From building your own cluster to running cloud-native applications with Kubernetes, this workshop covers it all using engaging examples and activities Cybersecurity is an area of increasing importance and a requirement for every software system. Problems in cybersecurity require adaptive data-driven solutions to be one step ahead of the attackers. AI offers methods of data analytics that enable us to efficiently recognize patterns in large-scale data. These methods have proven to be applicable in various cybersecurity problems, from authentication, detection of various types of cyberattacks in computer networks to the analysis of malicious executables. This book begins by introducing the data analytics environment in Cybersecurity and gives context on where AI methods would fit in Cybersecurity projects. It takes you on a journey with an in-depth explanation of AI methods and tools that can be used to apply those methods, design and implement AI solutions. Furthermore, it contains descriptions of scenarios in Cybersecurity where AI methods are applicable, including exercises and code examples that give the reader hands-on skills in applications of AI to Cybersecurity problems. This makes you capable to not only recognize where AI methods can be applied, but also to design and implement efficient solutions using AI methods. To make you even more effective, we add some common pitfalls from real-world applications of AI in cybersecurity problems and give considerations on how to deal with them. This book is aimed at Machine learning practitioners interested in applying their skills to cyber security issues. It is also for Cyber Security workers interested in leveraging machine learning methods. Fundamental concepts of machine learning and beginner level knowledge of Python Programming is needed for this book. Whether you are a student or an experienced professional, this book offers a unique and valuable learning experience that will give you the skills to protect your network and data against the ever-evolving threat landscape.