AI-900: Azure AI Fundamentals: Anomaly Detection


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level


Overview/Description
Anomaly detection can be a critical part of almost any business and can be used for fraud detection, identifying failures, and noticing unusual patterns in logs, records, or any time series based data. In this course, you’ll learn the purpose and uses for anomaly detection and how AI anomaly detection can be used to identify unusual patterns, failures, and fraud. You’ll then learn about the challenges of detecting anomalies in real world situations and how AI-based anomaly detection can be used to mitigate those challenges. Finally, you’ll learn how to build, configure, deploy, and test the Azure Anomaly Detection service to create anomaly detection services you can use in real world scenarios. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.

Expected Duration (hours)
1.5

Lesson Objectives

AI-900: Azure AI Fundamentals: Anomaly Detection

  • discover the key concepts covered in this course
  • describe the purpose and uses for anomaly detection and how AI anomaly detection can be used to identify unusual patterns, failures, and fraud
  • identify the challenges of detecting anomalies in real world situations and how AI-based anomaly detection can be used to mitigate those challenges
  • describe how the Azure Anomaly Detector Cognitive Service provides the tools and customization for adding anomaly detection to your apps and services
  • navigate the Azure Anomaly Detector service web site and interfaces used to start an anomaly detection service you can use in the real world
  • create an Azure Anomaly Detection service project and view some of the configuration options
  • integrate a time series based dataset into an Azure Anomaly Detection service project
  • train a best-fitting detection model on the time series data to get the best anomaly detection reporting
  • deploy the Azure Anomaly Detector service using an API key for external apps to collect anomaly reports
  • test and evaluate the Azure Anomaly Detector service using external data to simulate anomalies
  • customize the Azure Anomaly Detection service for sensitivity, detection, and other parameters
  • summarize the key concepts covered in this course

    • Course Number:
    it_clazaif_06_enus

    Expertise Level
    Beginner