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Labs

Azure Labs

FYI: many of these labs are being moved to Microsoft Learn.

Microsoft Learn gives you the ability to run all of these (and more!) great labs for free - without using your Azure credits. Check it out at docs.microsoft.com/learn!

Azure Labs is a collection of hands-on coding labs designed to help Computer Science faculty and students learn how to deploy solutions to the Azure cloud involving common scenarios such as Web development, AI and machine learning, data science, and IoT using cross-platform technologies. Most labs are compatible with Windows, macOS, or Linux and take 60 to 90 minutes to complete.

Before you start, make sure you have access to a Microsoft Azure subscription. Students can get a free Azure subscription and credits here:

The labs fall into six general categories:

Lab Categories Description
AI and Machine Learning Build bots and apps backed by AI and ML using Azure and Azure Cognitive Services and popular open-source libraries such as Keras and TensorFlow.
Azure Services Deploy serverless code with Azure Functions, run Docker containers, use Azure to build Blockchain networks and more.
Big Data and Analytics Spin up Apache Spark Clusters, Use Hadoop to extract information from big datasets or use Power BI to explore and visualize data.
Deep Learning These labs build on each other to introduce tools and libraries for AI. They're labeled 200-400 level to indicate level of technical detail.
Internet-of-Things Use Azure to collect and stream IoT data securely and in real time.
Web Development Quickly create a scalable web apps using Node, PHP, MySQL on easy-to-use tools like Visual Studio Code and GitHub.

Examples include building a machine-learning model that performs Optical Character Recognition (OCR), deploying an Azure Function that evaluates images uploaded to blob storage for adult content, and building a BlockChain network on Azure. Feel free to explore the folders and subfolders in this repo to discover all sorts of interesting exercises and use them to hone your Azure knowledge and development skills.

If you want to report any issues that need to be fixed, please log an issue on GitHub. Include the content section (Deep Learning, Azure Services, etc.), lab title, and exercise number, along with any error messages and screenshots. We are constantly adding new labs and refreshing existing ones, and we welcome your feedback on improving the content and keeping it current.

Unless otherwise noted, these materials are licensed under the terms of the MIT License. You may use them according to the license as is most appropriate for your project. The terms of this license can be found at https://opensource.org/licenses/MIT.