AI is all around us, and it is no longer just the work of scientists. In this course, Developing AI Models in Microsoft Azure, you will learn the ins and outs of Azure Machine Learning Service. You'll start with the basics, and learn how to set up your development environment with a demo walking through each important step. With your development environment set up, you'll examine how to use the facilities of the Azure machine learning workspace, interact with it via VSCode and Jupyter notebooks using the Azure ML SDK, how to provision remote compute, and how to deploy a model to the various options, such as docker image, ACI, or AKS. By the end of this course, you will have the necessary skills to tackle any enterprise class custom AI problem in the Microsoft Azure ecosystem.
Sahil Malik has been a Microsoft MVP for the past 8 years, author of several books and numerous articles in both the .NET and SharePoint space, consultant, and trainer who delivers talks at conferences internationally.
Course Overview (Music) Hello. My name is Sahil Malik, and welcome to my course, Developing AI Models in Microsoft Azure. Artificial intelligence and machine learning is an extremely important topic, and in this course, I provide you with an overview of what Azure has to offer in this space. I demystify the roles of Cognitive Services, ML Studio, and the ML workspace. Then I take a deep dive into the ML workspace and I explain how you can set up your development environment via Jupyter Notebooks or directly in VS Code. I show you how you can train and register a model. And finally, how to deploy it so your customers can call your model via a simple web service. I feel using Azure Machine Learning workspace you can tackle any enterprise-class AI problem. And by the end of this course, you will be well equipped to do so. I hope you find this course useful, and thank you for watching.