Playwright Training Course with Gen AI in Thane by Uncodemy

What you learn:Fundamentals of software testing, types of testing (functional, regression, smoke), testing lifecycle, and comparison of modern frameworks (Playwright vs Selenium vs Cypress). You’ll also learn test strategy basics and how automation fits into product delivery.

Hands-on:Create a simple manual test case, convert it into an automation test plan, and run a basic Playwright “Hello World” script.

Tools/Tech:Browser devtools, simple HTML demo app, Node.js runtime.

Assessment:Short quiz on testing vocabulary + a submitted test plan and a working basic Playwright script.

What you learn:Step-by-step environment setup (Node.js, npm/yarn), initializing Playwright projects, playwright.config configuration, managing dependencies, and project folder conventions for scalable test suites. Also covers project scaffolding and using templates.

Hands-on:Initialize a Playwright project, configure browsers list, set up test runner options, and create reusable config files for different environments (dev / staging / prod).

Tools/Tech:VS Code, terminal commands, package.json, playwright CLI.

Assessment:Submit configured project repo with documented README and runnable test commands.

What you learn:Comprehensive selector strategies (CSS, XPath, role/text, attribute selectors), robust locator design for dynamic pages, and implementing Page Object Model for clean, maintainable tests. Best practices for locator resilience and selector performance.

Hands-on:Convert a messy test script into a POM-based structure; create locator libraries and a utilities module for common actions (click, type, wait).

Tools/Tech:Playwright Locator API, reusable helper files, VS Code snippets.

Assessment:Code review of POM implementation + performance checklist (selector stability, reusability).

What you learn:Managing multiple browser contexts and isolated sessions, user profiles, authentication flows, and running the same test across Chromium, Firefox and WebKit. Techniques for parallelization while preserving test isolation.

Hands-on:Build tests that run login flows in isolated contexts, simulate multiple users, and run a small suite across three browser engines.

Tools/Tech:Playwright browser contexts API, headless vs headed modes, Docker for consistent browser environments.

Assessment:Report showing cross-browser pass/fail matrix and context isolation demonstration.

What you learn:Advanced assertion patterns, retries, wait strategies, implicit vs explicit waits, and techniques to identify and eliminate flaky tests. Learn how to instrument tests to surface timing-related issues and best practices for stable automation.

Hands-on:Implement retry logic, add health checks, use Playwright’s auto-wait features and explicit waitFor calls; create a small flaky test and stabilize it using learned techniques.

Tools/Tech:Playwright Test options, custom retry wrappers, logging and timestamped screenshots.

Assessment:Submit a before/after report demonstrating flakiness reduction and stability metrics.

What you learn:How to validate backend APIs within UI tests, intercept and mock network requests/responses, simulate slow networks or error conditions, and create deterministic test scenarios independent of unstable third-party services.

Hands-on:Write tests that stub API responses, test offline behavior, and validate UI behavior against mocked payloads. Create a contract-style test that asserts API response structure.

Tools/Tech:Playwright route/intercept API, Postman for reference, JSON schemas.

Assessment:Deliver test cases that demonstrate API mocking for at least two failure scenarios and one performance throttling case.

What you learn:Strategies for data-driven testing (CSV/JSON/DB sources), parameterization techniques in Playwright tests, and how to safely run tests in parallel without shared state issues. Learn test matrix design for broad coverage with minimal scripts.

Hands-on:Implement parameterized test suites that read multiple datasets, create CI matrix jobs to run permutations, and store results per dataset.

Tools/Tech:CSV/JSON readers, environment variable management, Playwright’s parallel runner options.

Assessment:Deliver a parallel test run report covering at least three data permutations with independent pass/fail logs.

What you learn:Practical ways to integrate Gen-AI into testing workflows: auto-generating test skeletons, suggesting locators, producing synthetic test data, and triaging flaky tests via AI suggestions. Also covers ethical/quality controls around generated content.

Hands-on:Use AI to generate test cases for a given user story, have AI propose selectors and then validate/adjust them manually; build a small pipeline that uses AI to create test-data sets.

Tools/Tech:ChatGPT/Copilot style APIs (conceptual integration), prompt design patterns, validation scripts.

Assessment:Submit an AI-assisted test suite along with prompts used and a short evaluation of AI suggestions (accuracy, usefulness, manual corrections required).

What you learn:How to deploy test suites into CI pipelines (GitHub Actions, Jenkins), schedule tests, collect artifacts (logs, traces, screenshots), and generate meaningful HTML/Allure style reports for stakeholders. Coverage on gating releases with test results.

Hands-on:Create a CI workflow that runs Playwright tests on push, captures artifacts on failure, and publishes a test report. Implement notifications to Slack/email on pipeline status.

Tools/Tech:GitHub Actions / Jenkins / GitLab CI, Allure reporter, S3/Artifacts storage, Slack integrations.

Assessment:Provide a working CI config and link to a sample run showing artifacts and structured reports.

What you learn:Final polishing for job readiness — covering common interview questions, whiteboard/logic problems related to testing, behavioral preparation, and packaging your capstone project for recruiters. Guidance on resume snippets, GitHub presentation, and demo scripts for live interviews.

Hands-on:Present your capstone project to a mentor panel, record a 10-minute demo walkthrough, and participate in mock technical + HR interviews. Receive targeted feedback and a preparation checklist for real interviews.

Tools/Tech:Recording tools, GitHub Pages for project showcase, template demo scripts.

Assessment:Successful mentor sign-off on capstone + completion of mock interview with improvement plan.

Module Duration & Outcome (Suggested):

• Total course hours: ~120–160 hours (theory + labs + projects).

• Module split: Each module: 8–18 hours depending on complexity (AI, CI, and capstone are heavier).

• Graduate outcome:Candidates will graduate with a deployable Playwright automation suite, AI-assisted test examples, CI pipelines, and a polished portfolio ready for placement.