The purpose of this program is to give you an insight into the security challenges involving workload protection and application security in the cloud, and Check Point’s solutions for those challenges. The program will also enable you to perform a basic deployment and configuration of the various solutions under the CloudGuard umbrella. Chapter 1 - Program introduction Chapter 2 – Introduction to Workload protection and application security Lesson 1: Introduction to cybersecurity in the cloud Lesson 2: Security challenges of cloud workloads Lesson 3: CloudGuard Workload Protection Chapter 3 - CloudGuard Workload Protection - Container Security Lesson 1: Recap Lesson 2: Runtime Protection Lesson 3: Image Assurance Lesson 4: Admission Control Lesson 5: Threat Intelligence Lesson 6: Posture Management Lesson 7: Deployment Lesson 8: Deployment troubleshooting Chapter 4 - Shifting protection to the left with CloudGuard ShiftLeft Lesson 1: Introduction to shifting security to the left Lesson 2: Deployment Chapter 5 – CloudGuard Workload protection - Serverless Security Lesson 1: Serverless security Lesson 2: CloudGuard Serverless Security for AWS Lambda Lesson 3: Deployment Chapter 6 – CloudGuard Application Security and API Protection Lesson 1: Introduction to application security and API protection Lesson 2: The CloudGuard AppSec solution Lesson 3: Architecture and deployment considerations Lesson 4: Deployment process Lesson 5: Deployment Lesson 6: Setting up API protection Lesson 7: Data and customization of AppSec policy Chapter 7 – Program summary Check Point CloudGuard provides unified cloud-native security for all your assets and workloads, giving you the confidence to automate security, prevent threats, and manage posture – everywhere – across your multi-cloud environment.

This is a self-paced lab that takes place in the Google Cloud console. In this lab you will use GCP services to help graph trades, volume, and time delta from trade execution to see any patterns in the high volatility of the cryptocurrency market.

This is a self-paced lab that takes place in the Google Cloud console. Hands-on lab to deploy the NGINX Ingress Controller on Google Kubernetes Engine.

This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.

This course is ideal for beginners eager to learn the fundamental concepts that underpin the Swift programming language. Explore the basic programming concepts and data structures that are core to any language, while discovering the unique aspects that make Swift as versatile as it is today. In this course, you will receive hands-on practice utilizing these concepts. More specifically, you will learn how to use constants and variables with different data types and explore how to sort and store information in collection types such as arrays, tuples and dictionaries. Finally, you will discover how to make your code reusable and more expressive by using functions and closures. By the end of this course, you will be able to: • Demonstrate a working knowledge of general programming principles • Prepare your computer system for Swift programming • Show understanding of Swift syntax and how to control the flow of code • Demonstrate knowledge of how to declare, use and modify constants and variables • Differentiate between the different types of operators and their functions • Demonstrate how to create simple control flow patterns and call functions using Swift This is a beginner course for learners who would like to prepare themselves for a career in iOS development. To succeed in this course, you do not need prior web development experience, only basic internet navigation skills and an eagerness to get started with coding.

Moving to the cloud creates numerous opportunities to start working in a new way and it empowers the workforce to better collaborate and innovate. But it’s also a big change. Sometimes the success of the change hinges not on the change itself, but on how it’s managed. This course will help people managers to understand some of the key challenges associated with cloud adoption, and provide them with a verified in-the-field framework that will assist them in supporting their teams on the change journey. By addressing the human factor of moving to the cloud, organizations increase their chances of realizing business objectives and investing in their future talent.

In this course, you will explore the tools and techniques that can be used to work with Modern Data Warehouses productively and securely within Azure Synapse Analytics. You will learn how Azure Synapse Analytics enables you to build Data Warehouses using modern architecture patterns and how the common schema is implemented in a data warehouse. You'll learn the best practices you need to adopt to load data into a data warehouse and the techniques that you can use to optimize query performance within Azure Synapse Analytics. This course is part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services for anyone interested in preparing for the Exam DP-203: Data Engineering on Microsoft Azure (beta). This is the fifth course in a program of 10 courses to help prepare you to take the exam so that you can have expertise in designing and implementing data solutions that use Microsoft Azure data services. The Data Engineering on Microsoft Azure exam is an opportunity to prove knowledge expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions that use Microsoft Azure data services. Each course teaches you the concepts and skills that are measured by the exam. By the end of this Specialization, you will be ready to take and sign-up for the Exam DP-203: Data Engineering on Microsoft Azure (beta).

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will continue working on your Pigeon Travel chat agent and add context as well as setup fulfillment to lookup and store reservations entries in Firestore.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will learn how to build a binary classification model from tabular data using Vertex AI.

By the end of this project, you will have successfully created a virtual private cloud using Amazon Web Services and launched a virtual machine instance in that cloud. A virtual private cloud is a secure, isolated private cloud hosted within a public cloud. Virtual private clouds allow users to establish a higher level of security and privacy within the cloud structure while taking advantage of the scalability offered by cloud providers. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.