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Detox & Playwright Web & Mobile Automation
Rating: 4.8 out of 5(65 ratings)
657 students

Detox & Playwright Web & Mobile Automation

Detox JS mobile E2E, Playwright TypeScript web & API testing, Page Objects, MCP & AI for QA
Created byLucky Trainings
Last updated 8/2026
English
English [Auto],

What you'll learn

  • Fundamentals of mobile automation testing using Detox
  • Writing end-to-end mobile tests using JavaScript
  • Setting up and using Playwright with TypeScript
  • Writing stable and reliable web automation tests using Playwright
  • Handling locators, waits, assertions, and test data
  • Debugging, reporting, and best practices
  • Real-world automation scenarios for testers
  • How modern automation tools differ from legacy tools

Course content

11 sections290 lectures33h 27m total length
  • Overview on AI4:29

    Discover how artificial intelligence acts as a thinking, learning computer system. See how AI understands language, recognizes images, and writes emails, poems, essays, manual test case, and automation test case.

  • Course Material2:30

    Organize the course material across AI, JavaScript, detox, TypeScript, and Playwright sections, with two repositories hosting complete source code, access materials, and presentations.

  • Overview on AI Part 29:28

    Explore how humans and AI collaborate in software development and testing. Recognize AI limits and use AI to accelerate tasks like test-case generation while maintaining human validation.

  • Overview on LLM6:35

    Describe how large language models, trained on vast data, function as AI brains that translate, summarize, answer, and generate content, using GPT-4, Claude-3, Gemini, and Lambda, vs Google search.

  • Overview on RAG2:14

    Explore how retrieval augmented generation enhances LLMs by retrieving data from a vector database and augmenting queries to produce accurate responses without full retraining.

  • Overview on Generative AI3:15

    Explore how generative AI creates new content and differs from traditional AI by generating code, documents, images, audio, and video from data.

  • Overview on Memory5:14

    Explore how AI memory enables meaningful conversations by storing, retaining, and retrieving past interactions, with examples of short-term vs long-term memory in user sessions and persisted chat histories.

  • Overview on AI Agent7:52

    Explore how an AI agent uses tools and independent decision-making to achieve a goal, perceive the environment, plan actions, execute with tools, and adapt based on results.

  • Overview on LangChain & LangGraph4:55

    Explore LangChain and LangGraph, revealing how LangChain connects LLMs to external data sources via a vector database, and how LangGraph defines AI workflows with nodes, edges, states, and checkpoints.

  • Overview on MCP4:39

    Explore MCP: a universal adapter protocol that lets AI models discover and call external tools—like calendars, code repos, and databases—through standardized, reusable, scalable interactions.

  • Overview on Human In the loop , Hallucination & Guardrails8:24

    Explore how human in the loop governs AI decisions, reduce hallucinations with precise prompts, and implement guardrails to set boundaries and approvals.

  • Overview on Fine-Tuning3:55

    Fine tuning updates an AI agent's existing knowledge base to tailor interactions for customers, branch staff, and officials, improving performance and contrasting with rag's external knowledge use.

  • Overview on Context Part 12:55

    Explore how providing context enhances language models and learning management systems, improving accuracy by supplying precise information before tasks.

  • Overview on Prompts5:34

    Explore prompt engineering and how clear context shapes AI responses, avoiding hallucinations by providing precise inputs and destination details for planning and booking tasks.

  • Overview on Context Part 27:39

    Define a context for an LLM to act as a manual or automation tester. Attach a context file with rules, acceptance criteria, and UI mockups to generate test cases.

  • Overview on Context Part 33:20

    Describe how a manual context file guides ChatGPT through a generic login flow, covering positive and negative tests, prompts, and client-specific acceptance criteria.

  • Overview on Prompts Part 27:13

    Explore zero-shot, one-shot, few-shot prompts and chain-of-thought reasoning within AI-driven automation workflows, emphasizing clear instructions and context files for accurate mobile and web test automation.

  • ChatGPT vs Copilot vs CURSOR5:00

    Compare ChatGPT, Copilot, and Cursor as coding assistants for automation testing, noting ChatGPT's general-purpose capabilities versus Copilot and Cursor that integrate with code bases and editors.

  • Overview on OpenAI3:08

    OpenAI, a research and development company, drives safe AI by open research, collaboration, and common principles and protocols, powering ChatGPT, Copilot, GPT models, and Dall-E behind the scenes.

  • Overview on AI Models3:56

    Explore what an ai model is and how it learns from data to recognize patterns and generate outputs, with gpt and dalle-e illustrating text and image tasks.

  • Generate API Key in OpenAI1:49

    Learn to generate an OpenAI API key from platform.openai.com by signing up and creating a secret key, then copy it to connect to OpenAI for building AI agents.

  • Overview on n8n workflow10:40

    Build an n8n workflow that reads data from Google Sheet via Google Drive, uses a GPT-4 mini AI agent, and sends an email to Sam when data matches.

  • Create workflow in n8n Part 27:42

    Design a dynamic n8n workflow that reads a Google Sheet, selects the proper email value, and sends an email via an AI-driven prompt, while validating recipient addresses.

  • Create workflow in n8n Part 39:23

    Build an n8n workflow that reads candidate data from Google Sheets sheet two, and sends background verification emails automatically when status is S.

