Gen AI, AI Agents and MCP in Software Testing (Functional, Automation and Performance Testing) – Live Training
(Types of Language Models, Prompt Engineering & Prompting Techniques, Leveraging AI Across All Phases of Software Testing)
Isha Training Solutions presents an Extensive and Highly Interactive Course: “Gen AI, AI Agents and MCP in Software Testing (Functional, Automation and Performance Testing)” Led by a seasoned industry expert with over 12 years of hands-on experience, this course offers comprehensive, practical insights into Gen AI applications in software testing. With a curriculum designed to align with current job market trends and industry demands, participants will gain in-depth knowledge of Gen AI concepts through real-world examples and hands-on practice.
The use of Generative AI is becoming increasinlgy important in every phase of SDLC. It can also be leveraged in the field of software testing. To harness the potential of this technology in testing, you must learn to interact with different Gen AI tools. This course is designed to make you skilled to use LLMs in different phases of software testing.You will also learn about GitHub Copilot, RAG, AI agents and MCP.
Why Learn Gen AI, AI Agents and MCP in Software Testing?
- Generative AI is one of the most in-demand skills in modern software testing.
- Learn how to use AI tools for test case generation, test data creation, and defect analysis.
- Improve productivity in manual testing, automation testing, and performance testing.
- Gain practical skills in AI-driven requirement analysis and intelligent test planning.
- Understand how to test AI-powered applications built with models like GPT-4.
- Learn to integrate AI with automation frameworks such as Selenium and Playwright.
- Explore how AI Agents can automate repetitive QA tasks and support self-healing automation.
- Use MCP (Model Context Protocol) to connect AI models with testing tools, databases, and project documentation.
- Increase job opportunities for QA engineers, automation testers, and test leads.
- Prepare for future roles in AI Testing, Gen AI Testing, and Intelligent QA Automation. 🚀
About the Instructor:
| Chandra Kumar has over 12 years of experience in Performance Engineering and Testing. He is a BlazeMeter Certified Apache JMeter and Microfocus LoadRunner Certified Professional. Chandra has extensive expertise with performance testing tools such as Apache JMeter, LoadRunner, and Neoload, as well as APM tools including Dynatrace, AppDynamics, PerfMon, and NMON.He has been providing professional training on Performance Test Tools and Performance Engineering for more than 2 years. In addition, he brings his expertise to “Generative AI in Software Testing: Functional, Automation, and Performance Testing”, offering participants practical insights and hands-on experience in leveraging Generative AI for enhanced software testing. |
Sample Videos:
“Generative AI in Software Testing – Functional, Automation and Performance Testing ” -Day1 Video
“Generative AI in Software Testing – Functional, Automation and Performance Testing” -Day2 Video:
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 259 89 USD Or USD13000 INR 12900 INR 6900 Rupees
OR
Free Day2 On:
Indian Timings: 18th March @ 8:00 PM – 9:00 PM (IST)/
U.S Timings: 18th March @ 10:30 AM – 11:30 AM (EST)/
U.K Timings: 18th March @ 2:30 PM – 3:30 PM (BST)
Class Schedule:
For Participants in India: Monday to Friday @ 8:00 PM – 9:00 PM (IST)
For Participants in the US: Monday to Friday @10:30 AM – 11:30 AM (EST)
For Participants in the UK: Monday to Friday @ 2:30 PM – 3:30 PM (BST)
What students have to say about Chandra Kumar:
| “The Generative AI course was a game-changer! Chandra Sir’s practical examples, along with his deep knowledge, made learning enjoyable. The focus on performance testing with AI tools was particularly enlightening. Thank you for an amazing training experience!”- Arjun Verma
“A transformative learning experience! Chandra Sir’s expertise in Generative AI for software testing opened up new horizons for me. His teaching, combined with hands-on projects, was highly effective. I highly recommend this course to anyone interested in modernizing their testing approach.” – Sneha Reddy “Excellent session! The detailed coverage of functional, automation, and performance testing using AI tools was exactly what I needed. Chandra Sir’s clear explanations and practical demos provided great insights. I appreciate the real-world case studies and tips shared during the sessions.”- Amit Raj “Chandra Sir’s teaching style is outstanding! He made advanced AI-driven testing techniques feel simple and accessible. The hands-on exercises were well-structured, and I loved how he answered every question patiently. This training has given me the confidence to explore automation testing with Generative AI.” – Neha Gupta “The training was insightful and engaging! Chandra Sir explained Generative AI concepts in software testing with real-world examples, making it easy to understand complex topics. His step-by-step approach to automation and performance testing techniques using AI was impressive. Looking forward to applying these skills in my projects!”- Rahul Sharma First of all thanks for Isha training solutions for giving this wonderful course. Chandra sir has solid experience in Gen AI software testing. He has covered with some practical examples. I have been learned few courses like performance testing, Tosca from Isha training. My journey with Isha training solutions is like around 5 years. All the best everyone who wants to explore new topics. – krishna Mohan |
What will I learn by the end of this course?
