Microsoft Applied Skills: Build an Azure AI Vision solution
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This course goes through all of the skills required for the Microsoft Applied Skills: Build an Azure AI Vision solution.
This can also help with Microsoft AI-102 “Designing and Implementing a Microsoft Azure AI Solution” exam, with “Implement computer vision solutions”.
In this 2½ hour course we’ll cover the skills that you need for the Microsoft Applied Skills credential for Azure AI Vision.
The tasks that you need to perform to get this skill are:
- Create a computer vision resource and analyze images. We’ll create a computer vision resource in a free Azure subscription, and use it to analyze images. We’ll create captions and dense captions, looking at the results in text and in JSON format, before looking at other features.
- Create, train, evaluate and consume a custom image analysis model. After that, we’ll create a custom image analysis model. We will train it to recognise three different types of products, and then test it so that it can identify them in new photos.
- Programming in C#. Finally, we’ll find out how to analyse images in code. We’ll use Visual Studio and customise code to connect to both the computer vision and the custom image resources, and use them to analyse images and return the analysis.
We’ll go through several practical examples, so you can see how you can analyse your own images.
By the end of the course, you’ll be much more confident about using building an Azure AI Vision solution and perhaps even take the official Microsoft assessment. That would look great on your CV or resume.
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21Downloading Visual Studio Community
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22Downloading the NuGet package
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23Creating a new project, looking around VS, and downloading a NuGet package
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24Investigating the ImageAnalyzer
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25Implementing the ImageAnalyzer in C#
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26Investigating the ImageAnalyzerResult
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27Implementing the ImageAnalyzerResult object in C#
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28Analyzing images using C#
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29Using the ImageAnalyzer and ImageAnalyzerResult in Python
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30Downloading NuGet in Visual Studio Code
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31Using C# in Visual Studio Code