DevOps and AI on AWS: Upgrading Apps with Generative AI

Ends tomorrow! Save 40% on your access to 10,000+ programs and make a real impact in your career. Save now.

DevOps and AI on AWS: Upgrading Apps with Generative AI

This course is part of DevOps and AI on AWS Specialization

Instructors: Russell Sayers

6,253 already enrolled

Included with Learn more

Ask Coursera

2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Understanding observability and its importance in application development
Practical use cases for AIOps in real-world scenarios
Key components of AIOps, including anomaly detection, predictive analysis, automated root cause analysis, and remediation

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

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

Explore the intersection of DevOps and Generative AI on AWS in this hands-on course. Learn to enhance existing applications with powerful AI features using Amazon Bedrock's large language models (LLMs). You'll gain practical experience in implementing customized text generation, mastering prompt engineering, and applying advanced techniques like fine-tuning and Retrieval Augmented Generation (RAG).

We focus on essential DevOps practices, guiding you through the process of coding, building, and testing an application upgraded with generative AI capabilities. You'll learn to integrate these AI features seamlessly into your software development lifecycle, ensuring smooth deployment and maintenance. The course also sharpens crucial developer skills. We highlight how to enable effective source control management, enabling efficient collaboration and version control in your projects. Additionally, you'll master unit testing to ensure the reliability of your applications.By the end of this course, you'll be equipped to modernize applications using generative AI, implement proven DevOps practices, and leverage AWS' AI services. Whether you're a developer expanding your AI expertise or a DevOps professional incorporating AI technologies, this course provides the tools to excel in the evolving landscape of software development and artificial intelligence. Join us to transform your applications and development practices with the power of generative AI on AWS.

This module introduces the TravelGuideAI application, a travel guide application that will be upgraded with generative AI features. It covers the course overview, source code repositories, and the tools and services required for developing generative AI applications, such as Amazon Bedrock, prompt engineering, and Amazon Q Developer.

What's included

10 videos4 readings2 assignments1 app item1 plugin

10 videosTotal 57 minutes

Welcome to the Course8 minutes
Meet the Instructors2 minutes
Module 1 Introduction5 minutes
Travel Guide Example Application6 minutes
Source Code Repositories7 minutes
Product Planning4 minutes
Generative AI with Amazon Bedrock7 minutes
Prompt Engineering5 minutes
Web Hosting with Amazon EC29 minutes
Amazon Q Developer5 minutes

4 readingsTotal 36 minutes

Pre-Course Survey1 minute
Course Roadmap5 minutes
Source Code Repositories10 minutes
Amazon Bedrock and Prompt Engineering20 minutes

2 assignmentsTotal 50 minutes

Pre-Assessment30 minutes
Module 1 Quiz20 minutes

1 app itemTotal 60 minutes

Introducing the TravelGuideAI App60 minutes

1 pluginTotal 10 minutes

Pre-Course Survey10 minutes

This module focuses on integrating generative AI features into the TravelGuideAI application using Amazon Bedrock. It covers branching strategies, upgrading the application, deploying the updated application, and exploring advanced topics like customizing Amazon Bedrock models, responsible AI, and the need for DevOps practices.

What's included

10 videos3 readings2 assignments1 app item1 plugin

10 videosTotal 57 minutes

Module 2 Introduction1 minute
Branching Strategies7 minutes
Upgrading the Travel Guide application5 minutes
Deploying the Travel Guide application6 minutes
Customizing an Amazon Bedrock Model8 minutes
Amazon Bedrock Knowledge Bases10 minutes
A closer look at Amazon Bedrock7 minutes
Responsible AI6 minutes
The Need for DevOps5 minutes
Course Closing2 minutes

3 readingsTotal 36 minutes

Amazon Bedrock20 minutes
Amazon Bedrock and Responsible AI15 minutes
Post-Course Survey1 minute

2 assignmentsTotal 80 minutes

Module 2 Quiz20 minutes
Final Assessment60 minutes

1 app itemTotal 60 minutes

Build and deploy the TravelGuideAI App60 minutes

1 pluginTotal 10 minutes

Post-Course Survey10 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Russell Sayers

Amazon Web Services

21 Courses140,704 learners

Offered by

Amazon Web Services

Explore more from Cloud Computing

Amazon Web Services
DevOps and AI on AWS: CI/CD for Generative AI Applications
Course
Status: Free Trial
Whizlabs
AWS: Generative AI & Bedrock
Course
Status: Preview
Whizlabs
Generative AI for AWS Cloud Engineers
Course
Status: Preview
Amazon Web Services
AWS Generative AI Essentials
Course

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

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.