Building AI Cloud Apps with Microsoft Azure | Coursera

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Master Azure cloud development and building AI solutions. Learn how to create scalable, intelligent cloud applications using Microsoft Azure.
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Develop and deploy create event-driven, serverless architectures with Microsoft Azure
Manage and select appropriate Microsoft Azure storage solutions
Deploy and manage containerized web applications using Azure App Service
Integrate Microsoft Azure machine learning, computer vision, and natural language processing into software solutions
This Building AI Cloud Apps with Microsoft Azure program offers a comprehensive nine-course program that covers a wide range of topics on developing cloud and AI solutions with Microsoft Azure, including Azure Functions, Azure Service Bus, Azure Storage, Azure Virtual Machines, and Azure App Service.
You will learn to create event-driven systems, master publish-subscribe patterns, manage Azure storage options, and deploy web applications using Azure App Service. After which, the specialization will discuss developing intelligent software solutions with artificial intelligence and machine learning using Microsoft Azure, including exploring key AI concepts and building practical AI applications. You will gain hands-on experience with Azure Machine Learning Studio, Azure Computer Vision Services, and Azure Natural Language Processing Services. You’ll also learn how to use GitHub Copilot to improve your efficiency as a software developer.
By completing this program, you will be well-equipped to design, develop, and deploy sophisticated cloud solutions that incorporate cutting-edge AI capabilities, positioning your software development ability to the forefront of the rapidly evolving field of cloud computing and artificial intelligence.
Throughout the specialization, learners will work on various hands-on projects that simulate real-world business scenarios. These projects will range from building serverless cloud solutions using Azure Functions to building language translation solutions using Azure Natural Language Services. These projects include:
Developing serverless, event-driven software solutions with Azure Functions and Azure Event Bus
Implementing storage solutions and managing virtual machines in Azure
Building and deploying web applications using Azure App Service and Docker containers
Implementing AI, computer vision, and natural language processing solutions using Azure AI Services
Develop an Azure Function
Deploy an Azure Function
Evaluate Azure services for integration and process automation scenarios
Test an Azure Function
How Azure Functions enable the creation of event-driven, compute-on-demand systems that can be triggered by various external events.
Implement the publish-subscribe pattern in the cloud using Azure Queue storage
Use Azure Service Bus topics and queues in a distributed architecture to ensure reliable communications
Connect sending and receiving applications with Event Hubs so you can handle extremely high loads without losing data
The basics of storage management in Azure
How to create a Storage Account
How to choose the right model for your data
Learn how to create, configure, and manage virtual machines on Linux and Windows that host web apps
Create and manage a virtual machine. Work with Windows virtual machines in Azure
Build a run a web application with the MEAN stack
Create and manage a Linux virtual machine
Use deployment slots to streamline deployment and roll back a web app in Azure App Service
Implement and deploy a web app to Azure App Service
Use the publishing features of Visual Studio 2019 to deploy and manage an ASP.NET Core web application hosted on Azure
Deploy and run a containerized web app with Azure App Service
How to identify guiding principles for responsible AI
How to identify features of common AI workloads
How to describe capabilities of no-code machine learning with Azure Machine Learning Studio
How to identify core tasks in creating a machine learning solution
How to describe core machine learning concepts
How to identify common machine learning types