GenAI for QA - Masterclass in Testing & Automation [2025]

Set up ChatGPT from scratch, explore the interface, configure data controls to prevent training data usage, and learn features like chat, search, reasoning, voice mode, image tools, and plan options.

Get started with Claude for testing tasks by signing up with Google, choosing the free plan, and using code generation, data visualization, and text and image analysis with data control.

learn how to set up Google's Gemini AI assistant, create or use a Gmail account, and customize settings, apps, and activity controls for streamlined QA tasks.

Master prompt engineering for QA by crafting clear, specific prompts to elicit accurate, actionable AI responses, with practical examples from software testing and everyday scenarios.

Define the AI role and provide context to shape precise responses. Break tasks into steps, specify output formats, and iteratively refine prompts for QA and testing.

Use ai to generate test cases for a login page, including positive and negative scenarios, test steps with expected results, plus usability and accessibility checks mapped to the test pyramid.

Learn how AI helps draft high-level test strategies and test plans from a product requirement document, detailing resources, timelines, MVP scope, and functional test cases for QA.

Leverage AI chatbots to generate comprehensive rest api test cases for get and post methods, covering valid and invalid inputs, edge cases, authentication, and error handling.

Leverage an AI assistant to craft mobile app test cases for searching courses by category and reviews, covering positive and negative scenarios, data sources, data validation, and mobile layout differences.

Generate test data for existing test cases using ai tools by refining prompts and appending results to the data table, with boundary value analysis for inputs like emails and passwords.

Use AI to generate detailed defect reports with structured fields like title, description, steps to reproduce, expected and actual results, and optional priority, while maintaining QA context across conversations.

Leverage AI assistants to rapidly set up a Selenium WebDriver framework in a Java Maven project, with a pom.xml and page object model for scalable test automation.

Discover how to locate and identify UI elements using AI assistants, focusing on unique locators with id, CSS, or XPath strategies for efficient automation.

Convert a standalone test script into a page object framework using ai-assisted refactoring, building a Selenium WebDriver and Java test automation framework with login verifications.

Create a data-driven test framework with AI by using a json-based data provider, json utils, and a generic test data structure to drive multiple test cases beyond login.

Implement a TestNG retry analyzer and listener to automatically re-run only failed tests, enabling efficient, data-driven suites in a page object model framework.

Extend reporting in a Selenium test framework by creating an extend report manager, wiring a test listener into the lifecycle, and logging high level test steps to an html report.

Design a Rest Assured java rest api test framework with data-driven json files, pojo models, log4j2 logging, allure reporting, and json schema validation, covering create, get, update, and delete user endpoints.

Demonstrates building a complete Rest Assured automation framework with AI-assisted code generation in Java, including pom.xml setup, Rest Assured client, models, data providers, JSON schema validation, and Allure reporting.

Debug a failing test, fix the gender field, and review logs to understand issues. Learn to generate AI-assisted reports with maven, test suites, and JSON schema validators.

Explore AI coding tools like GitHub Copilot, windsurf, and cursor, plugged into VS Code and JetBrains, with pricing insights and data retention policies for enterprise teams.

Use GitHub Copilot in IntelliJ IDEA to generate an all courses page object class and test class, with category, search, and click by title, positive, negative, and boundary tests.

Parameterize test data with Copilot by loading JSON file data via a data provider, updating test data JSON, and aligning the courses page tests with the existing framework.

Transform manual test cases into automation using Copilot, turning a forgot password test case into automated code, pages, and test files through prompts and iterative refinement.

Explore AI-powered debugging and auto-documentation with Copilot to quickly identify and fix test failures, explain project context, and add readable comments for test automation.

Explore private, offline AI chat assistants for data privacy, comparing GPT for all and LLM Studio, and install GPT for all locally on macOS to access local documents.

Install and configure a private LLM for secure testing tasks, using local documents and embeddings to build a vector database, then chat locally to compare GPT for all.

Explore ai powered testing tools and their shift from manual and code heavy approaches, highlighting self-healing, natural language test creation, and end-to-end tests.

Explore Test Trigger, an AI-based, no-code test automation tool for web, mobile, desktop, and API. Learn setup, account creation, and how it integrates with CI/CD, test management to boost automation.

Navigate test trigger documentation to access getting started guides, basic commands, API testing, and data generation features, and learn how to use stored values, checks, and templates for automated testing.

learn to automate web app testing with test rigor by creating test suites and data-driven test cases, using reusable rules and ai-powered execution to speed qa.

Master data driven testing with Test Trigger by creating data sets, rows, and variables to run multiple course scenarios. Link data sets to test across searches and selections.

Explore self-healing tests with TestRigor to achieve low-maintenance automation. Learn how AI adapts locators, handles tab switching, and repairs broken inputs without reworking tests.

Automate rest api testing with test trigger by creating an api test suite, executing get and post tests, validating http codes, and extracting data with jsonpath using bearer tokens.