AI for QA Engineers

Generative AI · Prompt Engineering · AI Automation · AI Agents for QA

Upgrade your existing QA career with practical AI skills.

📊Intermediate

⏱4 Weeks

🎙Live Online

📁4 Modules

🔧7 Tools

Designed for existing QA and SDET professionals who want to integrate AI into their daily testing workflows. This course covers generative AI fundamentals, prompt engineering for QA tasks, AI coding assistants, AI-powered test generation, failure analysis, regression analysis, reporting, and AI agents — without requiring you to rebuild your entire skill set.

₹7,999– ₹12,999

starting price

Enrol Now Talk to a Mentor

Intermediate

4 Weeks

Live Online

LevelIntermediate

Duration4 Weeks

FormatLive Online

Modules4

Who Is This Course For?

Practising QA engineers and manual testers
Automation engineers wanting to leverage AI tools
SDET professionals keeping pace with industry trends
QA leads evaluating AI adoption for their teams
Anyone with testing experience who wants to work faster and smarter with AI

What You'll Learn

Use ChatGPT, Claude, and Gemini effectively for QA tasks using prompt engineering

Integrate GitHub Copilot and Cursor into your automation workflow

Generate comprehensive test cases and test data from requirements using AI

Use AI for failure analysis, log correlation, and root cause identification

Implement AI-assisted regression analysis and risk-based test selection

Understand AI agents for QA workflows and evaluate their safe, responsible use

Course Curriculum

How LLMs work — without the maths
Prompt engineering: structure, context, and output control
AI for requirement analysis and test scenario generation
AI-generated test cases — reviewing, validating, and using them
AI limitations: hallucinations, bias, and when NOT to trust AI
Enterprise AI usage: security, confidentiality, and governance

AI-Powered Automation

AI is not a single chapter — it is integrated throughout this course at every stage.

AI is the entire course — every topic, every tool, every exercise

Prompt engineering specifically for QA tasks and testing contexts

AI tools: ChatGPT, Claude, Gemini, GitHub Copilot, Cursor

AI agents and multi-agent concepts for autonomous QA workflows

Responsible AI: governance, hallucination detection, and validation

Enterprise security and confidentiality guidance for AI tool use

Tools & Technologies

ChatGPTClaudeGeminiGitHub CopilotCursorPostman (AI features)Jira (AI features)

Live Project

Industry-Style Project Simulation

Apply AI across a realistic QA cycle — generate test cases from requirements using prompts, use Copilot to write automation scripts, perform AI-powered failure analysis on a set of pre-built test failures, and produce an AI-assisted test execution report. Practical, hands-on, and directly applicable to your current role.

Instructor

👨‍💻

Senior SDET / QA Automation Engineer

12 Years Industry Experience

Practising QA engineer with 12 years of experience building and testing software at scale. Brings real-world architectures, real failures, and practical solutions to every session — not textbook theory.

Career Outcomes

AI-Augmented QA EngineerSenior QA Engineer with AI specialisationQA Lead with AI adoption expertiseSDET with AI-first workflowsReady to progress to AI SDET Career Program

FAQs

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Ready to start AI for QA Engineers?

Learn from experienced QA and SDET professionals, work on real-world projects, and build the skills modern engineering teams expect.

Enrol Now Talk to a Mentor Download Course Curriculum