Working knowledge of JavaScript is helpful but not required. Days 1 and 2 cover all the TypeScript you need specifically for writing a Playwright framework. By the end of Day 2 you will be comfortable reading and writing any Playwright TypeScript sample without mentally translating it to JavaScript first.

You will have a complete Playwright TypeScript automation framework committed to your own GitHub repository, covering Page Object Model with custom fixtures, UI tests, API tests with authentication, Allure and HTML reporting, trace-based debugging, a GitHub Actions CI pipeline, and experience using Claude Code or Cursor to generate and self-heal tests. Day 7 adds a reviewed CV and a Playwright portfolio plan to that output.

Before Day 1 you need Node.js LTS (managed via nvm is recommended), VS Code, and Git installed on your laptop, plus a GitHub account. Before Day 5 you need Postman installed. Before Day 6 you need Claude Code or Cursor set up. All tools are free or available on a free tier and setup guidance is provided before each relevant day.

Day 6 covers two AI coding agents: Claude Code (from Anthropic) and Cursor. You will learn how to configure the agent against your own framework repository, write effective prompts that produce code matching your team's conventions, generate new test files from a user story or spec, and apply self-healing fixes to broken locators. You will also create a CLAUDE.md agent instruction file so the AI understands your framework automatically on every future run.

Yes. Day 5 is entirely dedicated to API testing. It starts with API fundamentals and manual exploration in Postman so you understand the request and response structure before automating it. You then use Playwright's built-in APIRequestContext to write GET, POST, PUT, and DELETE tests with authentication, and integrate API calls into UI tests for setup and teardown. API steps are visible in both the HTML reporter and the Trace Viewer.

Day 7 is a structured career programme covering five areas: how to represent Playwright experience effectively on your CV, how to write skills sections and project bullets that resonate with QA and SDET hiring managers, how to build a GitHub portfolio for an automation engineer, how to position your skills on LinkedIn for recruiter visibility, and a personal learning roadmap covering visual regression, accessibility testing, component testing, and further community resources.

Both are covered in Day 4. The Playwright HTML Reporter is built in and requires no additional setup. It shows pass/fail status, attachments, retries, and is generated with npx playwright show-report. Allure is a third-party reporter that produces richer, more visually detailed reports with history trends and category breakdowns. The course covers both and explains when each is the better choice for a given project or team.

A self-healing test is one that can detect a broken locator at runtime and automatically propose or apply a corrected selector without manual intervention. Day 6 covers the concept and the hands-on workshop has each learner use the AI agent to diagnose an intentionally broken locator and apply the suggested fix. You also learn the do's and don'ts of reviewing AI-generated locators and assertions before trusting them.

Yes. One of the deliberate design choices of this course is that Day 2 builds the Playwright framework by hand from an empty folder rather than using the CLI scaffold. This means every file, every config option, and every folder in the structure is understood because you created it yourself. Day 3 and Day 4 then extend that framework step by step rather than importing pre-built code.

Day 7 includes a personal learning roadmap covering the natural next steps: visual regression testing, accessibility testing with axe-core/playwright, Playwright component testing, advanced test data management strategies, and flaky test triage. ITLearnner also offers AI-Powered Test Automation with Playwright MCP and AI for Automation Testers as direct follow-on courses for those who want to go deeper into AI-augmented automation engineering.