Generative AI for DevOps: ChatGPT, Copilot, AWS & CI/CD [9/2026, ENG]
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Files
| 01. Introduction to AI in DevOps | |||
| 1. About instructor.mp4 | 1.49 MB | ||
| 1. About instructor.vtt | 1.17 KB | ||
| 2. What is AI in DevOps.mp4 | 4.28 MB | ||
| 2. What is AI in DevOps.vtt | 3.95 KB | ||
| 3. Where AI brings the most value in DevOps.mp4 | 7.02 MB | ||
| 3. Where AI brings the most value in DevOps.vtt | 4.5 KB | ||
| 4. Tools used in this course (ChatGPT, GitHub Copilot).mp4 | 10.7 MB | ||
| 4. Tools used in this course (ChatGPT, GitHub Copilot).vtt | 3.49 KB | ||
| 02. AI in Automation and Scripting | |||
| 1. Building a sample application (project setup).mp4 | 48.25 MB | ||
| 1. Building a sample application (project setup).vtt | 12.21 KB | ||
| 2. Generating Bash scripts with AI.mp4 | 34.7 MB | ||
| 2. Generating Bash scripts with AI.vtt | 10.26 KB | ||
| 3. Creating YAML configurations with AI.mp4 | 39.84 MB | ||
| 3. Creating YAML configurations with AI.vtt | 9.19 KB | ||
| 4. Automating daily DevOps tasks with AI.mp4 | 51.03 MB | ||
| 4. Automating daily DevOps tasks with AI.vtt | 12.16 KB | ||
| 5. Best prompts for script generation.mp4 | 8.92 MB | ||
| 5. Best prompts for script generation.vtt | 7.4 KB | ||
| 03. AI in CICD Pipelines | |||
| 1. Introduction to CICD with AI.mp4 | 8.71 MB | ||
| 1. Introduction to CICD with AI.vtt | 3.79 KB | ||
| 2. Real-world AI DevOps workflow.mp4 | 31.16 MB | ||
| 2. Real-world AI DevOps workflow.vtt | 7.56 KB | ||
| 3. Generating pipelines (GitHub Actions) with AI.mp4 | 58.89 MB | ||
| 3. Generating pipelines (GitHub Actions) with AI.vtt | 14.09 KB | ||
| 4. Optimizing pipelines using AI.mp4 | 73.54 MB | ||
| 4. Optimizing pipelines using AI.vtt | 13.82 KB | ||
| 5. Debugging CICD errors with AI.mp4 | 52.7 MB | ||
| 5. Debugging CICD errors with AI.vtt | 11.56 KB | ||
| 04. AI in Infrastructure as Code | |||
| 1. Introduction to Infrastructure as Code.mp4 | 14.2 MB | ||
| 1. Introduction to Infrastructure as Code.vtt | 3.93 KB | ||
| 2. Generating Terraform configurations with AI.mp4 | 93.22 MB | ||
| 2. Generating Terraform configurations with AI.vtt | 17.87 KB | ||
| 3. Creating infrastructure (VM, storage) with AI.mp4 | 78.1 MB | ||
| 3. Creating infrastructure (VM, storage) with AI.vtt | 14.12 KB | ||
| 4. Refactoring and improving IaC code.mp4 | 38.87 MB | ||
| 4. Refactoring and improving IaC code.vtt | 6.69 KB | ||
| 5. Best prompts for IaC.mp4 | 9.57 MB | ||
| 5. Best prompts for IaC.vtt | 5.53 KB | ||
| 05. AI in Docker and Containers | |||
| 1. Introduction to Docker in DevOps.mp4 | 14.81 MB | ||
| 1. Introduction to Docker in DevOps.vtt | 3.76 KB | ||
| 2. Generating a Dockerfile with AI.mp4 | 45.33 MB | ||
| 2. Generating a Dockerfile with AI.vtt | 11.62 KB | ||
| 3. Optimizing Dockerfiles using AI.mp4 | 37.2 MB | ||
| 3. Optimizing Dockerfiles using AI.vtt | 8.26 KB | ||
| 4. Debugging Docker builds with AI.mp4 | 24.35 MB | ||
| 4. Debugging Docker builds with AI.vtt | 6.09 KB | ||
| 06. AI in Monitoring and Log Analysis | |||
