This course is the final course in a series that aims to prepare you for a role working as a programmer. In this course we will look at several automation concepts in DevOps with Python. Labs will allow the students to apply the material in the lectures in simple computer programs designed to re-enforce the material in the lesson.

In this intermediate-level project you will write JavaScript code to search through a string variable. You’ll use a variety of JavaScript methods to locate values within a string to determine whether they exist, find their position in the string, or even replace them with other values. The Notepad++ editor and Chrome browser are used to write inline JavaScript code and view the results. 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.

This course is all about starting to learn how to develop video games using the C++ programming language and the Unreal Engine on Windows or Mac. This course assumes you have previous programming experience in some other language. Although we'll start at the very beginning for C++, hardly anybody learns (or teaches) C++ as a first language. Similarly, Unreal Engine is a commercial, industrial strength game engine. With great power comes great ... complexity, so it's important that you have the will to work hard to learn how to use C++ in Unreal Engine. Computer programming is really fun in general, and programming games is even better! Caution: Introduction (starting to learn C++ and Unreal Engine) is not the same as easy (not hard to do). Learning to program using C++ in Unreal Engine IS hard to do, especially since this course is essentially the first half of a freshman-level college course. Meeting the course challenges while you master the material will be rewarding to you, but doing that will require hard work and maybe even a few expletives along the way. Module 1: Write your first C++ console application and Unreal script Module 2: Learn how we store and use data in our programs Module 3: Learn how we use classes and objects to implement our code Module 4: Learn the basics of Unreal Engine

In modern cloud native application development, it’s oftentimes the goal to build out serverless architectures that are scalable, are highly available, and are fully managed. This means less operational overhead for you and your business, and more focusing on the applications and business specific projects that differentiate you in your marketplace. In this course, we will be covering how to build a modern, greenfield serverless backend on AWS. Building brand new applications on AWS is a different task than lifting and shifting existing applications into AWS. When you have an existing application that you need to move to AWS, you might first look to using Amazon EC2 as your virtual machines, or maybe you might look into using docker containers and container hosting services like Amazon Elastic Container Service or Amazon Elastic Kubernetes Service. Those are all great application hosting options, but in most cases, they still require you to have some kind of pulse on the underlying infrastructure hosting your application. ` Building Modern Python Applications on AWS will explore how to build an API driven application using Amazon API Gateway for serverless API hosting, AWS Lambda for serverless computing, and Amazon Cognito for serverless authentication. We will follow an API driven development process and first mock up what the API will look like. We will cover all the ins and outs of the service Amazon API Gateway, and as you’ll learn- it does a lot more than just hosting an API. Then we will add authentication to the API using Amazon Cognito. You’ll learn about how the authorization flow works with Cognito, and how to build it into your APIs. From there, we will add a Lambda backend that will be triggered by API Gateway. The lambda functions will be using the AWS SDKs to perform various data processing tasks. You’ll learn about the different configurations that exist for Lambda, and we will show you how to create and manage lambda functions. Some of the features of our API will require multiple lambda functions to execute in a specific order, like a workflow, and we will use AWS Step Functions to create a serverless workflow. Finally, we will talk about how to optimize your APIs at every layer using AWS features. Note: There are four versions of this class, "Building Modern Node.js Applications on AWS" for Node.js developers, Building Modern Java Applications on AWS" for Java developers, "Building Modern .NET Applications on AWS" for .NET developers, and this course, "Building Modern Python Applications on AWS" for Python developers. The courses do for a large part, overlap and in general, we recommend that you take the course that focuses on the SDK you plan to use to develop your AWS Cloud based applications. We expect that you have basic knowledge of AWS already. Some examples of concepts you should be familiar with are: you should know the basics of the AWS Global infrastructure, like what regions and availability zones are. You also should know the at a high-level AWS Identity and Access Management, or IAM, and how it is used to control access to AWS resources. You should also understand what an Amazon EC2 instance is, what Amazon S3 is, what a VPC is, as well as other basic AWS terminology.

In this 1 hour and 30 minutes long project, you will learn how to create a fully functional graphical calculator using Java and one of it’s most promising graphical libraries; JavaFX. This project gives you a head start with one of the most widely used programming languages in the world; Java. The project will teach you basic programming fundamentals such as data structures and conditional statements. Learning Java and JavaFX will open the door for you to create rich cross-platform applications customized to fit your needs.

This is a self-paced lab that takes place in the Google Cloud console. GKE Autopilot provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. Autopilot is a new managed mode of operation for Google Kubernetes Engine (GKE) in which Google creates, sizes, and automatically scales on your behalf the physical infrastructure needed to run your application workloads. In this lab, you get hands-on practice containerizing an application and deploying it to an Autopilot cluster using Kubernetes configuration and commands.

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 project will teach you TypeScript string properties and methods in the TypeScript playground which will make string handling easier.Since text data is commonly used as a “string” in TypeScript, the ability to use and manipulate strings is a core component of TypeScript programming. So in this guided project you are going to learn different string properties and methods which are important for string manipulation operations. 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.

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.

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.