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URL: https://www.coursera.org/learn/automate-optimize-and-maintain-ai-systems

⇱ Automate, Optimize, and Maintain AI Systems | Coursera


Automate, Optimize, and Maintain AI Systems

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Automate, Optimize, and Maintain AI Systems

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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

  • Strategic patching balances security urgency with system stability using dependency mapping and optimized maintenance windows.

  • MTTR trends expose resilience patterns and act as early warning signals for infrastructure health issues.

  • Automated maintenance playbooks enable self-healing systems, cutting manual effort while improving speed and consistency

  • Strong AI operations rely on security, dev, and ops teams collaborating to maintain performance and compliance.

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Recently updated!

January 2026

Assessments

6 assignmentsΒΉ

AI Graded see disclaimer
Taught in English

Build your subject-matter expertise

This course is part of the AI Systems Reliability & Security 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

The failure of AI systems can cost enterprises millions in downtime and lost opportunities. This course equips ML and AI professionals with the critical operational skills to keep generative AI systems running at peak performance.

You'll master the art of strategic patch management that balances urgent security requirements with business continuity needs. Learn to analyze Mean Time to Recovery (MTTR) patterns to build resilient systems that bounce back faster from failures. Most importantly, you'll create intelligent automation playbooks that detect issues before they impact users and execute remediation tasks without human intervention. By completing this course, you'll be able to coordinate complex maintenance windows across teams, run sophisticated analytics on incident data to identify automation opportunities, and build self-healing Ansible playbooks that restart stuck processes and update operational runbooks. This course uniquely combines strategic planning with hands-on automation, ensuring your AI systems maintain 99.9% uptime while meeting security compliance requirements. To be successful in this course, you should have experience with system monitoring, basic scripting knowledge, and familiarity with enterprise infrastructure operations.

Learners will master strategic patch management approaches that optimize security posture while maintaining business continuity for AI systems infrastructure. It bridges theoretical frameworks with practical, enterprise-scale implementation techniques.

What's included

3 videos1 reading2 assignments

3 videosβ€’Total 13 minutes
  • Why Strategic Patch Management Can Make or Break AI Operationsβ€’3 minutes
  • Analyzing Security vs. Availability Trade-offs in AI Systemsβ€’6 minutes
  • Building Patch Priority Assessment Matricesβ€’4 minutes
1 readingβ€’Total 10 minutes
  • Foundations of Strategic Patch Management for AI Infrastructureβ€’10 minutes
2 assignmentsβ€’Total 18 minutes
  • Enterprise Patch Management Scenario Analysisβ€’15 minutes
  • Strategic Patch Management Knowledge Checkβ€’3 minutes

Learners will master MTTR trend analysis techniques that identify system resilience patterns and enable proactive infrastructure improvements for AI operations.

What's included

3 videos1 reading1 assignment

3 videosβ€’Total 13 minutes
  • How MTTR Analysis Transformed Netflix's Infrastructure Reliabilityβ€’3 minutes
  • Calculating and Interpreting MTTR Metrics for AI Systemsβ€’8 minutes
  • Creating MTTR Dashboards and Trend Analysis Reportsβ€’2 minutes
1 readingβ€’Total 10 minutes
  • MTTR Fundamentals and Resilience Engineering Principlesβ€’10 minutes
1 assignmentβ€’Total 3 minutes
  • MTTR Analysis and Resilience Assessmentβ€’3 minutes

Learners will develop comprehensive Ansible playbooks with automated triggers and notification workflows that enable self-healing AI systems infrastructure through proactive monitoring response.

What's included

2 videos1 reading3 assignments

2 videosβ€’Total 12 minutes
  • Designing Playbook Architecture for Self-Healing AI Systemsβ€’8 minutes
  • Building Your First Automated Maintenance Playbookβ€’5 minutes
1 readingβ€’Total 10 minutes
  • Ansible Fundamentals for AI Operations Automationβ€’10 minutes
3 assignmentsβ€’Total 38 minutes
  • AI Operations Automation Mastery Assessmentβ€’15 minutes
  • Enterprise Playbook Development for AI Infrastructureβ€’20 minutes
  • Automated Maintenance Playbook Mastery Checkβ€’3 minutes

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Instructor

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,

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