| 1. Introduction to monitoring in DevOps.mp4 | 7.71 MB | ||
| 1. Introduction to monitoring in DevOps.vtt | 3.69 KB | ||
| 2. Log analysis using AI.mp4 | 51.91 MB | ||
| 2. Log analysis using AI.vtt | 12.03 KB | ||
| 3. Root cause analysis with AI.mp4 | 20.53 MB | ||
| 3. Root cause analysis with AI.vtt | 4.48 KB | ||
| 4. Interpreting errors and alerts.mp4 | 21.37 MB | ||
| 4. Interpreting errors and alerts.vtt | 7.22 KB | ||
| 07. Practical Use Cases of AI in DevOps | |||
| 1. Automating deployments with AI.mp4 | 41.08 MB | ||
| 1. Automating deployments with AI.vtt | 7.96 KB | ||
| 2. Automating rollbacks with AI.mp4 | 88.11 MB | ||
| 2. Automating rollbacks with AI.vtt | 16.01 KB | ||
| 3. Generating technical documentation with AI.mp4 | 31.57 MB | ||
| 3. Generating technical documentation with AI.vtt | 7.75 KB | ||
| 4. Creating runbooks using AI.mp4 | 18.64 MB | ||
| 4. Creating runbooks using AI.vtt | 4.61 KB | ||
| 08. Final Project – AI DevOps in Practice | |||
| 1. Preparing AWS EC2 for deployment.mp4 | 82.45 MB | ||
| 1. Preparing AWS EC2 for deployment.vtt | 13.04 KB | ||
| 2. Generating the application with AI.mp4 | 28.55 MB | ||
| 2. Generating the application with AI.vtt | 8.58 KB | ||
| 3. Creating and optimizing the Dockerfile with AI.mp4 | 29.4 MB | ||
| 3. Creating and optimizing the Dockerfile with AI.vtt | 7.35 KB | ||
| 4. Pushing the project to GitHub.mp4 | 17.6 MB | ||
| 4. Pushing the project to GitHub.vtt | 4.06 KB | ||
| 5. Creating GitHub Actions deployment workflow.mp4 | 22.5 MB | ||
| 5. Creating GitHub Actions deployment workflow.vtt | 6.01 KB | ||
| 6. Configuring GitHub Secrets for EC2 deployment.mp4 | 29.18 MB | ||
| 6. Configuring GitHub Secrets for EC2 deployment.vtt | 6.14 KB | ||
| 7. Running the final deployment step by step.mp4 | 77.85 MB | ||
| 7. Running the final deployment step by step.vtt | 13.69 KB | ||
| 10. Hands-on Labs AWS & AI (Optional Advanced Section) | |||
| 1. Introduction to Hands-on Labs.mp4 | 20.79 MB | ||
| 1. Introduction to Hands-on Labs.vtt | 2.38 KB | ||
| 2. Lab 1 API Testing with AWS Lambda & API Gateway.mp4 | 67 MB | ||
| 2. Lab 1 API Testing with AWS Lambda & API Gateway.vtt | 9.9 KB | ||
| 3. Lab 2 Working with Test Data in Amazon S3.mp4 | 97.91 MB | ||
| 3. Lab 2 Working with Test Data in Amazon S3.vtt | 19.1 KB | ||
| 4. Lab 3 Testing an AI-like API Endpoint.mp4 | 50.26 MB | ||
| 4. Lab 3 Testing an AI-like API Endpoint.vtt | 8.68 KB | ||
| 5. Lab Files & Resources.html | 71 B | ||
| 5. Labs-Files.zip | 6.65 KB | ||
| 11. Hands-on Labs II AWS & AI (Optional Advanced Section) | |||
| 1. Introduction to the Cloud Document Portal Project.mp4 | 25.02 MB | ||
| 1. Introduction to the Cloud Document Portal Project.vtt | 4.7 KB | ||
| 2. Github-copilot.txt | 44 B | ||
| 2. Preparing the AWS Environment and Deploying the Application.mp4 | 150.89 MB | ||
| 2. Preparing the AWS Environment and Deploying the Application.vtt | 31.51 KB | ||
| 3. Lab 1 – Applying Test Design Techniques.mp4 | 18.71 MB | ||
| 3. Lab 1 – Applying Test Design Techniques.vtt | 3.52 KB | ||
