Claude AI for Software Testing – Manual Testing, Automation & AI-Assisted QA – Live Training
(For Manual Testers, Automation Testers, Performance Testers & Aspiring AI-assisted QA Engineers.)
This comprehensive hands-on course is designed for Manual Testers, and QA professionals who want to leverage the power of Claude AI in modern software testing. The program covers the complete AI-assisted QA lifecycle including Generative AI fundamentals, Prompt Engineering, Agentic AI, Test Case Design, Bug Reporting, Test Data Generation, Requirements Analysis, Exploratory Testing, and SQL testing using AI-powered approaches.
Through practical demonstrations, real-time use cases, and guided lab sessions, learners will understand how to integrate Claude AI into daily QA activities to improve productivity, enhance test coverage, accelerate defect analysis, and streamline testing workflows. The course focuses on industry-oriented implementation techniques that help testers perform smarter and faster testing using advanced AI capabilities.
Participants will gain strong expertise in AI-assisted testing strategies, intelligent prompt creation, requirements gap detection, exploratory testing methodologies, and automation support using Claude AI. By the end of the training, learners will be equipped with the skills required to become future-ready AI-enabled QA professionals capable of working efficiently in modern AI-driven software development environments.
About The Instructor:
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The trainer is a passionate QA professional with over 10 years of industry experience in Software Testing, Automation Testing, API Testing, Database Testing, and AI-assisted Quality Engineering. With a strong focus on practical learning and real-time implementation, the trainer has successfully trained 100+ students from diverse technical backgrounds including Manual Testing, Automation, and modern AI-powered QA practices. The trainer believes in making complex concepts simple and easy to understand through hands-on demonstrations, industry use cases, and interactive learning sessions. Teaching is not just a profession but a true passion for the trainer. Known for a student-friendly and practical training approach, the trainer provides personalized guidance and 1-on-1 support based on individual learner requirements. Whether a student is a fresher, working professional, or experienced tester transitioning into AI-enabled QA roles, the trainer focuses on helping every learner build strong confidence, practical skills, and industry-ready knowledge. The trainer specializes in Generative AI for QA, Prompt Engineering, Test Case Design, Bug Analysis, Requirements Validation, Exploratory Testing, SQL Testing, and AI-powered testing workflows using tools like Claude AI. The sessions are designed to be highly interactive, career-oriented, and implementation-focused, ensuring students gain real-world exposure rather than only theoretical understanding. The trainer is committed to helping learners stay ahead in the rapidly evolving AI-driven software testing industry. |
Claude AI for QA Engineers – Demo Video:
Claude AI for QA Engineers – Day1 Video:
Live Sessions Price:
For LIVE sessions – Offer price after discount is 159 USD 109 59 USD Or USD11000 INR 9900 INR 4900 Rupees.
OR
Free Demo Session Timings:
4th November @ 9 PM – 10 PM (IST) (Indian Timings)
4th November @ 10:30 AM – 11:30 AM (EST) (U.S Timings)
4th November @ 3:30 PM – 4:30 PM (BST) (UK Timings)
Class Schedule:
For Participants in India: Monday to Friday @ 9 PM – 10 PM (IST)
For Participants in US: Monday to Friday @ 10:30 AM – 11:30 AM (EST)
For Participants in UK: Monday to Friday @ 3:30 PM – 4:30 PM (BST)
What student’s have to say about Trainer:
| The training was extremely practical and easy to understand. The trainer explained Claude AI concepts with real-time QA examples, which helped me understand how AI can actually improve testing activities. The hands-on sessions and prompt engineering examples were very useful for my daily work. – Sagarika
Excellent course for anyone working in QA or planning to upgrade their testing skills with AI. The trainer has strong industry experience and explains every topic with practical examples. The live demonstrations and real-time testing scenarios made the sessions very engaging. I particularly liked the sections on Agentic AI, exploratory testing strategies, and requirements gap analysis. The trainer also provided personal support and clarified doubts patiently after sessions. – Daniel The course content is very relevant to current industry needs. The trainer explained Generative AI concepts in a very simple way and showed how AI can actually help testers save time and improve efficiency. The practical exercises and assignments were very useful for gaining confidence. – Mohmmed I joined this course as a manual tester wanting to learn AI concepts for software testing. The trainer made the entire learning journey easy and engaging. Every topic was explained with examples, live demos, and practical exercises. The sessions on prompt engineering, AI-assisted SQL testing, exploratory testing strategies, and test case design helped me understand how modern QA teams are adopting AI. The trainer also motivated students continuously and provided career guidance throughout the course. – Vamsi Krishna An outstanding learning experience for QA professionals looking to explore the future of software testing with AI. The trainer covered everything from AI fundamentals and Claude AI capabilities to prompt engineering, requirements analysis, bug reporting, exploratory testing, and AI-assisted workflows in great detail. Every module was supported with practical demonstrations and real-world examples. The trainer also encouraged interactive learning, answered all queries patiently, and provided individual guidance based on student requirements. This course is highly valuable for anyone planning to build a strong career in AI-powered Quality Assurance. – Rajesh |
Who can enroll for this course?
