Choosing the Appropriate Microsoft Azure Services and Features

This course is a part of Designing Microsoft Azure AI Solutions, a 6-course Paths series from Pluralsight.

AI solutions in Microsoft Azure consist of a number of independent resources and services working together holistically to produce a complex solution. As an AI Engineer, In this course, Choosing the Appropriate Microsoft Azure Services and Features, you’ll gain understanding of the processes which are inherent within an AI solution as well as some of the challenges faced by data scientists in the building and training of machine learning models in order to be able to recommend the most appropriate services and features. First, you’ll look at the different types of data that you’re going to need to understand and deal with, including recommending the right services to support different data scenarios. Then, you’ll explore the difference between machine learning models and frameworks, including the different types of machine learning models, incorporating both standard machine learning as well as deep learning. Finally, you’ll explore machine learning pipelines and automated machine learning, including the business and technical challenges that these technologies are designed to overcome. At the end of this course, you will have a basic understanding of the different Azure services.