Microsoft Azure AI Engineer: Deploying AI Solutions in Microsoft Azure

Deploying and configuring AI solutions in Microsoft Azure to support business outcomes requires in-depth knowledge about the range of service and options available in Azure, as well as a foundational knowledge of what an AI solution actually is.

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Course Insight

Suitable for beginner learners. This course serves as an entry point into Information Technology, building foundational knowledge before moving on to advanced frameworks or specialized paths.

Beginner FriendlySelf-Paced Learning

SKILLS TO
MASTER

Information Technology Basics
Fundamental principles and concepts
Practical ApplicationTrending
Real-world project implementation
Best Practices
Industry standard workflows and guidelines
Problem Solving
Core Concepts
Implementation
Workflow Integration
Optimization
Careers:Cloud Engineer, DevOps Engineer, Solutions Architect.

Quick Facts

2 hour 21 minutes
Beginner
Core Courses
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What You’ll Learn

AI solutions in Microsoft Azure consist of a number of independent resources and services working together holistically to produce a complex solution. In this course, Microsoft Azure AI Engineer: Deploying AI Solutions in Microsoft Azure, you'll gain an understanding of the nature of AI solutions in order to be able to recommend the right services and configuration options which will enable the work of data scientists and ensure that business investment in AI is both fit-for-purpose and well maintained. First, you'll look at the core nature of AI solutions and how these are represented by solution architectures in Microsoft Azure. Then, you'll work on the different scenarios to provide the computing services which data scientists need to build, train, and deploy AI models, including understanding the operational frameworks of monitoring, security, and zero-trust architecture. Finally, you'll bring everything together by deploying an AI model in a container-based solution using IoT Edge. By the end of this course, you'll have a thorough understanding of how AI solutions in Microsoft Azure are put together, and how you, as an AI Engineer, can influence the architecture, configuration, and deployment of these solutions to support a wide range of business and technical outcomes.

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Outcomes

  • Course Overview : 2mins.
  • Deploying Azure AI Solutions : 26mins.
  • Understanding Continuous Monitoring : 33mins.
  • Deploying Container Environments : 30mins.
  • Deploying IoT Devices : 22mins.
  • Managing Security for AI Solutions : 25mins.
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FAQs

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Microsoft Azure AI Engineer: Deploying AI Solutions in Microsoft Azure
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