- Manual Testers looking to upgrade with AI-powered testing skills
- Automation Test Engineers interested in integrating AI into QA workflows
- SDETs and QA Engineers working on modern testing practices
- QA Leads and Test Managers aiming to improve team productivity using AI
- API, Functional, and Database Testers exploring AI-assisted testing approaches
- Professionals interested in Prompt Engineering for Software Testing
- Freshers and aspiring QA professionals wanting to learn next-generation testing skills
- Anyone interested in Generative AI applications in Software Testing and Quality Assurance
Salient Features:
- Approximately 20+ Hours of Live Training
- Every session gets recorded and one year access to these videos will be given.
- Course Completion Certificate
What will I Learn by the end of this course?
- Understand how Claude AI can support software testing and quality assurance
- Generate test cases, test scenarios, and test plans using AI.
- Analyze requirements and identify potential defects and edge cases
- Use Claude AI to improve manual testing activities.
- Assist in writing and improving automation test scripts using AI
- Analyze bugs, error messages, and test results more efficiently.
- Generate test data and improve test coverage.
- Create test documentation and reports with AI assistance.
- Explore AI-assisted API testing and test case generation.
- Apply effective prompt engineering techniques for QA tasks.
- Improve testing productivity, accuracy, and efficiency using Claude AI.
- Understand the limitations of AI-generated test cases and validate outputs before using them in real projects.
Course syllabus:
Module 1 –Foundations of Generative AI and LLMs
- AI vs. machine learning vs. Generative AI
- How LLMs respond; tokens, context windows, and hallucinations
- Claude model options and choosing a model for a task
- Strengths, limitations, privacy, and responsible use in QA
Module 2 –Understanding AI Agents for QA
- Reactive AI: prompt in, response out
- Agentic workflows: goal, planning, tool use, observation, and iteration
- Examples: test case generation vs. an agent that checks coverage and revises cases
- Human approval, permissions, guardrails, and failure modes
- Detailed MCP setup is reserved for Module 13
Module 3 – Prompt Engineering for QA Professionals
- Prompt anatomy: role, context, task, constraints, and output format
- Zero-shot and few-shot prompting
- Iterative prompting and prompt evaluation
- Reusable prompts for requirements, test design, bug reports, and performance analysis
- Hands-on: improve a weak prompt and compare outputs
Module 4 – Claude for Test Case Design & Coverage
- Functional, cynical, boundary-value, and equivalence-partition test design
- API test scenarios and expected results
- Traceability from requirements to test cases
- Reviewing duplicates, gaps, assumptions, and hallucinated requirements
- Lab: generate and review a structured login test suite
Module 5 –Bug Reporting and Root-Cause Investigation
- Clear bug titles, steps, actual vs. expected results, evidence, and severity
- Using sanitized logs and error messages
- Distinguishing observed facts from root-cause hypotheses
- Lab: turn a failure log into a bug report and investigation checklist
Module 6 – Test Data Generation
- Valid, invalid, boundary, and synthetic test data
- CSV and JSON data for test execution
- Data privacy, secrets, and personally identifiable information
- Lab: create a reusable test-data set and validate it
Module 7 – Requirements Analysis & Gap Detection
- BRD, FRD, user stories, and acceptance criteria
- Ambiguity and missing requirement detection
- Definition of Ready and requirement-to-test traceability
