Developing AI Applications on Azure

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Course overview

Provider
Coursera
Course type
Free online course
Level
Advanced
Deadline
Flexible
Duration
16 hours
Certificate
Paid Certificate Available
Course author
Ronald J. Daskevich, DCS
  • Define Artificial Intelligence and Machine Language

  • Describe AI tools and roles, and the Microsoft Team Data Science Process

  • Work with Azure APIs, including those for vision, language, and search

  • Create, train, test and deploy your AI model in the cloud

Description

This course introduces the concepts of Artificial Intelligence and Machine learning. We'll discuss machine learning types and tasks, and machine learning algorithms. You'll explore Python as a popular programming language for machine learning solutions, including using some scientific ecosystem packages which will help you implement machine learning. Next, this course introduces the machine learning tools available in Microsoft Azure. We'll review standardized approaches to data analytics and you'll receive specific guidance on Microsoft's Team Data Science Approach. As you go through the course, we'll introduce you to Microsoft's pre-trained and managed machine learning offered as REST API's in their suite of cognitive services. We'll implement solutions using the computer vision API and the facial recognition API, and we'll do sentiment analysis by calling the natural language service. Using the Azure Machine Learning Service you'll create and use an Azure Machine Learning Worksace.Then you'll train your own model, and you'll deploy and test your model in the cloud. Throughout the course you will perform hands-on exercises to practice your new AI skills. By the end of this course, you will be able to create, implement and deploy machine learning models.

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