COMING SOON

Build reliable browser tests and accelerate test development with AI. This hands-on course is designed for developers, QA engineers, and automation professionals who want to combine Python, PyTest, and Playwright with AI tools to test real-world web applications.

Start with an optional Python fundamentals section covering the language features you’ll use throughout the course. Already comfortable with Python? Skip ahead to PyTest, where you’ll learn to organize tests, manage setup and teardown with fixtures, and share configuration through conftest.py. Then explore Playwright through practical demonstrations of browser automation and testing across different browsers.

Building on these foundations, you’ll use the Playwright MCP server with AI coding tools to turn plain-English instructions into complete test suites. Learn to work with Claude Code and Codex to generate, review, and refine comprehensive tests, then integrate them into GitHub Actions to validate your application before deployment to staging or production.

By the end of the course, you’ll be able to:

• Apply essential Python skills to test automation. Work with core syntax, data structures, functions, and other useful language features—or skip this section if you already know Python.

• Build organized test suites with PyTest. Use fixtures for setup and teardown, share fixtures through conftest.py, skip and categorize tests with markers, and select tests using keyword expressions.

• Automate browser testing with Playwright. Navigate applications, interact with pages, verify expected behavior, and run tests across different browsers.

• Find page elements with confidence. Use get_by_label, get_by_text, get_by_role, locator, and other locator methods to create readable, maintainable tests.

• Author test suites using plain English. Use the Playwright MCP server with AI coding tools to explore application workflows and generate executable tests from natural-language instructions.

• Expand test coverage with Claude Code and Codex. Generate and refine tests for common workflows, edge cases, and failure scenarios, then review assertions and validate the results.

• Make automated testing part of delivery. Configure GitHub Actions to run your Playwright tests and require successful checks before deploying to staging or production.

Whether you’re getting started with browser automation or bringing AI into an existing testing workflow, this course provides a practical path from your first Python test to automated checks in your deployment pipeline. Develop the skills to write better tests, catch regressions earlier, and release with greater confidence.