| 4. Lab 2 – Executing Tests and Reporting Defects.mp4 | 20.49 MB | ||
| 4. Lab 2 – Executing Tests and Reporting Defects.vtt | 3.77 KB | ||
| 5. Lab 3 – Applying Risk-Based Testing.mp4 | 10.09 MB | ||
| 5. Lab 3 – Applying Risk-Based Testing.vtt | 2.08 KB | ||
| 12. Hands-on Labs III AWS & AI (Optional Advanced Section) | |||
| 1. Introduction to ShopLab.mp4 | 17.86 MB | ||
| 1. Introduction to ShopLab.vtt | 4.27 KB | ||
| 2. Deploying ShopLab on AWS.mp4 | 27.8 MB | ||
| 2. Deploying ShopLab on AWS.vtt | 6.39 KB | ||
| 2. template.yaml | 89.8 KB | ||
| 13. Practical Tasks | |||
| 1.1 Assignment-Practical Task 1.html | 3.96 KB | ||
| 2.2 Assignment-Practical Task 2.html | 4.31 KB | ||
| 14. Hands-on Coding Exercises AI-Assisted DevOps | |||
| 1. About the AI-Assisted DevOps Coding Exercises.html | 599 B | ||
| 10.9 Generate a Deployment Summary.html | 9.16 KB | ||
| 11.10 Analyze Production Incidents.html | 10.61 KB | ||
| 2.1 Check Server Health Status.html | 6.06 KB | ||
| 3.2 Detect Failed Services.html | 6.74 KB | ||
| 4.3 Find Errors in Application Logs.html | 7.14 KB | ||
| 5.4 Count Log Events by Severity.html | 7.72 KB | ||
| 6.5 Validate Required Environment Variables.html | 8 KB | ||
| 7.6 Analyze Server Resource Usage.html | 8.69 KB | ||
| 8.7 Identify Failed CICD Jobs.html | 7.82 KB | ||
| 9.8 Implement Deployment Retry Logic.html | 8.16 KB | ||
| 15. Theoretical Test | |||
| 1.1 Solve the theoretical test.html | 20.18 KB | ||
| 16. Additional Resources | |||
| 1. Downloadable Files.html | 64 B | ||
| 1. app.zip | 186.64 KB | ||
| 1. aws-app.zip | 64.71 KB | ||
| 2. Course Wrap-Up and Special Reward.mp4 | 5.55 MB | ||
| 2. Course Wrap-Up and Special Reward.vtt | 752 B | ||
| 3. Reward for Completing the Course.html | 788 B |
Description
Обучающие видео » Компьютерные видеоуроки и обучающие интерактивные DVD » Machine/Deep Learning, Neural Networks
Generative AI for DevOps: ChatGPT, Copilot, AWS & CI/CD
Год выпуска: 9/2026
Производитель: Udemy
Сайт производителя: https://www.udemy.com/course/generative-ai-devops-engineers/
Автор: Rafał Podraza
Продолжительность: 5h 14m
Тип раздаваемого материала: Видеоурок
Язык: Английский
Описание: This practical, hands-on course teaches DevOps engineers, developers, cloud engineers, and IT professionals how to use Generative AI, ChatGPT, and GitHub Copilot to automate, optimize, and improve modern DevOps workflows—not as a theoretical AI course, but with real examples you can immediately apply. You will learn how AI supports DevOps workflows, how to use ChatGPT and Copilot in projects, generate Bash scripts and YAML configurations, automate repetitive tasks, build and optimize CI/CD pipelines, debug CI/CD issues, generate Terraform configurations, improve Infrastructure as Code, create and optimize Dockerfiles, analyze logs, alerts, and monitoring data, automate deployments and rollbacks, generate technical documentation and runbooks, apply prompt engineering for DevOps scenarios, and follow best practices for responsible and efficient AI usage.
