Learn Generative AI for Software Testing

Overview

Mastering Generative AI for Software Testers & QA What you'll learn:

Learn hHow to use Gen AI LLM's effectively to maximize your QA Productivity with smart prompt engineering skillsGet overview of AI Powered Testing tools in current market and their capabilities for revolutionizing Test AutomationLearn generating Test Artifacts in fly such as Test Plan, Testcases, Test Data, Bug templates for given Business requirementsUnderstand how to Generate & optimize the Test code into framework standards with Gen AI Plugins such as Github copilot etc Unlock the Power of Generative AI and Advance Your Testing CareerAre you a Manual Tester, QA Engineer, or Automation Tester looking to stay ahead in today’s fast-paced testing landscape? This course is designed specifically for testers and QA professionals who want to harness the power of Generative AI to enhance productivity and expand their testing capabilities.What You’ll Learn in This Hands-On CourseGain clarity on AI vs Generative AI — understand the differences and key concepts.Explore popular Large Language Models (LLMs) such as ChatGPT, Google Gemini, and DeepSeek.Master the art of Prompt Engineering — the foundation for getting accurate and relevant outputs from AI tools.Learn to generate Test Plans, Test Cases, Test Data, and Bug Reports within seconds using Generative AI.Discover how to apply AI in Selenium Automation, API Testing, and Database Testing.Use GitHub Copilot to accelerate coding, fix bugs faster, and effortlessly generate documentation.Why This Course is Essential for TestersThe future of software testing is increasingly AI-powered — from writing test scripts to generating test data, performing exploratory testing, and optimizing SQL queries.

Generative AI can assist testers at every stage of the testing lifecycle. Whether you are a Manual Tester aiming to boost your efficiency or an Automation Engineer looking to streamline scripting, this course equips you with practical AI skills to future-proof your career.What You’ll ReceiveStep-by-step demonstrations for setting up ChatGPT, Google Gemini, and DeepSeek.Real-world examples showing AI applications in Manual Testing, Automation, API Testing, and Database Testing.Hands-on exercises and tailored prompts to practice using AI for testing tasks.Expert tips to save time, reduce errors, and improve test coverage using AI.Guidance on using GitHub Copilot to accelerate and enhance automation work.Who Should EnrollThis course is ideal for:

Manual Testers and QA EngineersAutomation Testers (Selenium, API, Database Testers)Test Leads and Test ManagersAnyone interested in understanding how AI is transforming the testing domainPrerequisitesBasic knowledge of manual testing, automation testing, and SQL is recommended — no prior AI experience is required.Future-proof your QA career by mastering Generative AI tools and techniques.

Enroll now and stay ahead!Course CurriculumChapter 1:

Introduction to AI and Generative AIUnderstanding Artificial Intelligence (AI) and real-world applicationsWhat is Generative AI? Real-world examplesDifferences between AI and Generative AIIntroduction to Large Language Models (LLMs)Why every QA professional should learn Generative AIOverview of popular Generative AI models (ChatGPT, Google Gemini, DeepSeek, and more)Chapter 2:

Exploring Large Language Models (LLMs)What exactly is an LLM?How Large Language Models workStep-by-step setup for ChatGPT, Google Gemini, and DeepSeekUnderstanding LLM features and techniques for effective interactionChapter 3:

Introduction to Prompt EngineeringWhat is a Prompt and why does Prompt Engineering matter?Key elements of a well-formed prompt:

InstructionContextInput DataOutput IndicatorEssential Prompt Engineering techniques:

Zero-shot PromptingOne-shot PromptingFew-shot PromptingChapter 4:

Quick Recap of Manual Testing FundamentalsKey manual testing concepts and terminologyChapter 5:

Applying Generative AI in Manual TestingInstantly generate comprehensive Test PlansAutomatically create Test Scenarios and Test CasesGenerate Test Data on demandUse AI to draft Bug Reports quicklyGenerate Test Execution Reports with minimal effortChapter 6:

Using Generative AI in Selenium AutomationAutomatically generate Selenium Test ScriptsDebug errors with AI-suggested solutionsAuto-generate XPath and CSS SelectorsGenerate test data for automation runsCreate documentation for test cases automaticallyGenerate Automation Reports using AIConvert code between languages and frameworksMigrate existing automation frameworks with AI assistanceOptimize XPath and locator strategies with AIUse AI to generate test data and integrate with APIsAdvanced prompt techniques for automation engineersChapter 7:

