Professional Level
2 Hands-on labs

Azure AI Implementation and Monitoring

By Dan Sasse

Prepare for Microsoft's Designing and Implementing an Azure AI Solution (AI-100) certification exam.

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2 hours
  • 15 Lessons
  • 2 Hands-On Labs

About the course

Artificial Intelligence, or AI, and the Machine Learning that drives it, is one of the most exciting new frontiers of technology being presented in the cloud today. Microsoft’s Designing and Implementing an Azure AI Solution (AI-100) is an exam that covers the Azure AI services and products available.

The Certification, as described by Microsoft:

  • Candidates for this exam analyze the requirements for AI solutions, recommend appropriate tools and technologies, and implements solutions that meet scalability and performance requirements.

  • Candidates translate the vision from solution architects and work with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end solutions. Candidates design and implement AI apps and agents that use Microsoft Azure Cognitive Services and Azure Bot Service. Candidates can recommend solutions that use open-source technologies.

  • Candidates understand the components that make up the Azure AI portfolio and the available data storage options.

  • Candidates implement AI solutions that use Cognitive Services, Azure bots, Azure Search, and data storage in Azure. Candidates understand when a custom API should be developed to meet specific requirements.

The fourth course covers implementation concepts, monitoring, and continuous improvement of an AI design.

Lab Highlights

Extracting Key Phrases from Text Using the .NET SDK Detecting Named Entities in Text Using the .NET SDK
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  • Chapter 1 3 Lessons Introduction 4:58

    An Important Note About A Cloud Guru and Linux Academy Courses

    1:19

    Course Introduction

    1:36

    About the Training Architect

    2:03
  • Chapter 2 6 Lessons Integrate AI Services with Solution Components 2:09:51

    Configure Prerequisite Components and Input Datasets to Allow Consumption of Cognitive Services APIs

    2:29

    Configure Integration with Azure Services

    1:55

    Configure Prerequisite Components to Allow Connectivity with Bot Framework

    2:44

    Implement Azure Search in a Solution

    2:43

    Detecting Named Entities in Text Using the .NET SDK

    1:00:00 Hands-On Lab

    Extracting Key Phrases from Text Using the .NET SDK

    1:00:00 Hands-On Lab
  • Chapter 3 5 Lessons Monitor and Evaluate the AI Environment 16:48

    Identify the Differences Between KPIs, Reported Metrics, and Root Causes of the Differences

    2:31

    Identify the Differences Between Expected and Actual Workflow Throughput

    3:18

    Maintain the AI Solution for Continuous Improvement

    3:00

    Monitor AI Components for Availability

    3:16

    Recommend Changes to an AI Solution Based on Performance Data

    4:43
  • Chapter 4 1 Lesson Where do you go from here? 0:30

    Good Work! Now: on to the last Course Segment!

    0:30

What are Hands-on Labs

What's the difference between theoretical knowledge and real skills? Practical real-world experience. That's where Hands-on Labs come in! Hands-on Labs are guided, interactive experiences that help you learn and practice real-world scenarios in real cloud environments. Hands-on Labs are seamlessly integrated in courses, so you can learn by doing.

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