The course includes a complete practical project where you prepare an AWS EC2 environment, generate an application with AI, create and optimize a Dockerfile, push the project to GitHub, build a GitHub Actions deployment workflow, configure GitHub Secrets, and perform a complete deployment step by step. It also includes practical tasks and role-play exercises for real DevOps and AI scenarios, plus a theoretical test to validate your understanding. It is aimed at DevOps engineers wanting to use AI daily, developers working with CI/CD and cloud, cloud and infrastructure engineers, automation engineers interested in AI-driven workflows, IT professionals improving productivity, and beginners interested in practical AI applications in DevOps, with no previous AI experience required since all concepts are explained step by step in a beginner-friendly way. The course focuses on practical DevOps use cases, real-world examples and workflows, hands-on exercises and deployment scenarios, and modern AI tools used in the industry, helping you save time, automate repetitive work, and improve DevOps efficiency. The course contains the use of artificial intelligence.
[spoiler="Содержание"]
01. Introduction to AI in DevOps
1. About instructor (01:00)
2. What is AI in DevOps (02:56)
3. Where AI brings the most value in DevOps (02:48)
4. Tools used in this course (ChatGPT, GitHub Copilot) (02:32)
02. AI in Automation and Scripting
1. Building a sample application (project setup) (09:00)
2. Generating Bash scripts with AI (07:18)
3. Creating YAML configurations with AI (07:17)
4. Automating daily DevOps tasks with AI (08:49)
5. Best prompts for script generation (04:30)
03. AI in CICD Pipelines
1. Introduction to CICD with AI (03:25)
2. Real-world AI DevOps workflow (05:20)
3. Generating pipelines (GitHub Actions) with AI (10:37)
4. Optimizing pipelines using AI (10:42)
5. Debugging CICD errors with AI (09:29)
04. AI in Infrastructure as Code
1. Introduction to Infrastructure as Code (02:54)
2. Generating Terraform configurations with AI (12:13)
3. Creating infrastructure (VM, storage) with AI (10:54)
4. Refactoring and improving IaC code (05:23)
5. Best prompts for IaC (04:22)
05. AI in Docker and Containers
1. Introduction to Docker in DevOps (03:09)
2. Generating a Dockerfile with AI (09:14)
3. Optimizing Dockerfiles using AI (06:38)
4. Debugging Docker builds with AI (04:38)
06. AI in Monitoring and Log Analysis
1. Introduction to monitoring in DevOps (03:00)
2. Log analysis using AI (09:03)
3. Root cause analysis with AI (03:33)
4. Interpreting errors and alerts (05:31)
07. Practical Use Cases of AI in DevOps
1. Automating deployments with AI (06:07)
2. Automating rollbacks with AI (12:21)
3. Generating technical documentation with AI (06:03)
4. Creating runbooks using AI (03:39)
08. Final Project – AI DevOps in Practice
1. Preparing AWS EC2 for deployment (10:49)
2. Generating the application with AI (05:24)
3. Creating and optimizing the Dockerfile with AI (05:46)
4. Pushing the project to GitHub (03:10)
5. Creating GitHub Actions deployment workflow (04:25)
6. Configuring GitHub Secrets for EC2 deployment (04:45)
7. Running the final deployment step by step (10:27)
10. Hands-on Labs AWS & AI (Optional Advanced Section)
1. Introduction to Hands-on Labs (02:05)
2. Lab 1 API Testing with AWS Lambda & API Gateway (09:05)
3. Lab 2 Working with Test Data in Amazon S3 (12:59)
4. Lab 3 Testing an AI-like API Endpoint (07:06)
11. Hands-on Labs II AWS & AI (Optional Advanced Section)
1. Introduction to the Cloud Document Portal Project (03:55)
2. Preparing the AWS Environment and Deploying the Application (24:08)
3. Lab 1 – Applying Test Design Techniques (02:35)
4. Lab 2 – Executing Tests and Reporting Defects (02:58)
5. Lab 3 – Applying Risk-Based Testing (01:30)
12. Hands-on Labs III AWS & AI (Optional Advanced Section)
1. Introduction to ShopLab (03:18)
2. Deploying ShopLab on AWS (04:15)
16. Additional Resources
2. Course Wrap-Up and Special Reward (00:33)
[/spoiler]
Файлы примеров: не предусмотрены
Формат видео: MP4
Видео: AVC, 1280x720, 16:9, 30fps, 667kbps
Аудио: AAC, 44.1Hz, 125kbps, stereo
[spoiler="Скриншоты"]
[/spoiler]
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