  • Overview on n8n workflow6:30

    Explore how to build AI-powered workflow automations with n8n, create a trial account, and design AI agents to automate tasks like email reminders and data retrieval, without coding.

  • Create account in JIRA for our testing purpose7:10

    Learn how to create a Jira cloud account for test automation, generate an API token, set up a project and Zephyr test management, and prepare test workflows for automation.

  • n8n workflow for creating Bugs in JIRA Part 15:58

    Execute an n8n workflow to create Jira defects from Excel data for new status, enabling Zephyr, configuring cloud credentials (email, API token, domain), and debugging project linkage issues.

  • n8n workflow for creating Bugs in JIRA Part 25:04

    Explore how to build an n8n workflow to create Jira bugs from new sheet statuses, implementing credentials setup, URL handling, project selection, and automatic defect creation.

  • Create Public Chat in n8n workflow6:02

    Learn how to publicize an n8n chat, generate a shareable URL, and verify interactions by sending prompts, updating a sheet-based workflow, and auto-creating defects with new statuses.

  • Overview on OpenAI Tokens4:32

    This lecture explains tokens as the fundamental unit of text in OpenAI, how token count affects cost and rate limits, and how to optimize prompts on trial accounts.

  • CURSOR - Create a Chrome Extension for Record & Playback20:27

    Explore building a chrome extension that records browser actions and plays them back, generated by cursor ai with prompts in Playwright TypeScript or Selenium Java, guided by a human-in-the-loop.

  • CURSOR - Create a Chrome Extension for Record & Playback Part 22:11

    Create a Chrome extension for record and playback that generates playwright or selenium scripts in TypeScript, showcasing recording actions, playback, and downloadable test scripts.

  • CURSOR - Create an OTP Shield Mobile APP21:15

    Create an OTP shield mobile app that monitors SMS, calls, WhatsApp for OTP prompts and warnings, and blocks APK files. Generate project and build APK with Android Studio and Gradle.

  • Overview on GPT4ALL with example14:33

    Explore GPT4All, a free open-source desktop AI that runs LLMs locally offline, enabling private document analysis, test-case generation, and code creation using Playwright or Selenium.

  • Overview on Custom Agent.md file7:08
  • Creating Manual Testcase generator Agent part 113:52
  • Creating Manual Testcase generator Agent part 210:42
  • Creating Manual Testcase generator Agent part 314:33
  • Create an Playwright Agent12:42

Requirements

  • Basic understanding of software testing concepts
  • No prior automation experience required
  • Basic programming knowledge is helpful but not mandatory
  • Willingness to learn modern testing tools

Description

** Complete path: Detox (JavaScript) + Playwright (TypeScript) + AI for QA **


Learn modern web and mobile automation from scratch — Detox with JavaScript for React Native mobile E2E, Playwright with TypeScript for web & API testing, plus AI fundamentals for testers.


This Detox and Playwright course is built for manual testers, beginners, and QA engineers who want one practical path covering mobile + web automation with modern tools.


What you will learn in this course:

- AI fundamentals for QA and modern testing workflows

- JavaScript basics required for Detox automation

- Detox mobile automation for React Native (Android focus + E2E skills)

- TypeScript fundamentals required for Playwright

- Playwright TypeScript web automation (locators, assertions, UI interactions)

- Playwright API testing, Page Object Model, Git & GitHub Actions

- How Detox and Playwright fit into a modern automation career path

- MCP and AI-assisted testing concepts used with modern frameworks


Keywords covered in this course:

Detox, Detox JavaScript, Detox React Native, Playwright TypeScript, Playwright automation, Playwright API testing, web and mobile automation, React Native E2E testing, Page Object Model, MCP, AI for QA, JavaScript for testers, TypeScript for automation.


This course combines mobile automation with Detox and web/API automation with Playwright TypeScript so you can build end-to-end skills for real projects and interviews.


If you are searching for Detox and Playwright, Detox JavaScript, Playwright TypeScript, or web and mobile automation training in one course, this course is for you.



This course is a complete, end-to-end learning path for testers who want to upgrade to modern, AI-powered automation testing. It is designed from scratch and gradually takes you from testing fundamentals to real-world mobile and web automation using Detox (JavaScript) and Playwright (TypeScript), along with a solid foundation in AI concepts for testers.

AI Fundamentals for Testers - You will start with a clear and practical introduction to Artificial Intelligence concepts relevant to software testing. This section focuses on understanding AI at a high level so testers can confidently use and discuss AI in automation and testing workflows.

Mobile Automation Testing with Detox (JavaScript) - You will then deep-dive into mobile automation using Detox, a powerful end-to-end testing framework for React Native applications.

Web Automation with Playwright (TypeScript) - In the final section, you will master Playwright with TypeScript, one of the most in-demand automation tools in the industry.

By the End of This Course

You will have:

  • A strong understanding of AI concepts for testers

  • Hands-on experience in mobile automation using Detox

  • Real-world skills in Playwright with TypeScript

  • Confidence to work on modern automation projects

  • Skills aligned with current and future testing roles

This course is ideal for testers who want to stay relevant, future-proof their careers, and move beyond legacy automation tools into AI-driven, modern testing.

Who this course is for:

  • Manual testers who want to move into automation
  • Automation testers upgrading to modern tools
  • QA engineers preparing for future testing roles
  • Testers interested in mobile and web automation
  • Anyone looking to learn Detox+JavaScript & Playwright+TypeScript from scratch