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⇱ DevOps and AI on AWS: AIOps | Coursera


DevOps and AI on AWS: AIOps

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DevOps and AI on AWS: AIOps

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Gain insight into a topic and learn the fundamentals.
4.9

10 reviews

Beginner level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
4.9

10 reviews

Beginner level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand AIOps and its role in addressing operational challenges.

  • Implement AI-driven monitoring to reduce alarm fatigue and information overload.

Details to know

Shareable certificate

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Assessments

4 assignments

Taught in English

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This course is part of the DevOps and AI on AWS 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 2 modules in this course

In this course, we focus on how we can use AI techniques to improve our DevOps operational efficiency. We have added AI features to our applications, now it’s time to do the same for our DevOps processes. With our travel guide now in production, let’s dive into the challenges we’ll face as we scale – and how we can mitigate those challenges. As we scale, we’ll undoubtedly experience some monitoring alarms as we scan our development environment. In this scenario, information overload without the right tools can leave you stuck: you either have too much data with no clear direction on what’s actionable, or, in some cases, you don’t have enough of the right information and visibility to make informed decisions. That’s where AIOps can make a huge difference. AIOps is the process of using machine learning techniques to solve operational problems. The goal of AIOps is to reduce human intervention in the IT operations processes, reduce operational incidents, and improve your applications. Let’s learn how AIOps can help streamline operations, improve the way we monitor applications, and automate responses to common problems.

This module introduces the concept of AIOps (Artificial Intelligence for IT Operations) and how it can enhance observability and address specific challenges in DevOps processes. It covers various AWS services and tools that leverage AI/ML to detect anomalies, identify performance issues, and improve operational efficiency.

What's included

7 videos6 readings2 assignments1 app item1 plugin

7 videosβ€’Total 32 minutes
  • Introduction to the Courseβ€’6 minutes
  • Module 1 Introductionβ€’1 minute
  • Observabilityβ€’5 minutes
  • AIOps Fundamentalsβ€’5 minutes
  • Amazon CloudWatch Anomaly Detectionβ€’6 minutes
  • AWS X-Ray Insightsβ€’3 minutes
  • Amazon DevOps Guruβ€’6 minutes
6 readingsβ€’Total 41 minutes
  • Welcome to the Courseβ€’5 minutes
  • Pre-Course Surveyβ€’1 minute
  • Course Roadmapβ€’5 minutes
  • Observabilityβ€’5 minutes
  • AI Ops Fundamentalsβ€’10 minutes
  • Amazon Devops Guruβ€’15 minutes
2 assignmentsβ€’Total 50 minutes
  • Module 1 Quizβ€’30 minutes
  • Pre-Assessmentβ€’20 minutes
1 app itemβ€’Total 60 minutes
  • Instrument the Application and View Traces on X-Rayβ€’60 minutes
1 pluginβ€’Total 10 minutes
  • Pre-Course Surveyβ€’10 minutes

This module focuses on leveraging AI/ML to enhance the developer experience and improve code quality and security. It covers AWS services like Amazon CodeGuru and Amazon CodeCatalyst, which use AI/ML to provide intelligent code reviews, identify vulnerabilities, and offer personalized recommendations.

What's included

3 videos3 readings2 assignments1 plugin

3 videosβ€’Total 10 minutes
  • Module 2 Introductionβ€’1 minute
  • Amazon Q Developer Security Scanningβ€’5 minutes
  • Course Closingβ€’4 minutes
3 readingsβ€’Total 31 minutes
  • Amazon Q Developer Security Scanningβ€’15 minutes
  • Post-Course Surveyβ€’1 minute
  • Glossaryβ€’15 minutes
2 assignmentsβ€’Total 90 minutes
  • Self-Reflectionβ€’30 minutes
  • Post Assessmentβ€’60 minutes
1 pluginβ€’Total 10 minutes
  • Post-Course Surveyβ€’10 minutes

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Instructors

Amazon Web Services
21 Coursesβ€’139,316 learners

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Reviewed on May 13, 2025

I can understand more about AWS services that they can apply in GenAI projects. This course can help me to work in my project.

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.

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