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[center]![[Obrazek: 40bbb0410ed64b00409a12db1cdf0442.jpg]](https://i126.fastpic.org/big/2025/1225/42/40bbb0410ed64b00409a12db1cdf0442.jpg)
Coderabbit Ai: Automated Code Reviews
Published 12/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.57 GB
[/center] | Duration: 1h 49m
GitHub pull requests, Cursor IDE, CI/CD pipelines, YAML config, and real-world team workflows
What you'll learn
Understand how AI-powered code reviews work and where CodeRabbit fits in modern development workflows
Set up and configure CodeRabbit using .coderabbit.yml for different project types
Automatically review GitHub pull requests using AI
Use natural-language commands to ask CodeRabbit to explain, summarize, and suggest fixes in PRs
Detect bugs, security issues, code smells, and best-practice violations early
Enforce CodeRabbit as a mandatory reviewer using GitHub branch protection rules
Integrate CodeRabbit into CI/CD pipelines as a quality gate
Reduce manual review time while improving code consistency and reliability
Apply CodeRabbit in real-world team and production workflows
Requirements
A GitHub account to follow along with hands-on demos
Basic knowledge of using a code editor (VS Code or Cursor is helpful)
Willingness to experiment with AI tools in real projects
Description
Code reviews are one of the most important parts of software development, but they are also one of the biggest bottlenecks. Manual reviews take time, slow down pull requests, and depend heavily on senior developers being available. This course shows you how to solve that problem using CodeRabbit AI.In this course, you will learn how to use CodeRabbit AI to automate code reviews, identify bugs early, improve code quality, and speed up pull request approvals without sacrificing standards. You will see how modern development teams use AI to support developers instead of replacing them.The course is fully hands-on and based on real workflows. You will work with real GitHub pull requests and see how CodeRabbit reviews code automatically. You will learn how to configure CodeRabbit using YAML, customize its behavior, and control how strict or detailed the reviews should be. We also cover how to integrate CodeRabbit with Cursor IDE so developers can understand and fix issues faster inside their editor.You will also learn how to add CodeRabbit as a required review step in CI/CD pipelines. This ensures that no code gets merged without automated checks, helping teams maintain consistent quality across projects. Real-world examples show how messy code, security issues, performance problems, and best-practice violations are detected and explained clearly by AI.The course includes practical demonstrations inspired by real company workflows, showing how teams reduce review time, increase merge speed, and improve collaboration between junior and senior developers.What you will learn in this course:How AI-powered code reviews work in real projectsHow to use CodeRabbit with GitHub pull requestsHow to configure CodeRabbit using YAMLHow to integrate CodeRabbit with Cursor IDEHow to enforce automated reviews using CI/CD pipelinesHow to review, fix, and merge code faster with confidenceThis course is ideal for solo developers, startup teams, agencies, and engineering leads who want faster reviews and better quality. By the end of the course, you will be confident using CodeRabbit AI to review, fix, approve, and ship code faster every day, with less manual effort and better results overall.
Software developers who want to improve code quality using AI,Frontend, backend, and full-stack developers working with GitHub,Startup teams looking to speed up pull request reviews,Engineering teams that want consistent, automated code reviews,Tech leads and architects responsible for code quality and standards,DevOps and CI/CD engineers adding quality gates to pipelines,Solo developers who want enterprise-level code reviews without extra cost,Anyone curious about using AI in real-world development workflows
Coderabbit Ai: Automated Code Reviews
Published 12/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.57 GB
[/center] | Duration: 1h 49m
GitHub pull requests, Cursor IDE, CI/CD pipelines, YAML config, and real-world team workflows
What you'll learn
Understand how AI-powered code reviews work and where CodeRabbit fits in modern development workflows
Set up and configure CodeRabbit using .coderabbit.yml for different project types
Automatically review GitHub pull requests using AI
Use natural-language commands to ask CodeRabbit to explain, summarize, and suggest fixes in PRs
Detect bugs, security issues, code smells, and best-practice violations early
Enforce CodeRabbit as a mandatory reviewer using GitHub branch protection rules
Integrate CodeRabbit into CI/CD pipelines as a quality gate
Reduce manual review time while improving code consistency and reliability
Apply CodeRabbit in real-world team and production workflows
Requirements
A GitHub account to follow along with hands-on demos
Basic knowledge of using a code editor (VS Code or Cursor is helpful)
Willingness to experiment with AI tools in real projects
Description
Code reviews are one of the most important parts of software development, but they are also one of the biggest bottlenecks. Manual reviews take time, slow down pull requests, and depend heavily on senior developers being available. This course shows you how to solve that problem using CodeRabbit AI.In this course, you will learn how to use CodeRabbit AI to automate code reviews, identify bugs early, improve code quality, and speed up pull request approvals without sacrificing standards. You will see how modern development teams use AI to support developers instead of replacing them.The course is fully hands-on and based on real workflows. You will work with real GitHub pull requests and see how CodeRabbit reviews code automatically. You will learn how to configure CodeRabbit using YAML, customize its behavior, and control how strict or detailed the reviews should be. We also cover how to integrate CodeRabbit with Cursor IDE so developers can understand and fix issues faster inside their editor.You will also learn how to add CodeRabbit as a required review step in CI/CD pipelines. This ensures that no code gets merged without automated checks, helping teams maintain consistent quality across projects. Real-world examples show how messy code, security issues, performance problems, and best-practice violations are detected and explained clearly by AI.The course includes practical demonstrations inspired by real company workflows, showing how teams reduce review time, increase merge speed, and improve collaboration between junior and senior developers.What you will learn in this course:How AI-powered code reviews work in real projectsHow to use CodeRabbit with GitHub pull requestsHow to configure CodeRabbit using YAMLHow to integrate CodeRabbit with Cursor IDEHow to enforce automated reviews using CI/CD pipelinesHow to review, fix, and merge code faster with confidenceThis course is ideal for solo developers, startup teams, agencies, and engineering leads who want faster reviews and better quality. By the end of the course, you will be confident using CodeRabbit AI to review, fix, approve, and ship code faster every day, with less manual effort and better results overall.
Software developers who want to improve code quality using AI,Frontend, backend, and full-stack developers working with GitHub,Startup teams looking to speed up pull request reviews,Engineering teams that want consistent, automated code reviews,Tech leads and architects responsible for code quality and standards,DevOps and CI/CD engineers adding quality gates to pipelines,Solo developers who want enterprise-level code reviews without extra cost,Anyone curious about using AI in real-world development workflows
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