems across industries Design a practical enterprise ML platform architecture Gain an understanding of AI risk management frameworks and techniques Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using artificial intelligence services and custom models Dive into generative AI with use cases, architecture patterns, and RAG Who this book is for This book is for solutions architects working on ML projects, ML engineers transitioning to ML solution architect roles, and MLOps engineers. Additionally, data scientists and analysts who want to enhance their practical knowledge of ML systems engineering, as well as AI/ML product managers and risk officers who want to gain an understanding of ML solutions and AI risk management, will also find this book useful. A basic knowledge of Python, AWS, linear algebra, probability, and cloud infrastructure is required before you get started with this handbook.
Written by a leading expert in the field, this unique volume contains current test design approaches and focuses only on software test design. Copeland illustrates each test design through detailed examples and step-by-step instructions.
In a world where technology is rapidly evolving, the fusion of project management and artificial intelligence stands at the forefront of innovation. The AI Revolution in Project Management delves deep into the transformative power of generative AI tools that promise to reshape industries, and revolutionize how we manage projects. Whether you're looking to build dynamic teams using AI, choose a project development approach, or monitor project performance, this book has got you covered. Each chapter provides insightful narratives and includes a supplemental Technical Guide that provides tips on using the AI technology. With case studies and prompts, the dialogues showcase AI in action, from stakeholder engagement to risk management. Dive in with experts who’ve spent countless hours using these AI tools in project scenarios to offer a transparent view into generative AI-driven project management. In this book you'll learn: How to create prompts that generate meaningful and actionable insights tailored for your projects When to use AI to enhance decision-making, super-charge productivity, and elevate overall project efficiency Which generative AI models and plug-ins to use for specific project scenarios, ensuring seamless integration and maximum efficiency "AI is not just a buzzword; it’s a tool reshaping how we manage projects and engage with stakeholders." - From the Foreward by Ricardo Viana Vargas, Ph.D. Ricardo is an experienced leader in global operations, project management, business transformation, and crisis management. As founder and managing director of Macrosolutions, a consulting firm with international operations in energy, infrastructure, IT, oil, and finance, he managed more than $20 billion in international projects in the past 25 years. Update As AI products continue to evolve, information published in this book may change. Please note that as of February 2024, there is a name change for Bing Chat and Bard Chat. Microsoft Bing Chat is now Copilot: https://copilot.microsoft.com/. Google Bard is now Gemini: https://gemini.google.com/.
This book will teach you how to test computer software under real-world conditions. The authors have all been test managers and software development managers at well-known Silicon Valley software companies. Successful consumer software companies have learned how to produce high-quality products under tight time and budget constraints. The book explains the testing side of that success. Who this book is for: * Testers and Test Managers * Project Managers-Understand the timeline, depth of investigation, and quality of communication to hold testers accountable for. * Programmers-Gain insight into the sources of errors in your code, understand what tests your work will have to pass, and why testers do the things they do. * Students-Train for an entry-level position in software development. What you will learn: * How to find important bugs quickly * How to describe software errors clearly * How to create a testing plan with a minimum of paperwork * How to design and use a bug-tracking system * Where testing fits in the product development process * How to test products that will be translated into other languages * How to test for compatibility with devices, such as printers * What laws apply to software quality
What makes the world's leading engineering and QA teams so successful? Learn from Google, Etsy, The New York Times, GitHub, King, HelloFresh and many more. Leading Quality is the ultimate guide to becoming a leader of quality, mastering strategic decisions and enabling your team to accelerate growth.
Like a good story, successful design is a series of engaging moments structured over time. The User’s Journey will show you how, when, and why to use narrative structure, technique, and principles to ideate, craft, and test a cohesive vision for an engaging outcome. See how a “story first” approach can transform your product, feature, landing page, flow, campaign, content, or product strategy.