- Lab: create a requirement review report and identify missing scenarios
Module 8 – AI-Assisted Exploratory Testing Strategy
- Exploration charters and testing heuristics
- Session-based testing and evidence capture
- Using AI to suggest paths without surrendering tester judgement
- Lab: prepare a charter and session summary
Module 9 – SQL and Database Testing using AI
- Using Claude to draft and explain SQL
- Data validation, joins, filtering, and test queries
- Reviewing queries for correctness and safety
- Use read-only practice data; do not run unreviewed destructive SQL
Module 10 – Bulid an AI Test Case Generator with Claude
- prompt- based generation directly in Claude
- Deliverable: working test case generator and a sample output file
Module 11 – JMeter Performance Testing Automation with Claude
- Turn a performance scenario into a JMeter test-plan design
- Generate and review JMX components, assertions, and parameterization
Module 12 – Functional Test Automation with Claud
- Record a test with codegen
- Claude can clean the recorded script and add assertions
- Organize tests with Page Object Model
- Fix failing tests with Claude’s help, then rerun to confirm
- Deliverable: a small working test suite (login, cart and API tests)
Module 13 – MCP, Connectors , and Tool – Using QA Workflows
- What MCP does and how tool connections differ from pasted context
- Connectors and integrations available in the learner’s current environment
Module 14 – Smarter QA With AI
- Regression Test Selection
- AI-Assisted Code Review for Testers
- AI-Assisted Test Impact Analysis
Live Sessions Price:
Call or Whatsapp Kumar gupta @ +91-9133190573
OR
For LIVE sessions – Offer price after discount is 159 USD 109 59 USD Or USD11000 INR 9900 INR 4900 Rupees.
Sample Course Completion Certificate:
Your course completion certificate looks like this……

Note:
To maintain the quality of our training and ensure a smooth learning experience for all participants, we do not allow batch repetition or switching between courses.
To reiterate, moving from one course to another or shifting from one trainer to another (even if it is the same course) is not possible. Changing batches or trainers in any form is strictly not permitted.
We request all learners to attend the scheduled sessions regularly and make the most of their learning journey. Thank you for your understanding and continued support.
Course Features
- Lectures 53
- Quiz 0
- Duration 20 hours
- Skill level All levels
- Language English
- Students 159
- Assessments Yes
- 14 Sections
- 53 Lessons
- 20 Hours
- Module 1 –Foundations of Generative AI and LLMs4 Items
- Module 2 –Understanding AI Agents for QA5 Items
- 2.1Reactive AI: prompt in, response out
- 2.2Agentic workflows: goal, planning, tool use, observation, and iteration
- 2.3Examples: test case generation vs. an agent that checks coverage and revises cases
- 2.4Human approval, permissions, guardrails, and failure modes
- 2.5Detailed MCP setup is reserved for Module 13
- Module 3 – Prompt Engineering for QA Professionals5 Items
- Module 4 – Claude for Test Case Design & Coverage5 Items
- Module 5 –Bug Reporting and Root-Cause Investigation4 Items
- Module 6 – Test Data Generation4 Items
- Module 7 – Requirements Analysis & Gap Detection4 Items
- Module 8 – AI-Assisted Exploratory Testing Strategy4 Items
- Module 9 – SQL and Database Testing using AI4 Items
- Module 10 – Bulid an AI Test Case Generator with Claude2 Items
- Module 11 – JMeter Performance Testing Automation with Claude2 Items
- Module 12 – Functional Test Automation with Claud5 Items
- Module 13 – MCP, Connectors , and Tool – Using QA Workflows2 Items
- Module 14 – Smarter QA With AI3 Items


