AI-Driven Debugging Enhancing Debugging Skills with AI

Learn how to spot, verify, and fix bugs with AI as your coding partner
What you'll learn
Spot exactly where AI helps in debugging and where it wastes time
Use AI tools like ChatGPT, Claude Sonnet, and Copilot to speed up root cause analysis
Feed AI clean, targeted context so it gives useful answers instead of guesses
Write unit tests, edge cases, fuzz tests, and benchmarks with AI's help
Catch AI's mistakes before they cause bigger problems in production
Audit AI-generated fixes using diff tools, linters, and static analysis
Identify and prevent AI-driven security risks like injection flaws or weak validation
Run full-loop debugging with AI from bug report to verified patch
Build and refine your own AI-powered debugging checklist for real-world projects
Blend AI assistance with your own expertise to become a faster, more reliable debugger
Requirements
Strong programming skills in at least one language (Python, Java, C++, or similar).
Experience with debugging workflows and version control (Git).
Familiarity with automated testing (unit tests, integration tests).
Basic understanding of AI tools like ChatGPT or similar assistants is helpful but not required.
Description
Debugging is hard. Adding AI into the mix can make it faster-or much riskier. Tools like Copilot, and other AI assistants can suggest fixes, but they can also introduce new bugs or hide existing ones. This course shows you how to use AI as a debugging partner without losing control of your code.What this course gives youA practical system for combining classic debugging skills with AI assistance. You'll learn when AI can speed you up, when it can mislead you, and how to always keep verification in your workflow.What you'll learnHow AI fits into modern debuggingWays to feed AI clean context for better suggestionsTechniques to isolate problems with and without AIUsing AI to generate and expand test coverageSpotting AI "fixes" that hide new bugsFact-checking AI explanations with tools and checklistsRecognizing and managing AI security risksBuilding a full-loop debugging workflow with AI agentsCreating your personal debugging checklistHow we'll workYou'll:Run activities that train you to isolate code issues with AI helpPractice generating unit tests and fuzz tests with AIAudit AI patches and spot hidden mistakesLearn to manage AI as if it were a junior developerBuild and refine your own debugging playbookWhy it mattersBy the end, you'll be able to treat AI as a multiplier, not a replacement. You'll debug faster, with stronger safeguards, and with a clear system for verifying every AI-assisted change.No hype. No blind trust. Just real debugging skills, enhanced with AI.
Who this course is for
Software developers and software engineers who want to integrate AI into their debugging process.
Senior and lead engineers looking to boost debugging efficiency with AI-assisted workflows.
Developers responsible for testing, security validation, and performance optimization.
Professionals seeking to crosscheck and validate AI-generated debugging solutions for accuracy and safety.
Homepage
https://www.udemy.com/course/ai-driven-debugging-enhancing-debugging-skills-with-ai/

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