- Understand the fundamentals of Generative AI in Software Testing and how AI is transforming modern QA processes.
- Learn how to use Gen AI tools for test case generation, test data creation, and defect analysis to improve testing efficiency.
- Gain practical knowledge of AI-powered Functional Testing to validate application features more effectively.
- Learn how AI Agents automate testing tasks, assist testers, and improve overall testing productivity.
- Understand Model Context Protocol (MCP) and how it connects AI models with testing tools and enterprise systems.
- Build AI-assisted Automation Testing frameworks for UI and web application testing.
- Learn AI-driven API testing techniques for validating backend services and microservices.
- Explore AI-based Performance Testing to identify performance bottlenecks and analyze system behavior.
- Understand LLM testing concepts, including prompt testing, response validation, and hallucination detection.
- Work on real-time projects using Gen AI, AI Agents, and automation testing tools.
- Improve skills in functional testing, automation testing, and performance testing using AI technologies.
- Prepare for modern QA roles such as AI Test Engineer, Automation Tester, and QA Engineer
Salient Features
- 25 Hours of On-Demand Live Sessions and Recorded Videos: Gain lifetime access to extensive training materials.
- Course Completion Certificate: Receive a certificate upon successful completion of the course.
- Hands-On Projects: Engage in real-world projects and live applications to apply the skills learned, ensuring practical, hands-on experience
Who can enroll for this course?
- Manual Testers who want to upgrade their skills with Generative AI and AI-powered testing tools.
- Automation Testers and QA Engineers looking to learn AI-driven automation testing and intelligent test frameworks.
- Software Developers who want to understand AI-based testing techniques for modern applications.
- Freshers and IT Graduates interested in building a career in AI Testing, Automation Testing, and QA.
- Test Leads, QA Managers, and DevOps Engineers who want to explore Gen AI, AI Agents, and MCP in software testing.
Course syllabus:
Gen AI Fundamentals – (3 Hours)
1. Introduction, Key concepts and terms:
- Overview of Artificial Intelligence (AI) and its significance
- Machine learning
- Deep learning
- Natural language processing
- Generative AI
- Language model
2. Difference between AI and Gen AI
3. Types of language models:
- Large language models
- Small language models
4. How do LLMs work
- Architecture and mechanisms behind LLMs
5. What is a prompt:
- Definition and role of prompts in AI interactions
6. Limitations of LLMs
- Cognitive Constraints
- Security Risks
- Privacy and Legal Concerns
7. Language model parameters
- Technical parameters
- Behavioral parameters
8. Applications and use cases of AI
- Chatbots, virtual assistants, and customer service
- Code generation, content creation, and predictive analytics
LLM Examples and Set up – (1 Hours)
9. Introduction to LLMs and their examples
10. Set up of different LLMs – ChatGPT, Gemini, DeepSeek, GitHub Copilot
Prompt Engineering – (4 Hours)
11. What is prompt engineering
- Introduction to prompt engineering
- Definition and significance of crafting effective prompts
12. Prompt components
- Basic prompt structure
13. Prompt Frameworks
14. Formatting and prompt parameters
- Formatting styles
- Temperature, Max tokens and Stop sequences
15. Prompt tuning process
- Adjusting prompts for specific responses
- Iterative testing and refinement of prompt phrasing
16. Different prompting techniques
- Shot based prompting
- Sequential prompting
- Context guiding prompting
17. Handling Hallucinations and Biases
18. Best practices
- Best practices in prompt engineering
GitHub Copilot and its features – (2 Hours)
- Introduction to GitHub Copilot
- How does it work and its different featues
RAG, Agentic AI and MCP servers – (2 Hours)
19. Introduction to RAG (Retrieval-Augmented Generation)
20. How RAG works and its benefits
21. Introduction to Agentic AI
22. How Agentic AI works and its examples
23. Introduction to MCP servers
24. Working with MCP servers
Gen AI in Software Testing – (4 Hours)
25. Requirement analysis
- Requirement analysis with AI conversational tools
- Deeper understanding of requirements
- Identify testable requirements
- Requirement traceability matrix
26. Test planning
- Test strategy and approach preparation
- Selection of different testing tools
- Effort estimation
- Risk-based test prioritization
- Identify different types of performance tests
27. Test case development
- Functional test case creation
- Automation script development
- Performance test script development
- Optimizing test coverage and identifying edge cases
- Test data creation
28. Test environment set up
- Test environment creation plan
- Test environment selection
- Verification of test environment
29. Test execution
- Defect creation
- Performance bottlenecks
- Defect reporting
- Daily and weekly status
30. Test cycle closure
- Assess the test closure cycle
- Test results analysis
- Test metrics preparation
- Test report creation
How can I enroll for this course?
OR
For any other details, Call me or Whatsapp me on +91 9133190573
Live Sessions Price:
For LIVE sessions – Offer price after discount is 129 USD 109 89 USD Or USD15000 INR 9900 INR 6900 Rupees.