Cybersecurity Career Master Plan. Proven techniques and effective tips to help you advance in your cybersecurity career

Dr. Gerald Auger, Jaclyn "Jax" Scott, Jonathan Helmus, Kim Nguyen, ...

Cybersecurity is an emerging career trend and will continue to become increasingly important. Despite the lucrative pay and significant career growth opportunities, many people are unsure of how to get started.This audiobook is designed by leading industry experts to help you enter the world of cybersecurity with confidence, covering everything from gaining the right certification to tips and tools for finding your first job. The audiobook starts by helping you gain a foundational understanding of cybersecurity, covering cyber law, cyber policy, and frameworks. Next, you'll focus on how to choose the career field best suited to you from options such as security operations, penetration testing, and risk analysis. The audiobook also guides you through the different certification options as well as the pros and cons of a formal college education versus formal certificate courses. Later, you'll discover the importance of defining and understanding your brand. Finally, you'll get up to speed with different career paths and learning opportunities.By the end of this cyber audiobook, you will have gained the knowledge you need to clearly define your career path and develop goals relating to career progression.

Elastic Stack 8.x Cookbook. Over 80 recipes to perform ingestion, search, visualization, and monitoring for actionable insights

Huage Chen, Yazid Akadiri, Shay Banon

Learn how to make the most of the Elastic Stack (ELK Stack) products—including Elasticsearch, Kibana, Elastic Agent, and Logstash—to take data reliably and securely from any source, in any format, and then search, analyze, and visualize it in real-time. This cookbook takes a practical approach to unlocking the full potential of Elastic Stack through detailed recipes step by step.Starting with installing and ingesting data using Elastic Agent and Beats, this book guides you through data transformation and enrichment with various Elastic components and explores the latest advancements in search applications, including semantic search and Generative AI. You'll then visualize and explore your data and create dashboards using Kibana. As you progress, you'll advance your skills with machine learning for data science, get to grips with natural language processing, and discover the power of vector search. The book covers Elastic Observability use cases for log, infrastructure, and synthetics monitoring, along with essential strategies for securing the Elastic Stack. Finally, you'll gain expertise in Elastic Stack operations to effectively monitor and manage your system.

The Scrum Master Guide. A practical guide to successfully practicing Scrum and achieving Scrum Master certifications - Second Edition

Fred Heath

Curious why so many rely on Scrum and what makes Agile so effective? Learn from seasoned software engineer and Scrum expert Fred Heath, everything you need to become a certified Scrum Master. With over two decades of experience across the software development lifecycle, Fred brings invaluable insights from his extensive work in Scrum, both as a Scrum Master and developer. In this updated guide, he not only takes you from Scrum basics to mastery but also offers practical, real-world knowledge to help you become an effective Scrum Master.The first part of the book introduces the Scrum fundamentals and prepares you for Level I certification, covering the importance of Scrum team structure, the benefits of well-planned sprints, and how to create and manage sprint and product backlogs.The second part elevates your skills to the Level II certification standard, exploring advanced topics such as Scrum anti-patterns, scaling Scrum, and how to support developers and product owners. Each chapter concludes with quizzes to reinforce the concepts you've learned. The book wraps up with exam preparation tips and myth-busting strategies to give you a competitive edge in passing your Scrum Master exams.By the end of this book, you'll be proficient as a Scrum Master ensuring you won’t fall behind in an ever-increasingly agile world.

Hands-On Microservices with Django. Build cloud-native and reactive applications with Python using Django 5

Tieme Woldman

This book is for Django developers looking to create optimized and scalable web applications using microservices. With it, you’ll learn the principles of microservices and message/task queues and build your first microservices with Django RESTful APIs (DFR) and RabbitMQ. You’ll also master the fundamentals, dockerize your microservices, and optimize and secure them for production environments. By the end, you'll have the skills to design and develop production-ready Django microservices applications with DFR, Celery/RabbitMQ, Redis, and Django's cache framework.

