This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will learn how you can use Identity-Aware Proxy (IAP) TCP forwarding to enable administrative access to VM instances that do not have external IP addresses or do not permit direct access over the internet.

This is a self-paced lab that takes place in the Google Cloud console. A convolution is a filter that passes over an image, processes it, and extracts features that show a commonality in the image. In this lab you'll see how they work, and try processing an image to extract features from it! You also explore pooling, which compresses your image and further emphasizes the features.

Components are popular in engineering and used for building user interfaces and games. Components are elements that you can use in designs when working with Figma. They help to make your projects have consistency. Adding the concept of components to a design tool makes the composition of complex designs more consistent and efficient. The great part of components in Figma is that Figma wants to make components easy to learn and use while still being powerful enough for advanced users. Learning about components will help you to build things faster and more consistently. By the end of this project you will be able to manipulate components in your projects easier.

This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.

This is a self-paced lab that takes place in the Google Cloud console. In this hands-on lab you will learn how to perform basic tasks in Cloud Storage using the gsutil command-line tool. For a short preview, watch <A HREF="https://youtu.be/69MdTXgA6Ws"/>Cloud SDK - Essential Command-Line Tools for Google Cloud Platform</A>.

In this 1-hour long project-based course on Introduction to Docker: Build your own portfolio website, you will learn how to use Docker on the command line and create your own portfolio website from a Bootstrap template in a Docker container. You will get to explore and demystify the Docker landscape and see how Docker works by using it. You will learn many fundamental concepts which will help you progress in your career, studies and knowledge, such as images, containers, the registry, the client/server model in Docker via the Docker Engine etc. You will use various commands and become comfortable spinning up containers, doing basic debugging to see statuses of containers, linking local files to files inside of Docker and learning basic networking to map a container port to a port on your local host machine to set up a development environment with Docker. Most importantly you will leave this course more confident in your knowledge of Docker and ready to understand Docker at a more advanced level, and ready to contribute better to your technical or development teams 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.

It is a common situation that, in any company, employees want to get general information about a topic they are interested in, for example, how many vacation days they have, when was the company founded, do they work on weekends, are there any dressing rules, who is the CEO and so on. Of course, there is always a person or multiple persons in the company who can give those answers, but there is a much better way of providing your colleagues with information they need then chasing those all-knowing employees for answers, and that is a fully automated chatbot created with Power Virtual Agent, which is one of the 4 main parts of the Power Platform. In this 35-minutes long guided project, “Use SharePoint & Power Virtual Agent to Create Smart Chatbot”, you will create a SharePoint site and list, add some data to it and create a Power Virtual Agent chatbot which will automate the information flow from your company to the employees. Once the chatbot is up and running, you and your colleagues won’t have to bother other colleagues in person or send them emails or texts anymore, you will be able to have a nice and easy-going conversation with the bot behind the chatbot and find out the information you need. Since this project uses Office 365 services like SharePoint and Power Virtual Agent (part of the Microsoft Power Platform), you will need access to a Microsoft account and a Microsoft 365 Developer Program subscription account. In the video at the beginning of the project you will be given instructions on how to sign up for both. If you are ready to create your artificial co-worker which will help you and your colleagues provide information to others, then this project is for you! Let's get started!

In this 1-hour long project-based course, you will learn to create an IoT hub in the Azure cloud, and learn to use the Azure IoT Hub extension for Visual Studio Code to monitor and send device-to-cloud messages and cloud-to-device messages. Then you will learn to create an Azure storage account and create a stream analytics job with an IoT hub as input and a storage account as output so that the messages can be stored on the Azure storage. Finally, you will also configure message routing that enables sending telemetry data from IoT Hub to custom endpoints, and to store the data we will route the messages to the blob storage in Azure. Before beginning this course, you should be familiar with the services of Microsoft Azure such as Azure IoT hub, stream analytics, and Storage account. Also, you should have an Azure account prior.

This is a self-paced lab that takes place in the Google Cloud console. This lab shows you how to use the Wrangler and Data Pipeline features in Cloud Data Fusion to clean, transform, and process taxi trip data for further analysis.

In Microsoft Azure, the Computer Vision cognitive service uses pre-trained models to analyze images, enabling software developers to easily build applications"see" the world and make sense of it. This ability to process images is the key to creating software that can emulate human visual perception. In this course, you'll explore some of these capabilities as you learn how to use the Computer Vision service to analyze images. This course will help you prepare for Exam AI-900: Microsoft Azure AI Fundamentals. This is the third course in a five-course program that prepares you to take the AI-900 certification exam. This course teaches you the core concepts and skills that are assessed in the AI fundamentals exam domains. This beginner course is suitable for IT personnel who are just beginning to work with Microsoft Azure and want to learn about Microsoft Azure offerings and get hands-on experience with the product. Microsoft Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Microsoft Azure Data Scientist Associate or Microsoft Azure AI Engineer Associate, but it is not a prerequisite for any of them. This course is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience is not required; however, some general programming knowledge or experience would be beneficial. To be successful in this course, you need to have basic computer literacy and proficiency in the English language. You should be familiar with basic computing concepts and terminology, general technology concepts, including concepts of machine learning and artificial intelligence.