Applying Generative AI to API TestingGenerate API Payloads using AICreate POJO Classes from JSON responsesAutomatically generate JSON Schema from API responsesAdd assertions to API tests with AI-generated codeConvert data formats (JSON to CSV and vice versa)Build utility methods to read data from JSON, CSV, and XML files using AIChapter 8:

AI in SQL and Database TestingAI-powered SQL Query GenerationQuery optimization and performance tuningData integrity and validation checksVerify query accuracy using AISchema validation using AI-generated promptsEnsure data consistency during data migration tasks with AI assistanceChapter 9:

Mastering GitHub Copilot for Testers and Automation EngineersInstall and set up GitHub CopilotGenerate meaningful commit messages automaticallySummarize code changes with AI assistanceUse Copilot to suggest bug fixes and improvementsGenerate sample test data directly in your IDEAutomatically rewrite code to match desired styles or patternsUse Copilot to generate documentation for your test methodsChapter 10:

AI AgentsLimitations of LLM'sHow AI Agents overcome limitations of LLM'sLLMs Vs AI AgentsChapter 11:

Exploring testRigor (Generative AI Based Test Automation Tool)"Many more AI concepts are in the pipeline.

Stay tuned!"Take the next step in your QA career and become an AI-empowered tester. Enroll today and transform the way you test!

Syllabus

• **Introduction to AI and Generative AI**
• Understanding Artificial Intelligence (AI) and real-world applications
• What is Generative AI? Real-world examples
• Differences between AI and Generative AI
• Introduction to Large Language Models (LLMs)
• Why every QA professional should learn Generative AI
• Overview of popular Generative AI models (ChatGPT, Google Gemini, DeepSeek, and more)
• **Exploring Large Language Models (LLMs)**
• What exactly is an LLM?
• How Large Language Models work
• Step-by-step setup for ChatGPT, Google Gemini, and DeepSeek
• Understanding LLM features and techniques for effective interaction
• **Introduction to Prompt Engineering**
• What is a Prompt and why does Prompt Engineering matter?
• Key elements of a well-formed prompt:
Instruction
Context
Input Data
Output Indicator
• Essential Prompt Engineering techniques:
Zero-shot Prompting
One-shot Prompting
Few-shot Prompting
• **Quick Recap of Manual Testing Fundamentals**
• Key manual testing concepts and terminology
• **Applying Generative AI in Manual Testing**
• Instantly generate comprehensive Test Plans
• Automatically create Test Scenarios and Test Cases
• Generate Test Data on demand
• Use AI to draft Bug Reports quickly
• Generate Test Execution Reports with minimal effort
• **Using Generative AI in Selenium Automation**
• Automatically generate Selenium Test Scripts
• Debug errors with AI-suggested solutions
• Auto-generate XPath and CSS Selectors
• Generate test data for automation runs
• Create documentation for test cases automatically
• Generate Automation Reports using AI
• Convert code between languages and frameworks
• Migrate existing automation frameworks with AI assistance
• Optimize XPath and locator strategies with AI
• Use AI to generate test data and integrate with APIs
• Advanced prompt techniques for automation engineers
• **Applying Generative AI to API Testing**
• Generate API Payloads using AI
• Create POJO Classes from JSON responses
• Automatically generate JSON Schema from API responses
• Add assertions to API tests with AI-generated code
• Convert data formats (JSON to CSV and vice versa)
• Build utility methods to read data from JSON, CSV, and XML files using AI
• **AI in SQL and Database Testing**
• AI-powered SQL Query Generation
• Query optimization and performance tuning
• Data integrity and validation checks
• Verify query accuracy using AI
• Schema validation using AI-generated prompts
• Ensure data consistency during data migration tasks with AI assistance
• **Mastering GitHub Copilot for Testers and Automation Engineers**
• Install and set up GitHub Copilot
• Generate meaningful commit messages automatically
• Summarize code changes with AI assistance
• Use Copilot to suggest bug fixes and improvements
• Generate sample test data directly in your IDE
• Automatically rewrite code to match desired styles or patterns
• Use Copilot to generate documentation for your test methods
• **AI Agents**
• Limitations of LLMs
• How AI Agents overcome limitations of LLMs
• LLMs vs AI Agents
• **Exploring testRigor (Generative AI Based Test Automation Tool)**
• Overview and features
• **Course Conclusion**
• Recap main topics and concepts
• Future AI concepts in testing (stay tuned for updates)

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Taught by

Pavan Kumar

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Subjects

Computer Science