Claude Code Testing and Debugging AI-Powered Generation

What you'll learn

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Use the Claude Code CLI to autonomously generate comprehensive unit and integration test suites for complex applications with zero manual boilerplate.
Command Claude to analyze stack traces, identify root causes of logic flaws, and automatically patch bugs directly inside your local codebase.
Integrate AI-driven quality assurance into GitHub Actions or GitLab CI to catch and fix code vulnerabilities automatically before they reach production.
Master enterprise workflows for coding agents to resolve multi-file, real-world GitHub issues using the SWE-bench evaluation framework.
Requirements

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Basic understanding of software development (e.g., Python, JavaScript) and comfort navigating a terminal or command-line interface. You will also need an active Anthropic API key to utilize the Claude Code CLI tools. No prior AI engineering experience is required.
Description

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"This course contains the use of artificial intelligence."
Turn Claude Code from a fast code generator into a disciplined testing, debugging, and CI/CD partner.
You will learn a practical, evidence-first workflow for using Claude Code on real engineering tasks. Instead of accepting the first patch that appears, you will define expected behavior, create meaningful tests, diagnose failures, review generated diffs, and verify changes through automated quality checks.
Who this course is for

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Mid-level software engineers, QA automation specialists, and DevOps engineers who are tired of writing boilerplate tests and want to drastically reduce debugging time by integrating autonomous AI coding agents directly into their local development workflows.
Homepage

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