AI-Powered Software Testing — GenAI for QA Engineers

About this course

A practical, vendor-neutral course on using generative AI across the testing life cycle - from prompt engineering and test design to automation, API testing, defect reporting and tool evaluation. Every lesson is a hands-on lab on public practice apps, with a strong focus on verifying AI output, protecting confidential data and keeping human judgement in charge. You also learn to test LLM-powered applications and finish with a portfolio capstone on Sauce Demo.

What you will be able to do

• Write structured, reusable prompts that turn user stories into traceable test scenarios and review them with a checklist
• Use AI to apply EP, BVA and decision tables, generate seeded synthetic test data with Faker and convert criteria into declarative Gherkin
• Generate Playwright, Selenium and REST Assured code with AI assistants, then review, refactor to POM and prove the tests can fail
• Mask logs and personal data before using AI for bug reports, root-cause hypotheses and test summary reports
• Evaluate self-healing, visual AI and MCP-based tools with an evidence-based weighted scorecard
• Test LLM applications with golden sets, prompt-injection, bias checks and multi-run regression strategies
• Build a Python AI helper that calls any OpenAI-compatible API with environment-variable keys, redaction and an audit log
• Publish a portfolio-ready, AI-assisted test suite with a prompts log, review log, quality metrics and CI

Syllabus

1. ▶
   1. AI, ML and LLMs for Testers — What AI Can and Cannot Do in the STLC Understand how LLMs work, where AI genuinely helps across the STLC, and measure hallucination and non-determinism yourself with a hands-on experiment. Lesson + Lab · 60 min · 6 lab tasks · 5-question quiz · Free preview
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   2. Prompt Engineering for QA — Reusable Templates for Test Scenarios Learn the Role-Context-Task-Constraints-Format structure, build a reusable prompt template with a privacy check, and generate and critically review test scenarios from a real user story. Hands-on Lab · 75 min · 7 lab tasks · 5-question quiz
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   3. AI for Test Design — Edge Cases, Synthetic Data and Gherkin Use AI to apply EP, BVA and decision tables, prove the results with pytest, generate reproducible synthetic Indian test data with Faker, and convert acceptance criteria to declarative Gherkin. Hands-on Lab · 90 min · 6 lab tasks · 5-question quiz
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   4. AI Coding Assistants for Automation — Generate, Review and Refactor to POM Generate Playwright and Selenium code with AI assistants, review it with a 7-point checklist, refactor it into Page Object Model and prove the tests can fail. Hands-on Lab · 90 min · 7 lab tasks · 5-question quiz
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   5. AI for API Testing — From OpenAPI Spec to Postman and REST Assured Summarise an OpenAPI spec with Python, have AI draft a coverage matrix and test scripts, then run reviewed Postman/Newman and REST Assured tests and report spec-vs-actual mismatches. Hands-on Lab · 90 min · 7 lab tasks · 5-question quiz
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   6. AI for Bug Reports, Log Analysis and Test Summary Reports Mask sensitive data in logs with Python, use AI for root-cause hypotheses and well-structured bug reports, and produce test summary reports where numbers come from code. Hands-on Lab · 75 min · 6 lab tasks · 5-question quiz
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   7. Self-Healing Locators, Visual AI and the AI Testing Tools Landscape Understand how self-healing locators and visual AI work, try codegen, a self-healing demo and Playwright visual diffs, and evaluate AI testing tools with a weighted scorecard. Lesson + Lab · 75 min · 6 lab tasks · 5-question quiz
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   8. Testing AI/LLM Applications — Evaluation, Prompt Injection, Bias and Regression Learn quality dimensions and assertion strategies for LLM products, then build a golden-set, prompt-injection and bias test suite with pytest that handles non-deterministic output. Hands-on Lab · 90 min · 6 lab tasks · 5-question quiz
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   9. Build an AI Testing Helper in Python — API Keys, Privacy and Governance Build a Python helper that redacts sensitive data, calls any OpenAI-compatible LLM API (cloud or local) with an environment-variable key, saves draft output and writes an audit log. Hands-on Lab · 90 min · 7 lab tasks · 5-question quiz
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    10. Capstone Project — AI-Assisted Test Suite for Sauce Demo Build a portfolio-ready, AI-assisted Playwright suite for saucedemo with a prompts log, AI drafts versus reviewed code, measured quality, GitHub Actions CI and a rubric-based self-evaluation. Capstone Project · 120 min · 8 lab tasks · 5-question quiz