Identifying Security Requirements of an AI Solution
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In this course, you will walk through the services used to create an AI solution in Azure and the requirements to secure the solution, including data security and deployment security of Machine Learning models and Cognitive Services.
Learn what it takes to secure your newly developed and/or deployed AI solution in Microsoft Azure. In this course, Identifying Security Requirements of an AI solution, you will learn foundational knowledge to secure your AI Solution no matter whether you are leveraging Azure Cognitive Services or custom machine learning models. First, you will discover how to leverage Azure Cognitive Services in a secure authenticated way. Next, you will learn what security options are available for any test data that you need to train the models of both Cognitive Services and machine learning models. Finally, you will explore how to secure the deployment of an AI solution using machine learning models. When you are finished with this course, you will have the skills and knowledge of security options within Azure Services needed to secure an AI solution from development to deployment.
Author Name: Brian Harrison
Author Description:
Brian has been working in the Cloud space for more than a decade as both a Cloud Architect and Cloud Engineer. He has experience building Application Development, Infrastructure, and AI-based architectures using many different OSS and Non-OSS based technologies. In addition to his work at Pluralsight, he is always trying to educate customers about how to get started in the cloud with his many blogs and videos. He is currently working as a Cloud Solution Architect for Microsoft designing solution… more
Table of Contents
- Course Overview
1min - Working with Authorization and Authentication
23mins - Security of Test Data
30mins - Securing an AI Solution Deployment
33mins
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