AI for Absolute Beginners: A Clear Guide to Tomorrow. Demystifying AI for Beginners and Paving the Path to Future Innovations

Oliver Theobald

The course begins with an engaging introduction to the world of Artificial Intelligence, making it approachable for absolute beginners. We unravel the mysteries of AI's evolution, from its historical roots to the cutting-edge technologies shaping our future. By explaining complex concepts in simple terms, this course aims to illuminate the path for those curious about how AI impacts our world.The course focuses on the core components of AI, including machine learning, deep learning, and natural language processing, before advancing to more specialized topics like generative AI and computer vision. Each module is designed to build a comprehensive understanding, emphasizing why these technologies are crucial for solving real-world problems and how they're transforming industries.The course wraps up by exploring the ethical considerations and privacy concerns associated with AI, along with a visionary look at the future of work in an AI-driven world. It offers a treasure trove of further resources, ensuring learners have everything they need to continue their exploration of AI.

Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications

Valery Manokhin, Agus Sudjianto

In the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. Practical Guide to Applied Conformal Prediction in Python addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework set to revolutionize uncertainty management in various ML applications.Embark on a comprehensive journey through Conformal Prediction, exploring its fundamentals and practical applications in binary classification, regression, time series forecasting, imbalanced data, computer vision, and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse industries. Practical examples in Python using real-world datasets reinforce intuitive explanations, ensuring you acquire a robust understanding of this modern framework for uncertainty quantification.This guide is a beacon for mastering Conformal Prediction in Python, providing a blend of theory and practical application. It serves as a comprehensive toolkit to enhance machine learning skills, catering to professionals from data scientists to ML engineers.

Learn Quantum Computing with Python and IBM Quantum. Write your own practical quantum programs with Python - Second Edition

Robert Loredo

The IBM Quantum Platform was built to enable developers to learn the basics of quantum computing by providing access to high performant quantum computers and provide documentation and courses to help get up to speed with the latest features in quantum computing. Updated with new examples and changes to the platform, this edition begins with an introduction to the IBM Quantum Platform and the Quantum Information Science Kit (Qiskit) SDK. You will become well versed in the IBM Quantum Composer interface as well as running your quantum circuits on a real quantum computer. Along the way, you’ll learn some of the fundamental principles regarding quantum mechanics, qubits, quantum gates, quantum circuits, and the error mitigation techniques that are used to perform operations on qubits. As you build on your knowledge, you’ll understand the functionality of IBM Qiskit and the developer-focused resources so you can create your own quantum algorithms. You’ll learn how to monitor and optimize your quantum circuits. Lastly, you’ll look at the fundamental quantum algorithms and understand how they can be applied effectively. By the end of this quantum computing book, you'll know how to build quantum algorithms and will have gained a practical understanding of quantum computation that you can apply to your research or business.

15 Math Concepts Every Data Scientist Should Know. Understand and learn how to apply the math behind data science algorithms

David Hoyle

Data science combines the power of data with the rigor of scientific methodology, with mathematics providing the tools and frameworks for analysis, algorithm development, and deriving insights. As machine learning algorithms become increasingly complex, a solid grounding in math is crucial for data scientists. David Hoyle, with over 30 years of experience in statistical and mathematical modeling, brings unparalleled industrial expertise to this book, drawing from his work in building predictive models for the world's largest retailers. Encompassing 15 crucial concepts, this book covers a spectrum of mathematical techniques to help you understand a vast range of data science algorithms and applications. Starting with essential foundational concepts, such as random variables and probability distributions, you’ll learn why data varies, and explore matrices and linear algebra to transform that data. Building upon this foundation, the book spans general intermediate concepts, such as model complexity and network analysis, as well as advanced concepts such as kernel-based learning and information theory. Each concept is illustrated with Python code snippets demonstrating their practical application to solve problems.By the end of the book, you’ll have the confidence to apply key mathematical concepts to your data science challenges.