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Monitor, Scale and Backup Your AI App

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Coursera

Monitor, Scale and Backup Your AI App

LearningMate

Instructor: LearningMate

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

2 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Effectively monitor, scale, and back up AI applications to ensure optimal performance and meet service level agreements (SLAs).

Details to know

Shareable certificate

Add to your LinkedIn profile

Recently updated!

January 2026

Assessments

5 assignments¹

AI Graded see disclaimer
Taught in English

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Build your subject-matter expertise

This course is part of the Build AI Apps Like a Pro: No-Code Tools for Beginners Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

This module focuses on establishing a foundation for operational excellence by teaching learners how to monitor AI applications proactively. You will learn to identify key performance indicators and use platform analytics to set up real-time dashboards and automated alerts. This ensures that potential issues are caught and addressed before they impact users, drawing on real-world practices like those used with Azure AI Foundry.

What's included

2 videos1 reading1 assignment

In this module, learners will discover how to ensure their AI applications can handle fluctuating demand. You will learn to analyze performance metrics to make intelligent scaling decisions, balancing cost and responsiveness. The module covers different scaling strategies and how to apply them to meet latency requirements and service level agreements, using the Azure AI Search and Datadog integration as a guiding example.

What's included

2 videos1 reading2 assignments

This final module addresses the critical need for disaster recovery and data protection. Learners will learn to evaluate and design backup and restore procedures that align with business requirements like Recovery Point Objectives (RPO) and Recovery Time Objectives (RTO). The module emphasizes the importance of regular testing and validation to ensure compliance and minimize downtime, incorporating insights from the CAST AI and Corptec case studies.

What's included

2 videos1 reading2 assignments

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Instructor

LearningMate
Coursera
97 Courses1,674 learners

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Frequently asked questions

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.