AI, LLM Testing & Generative AI Automation Course with Python, Azure ML, RAG, Playwright Live Training – Day 3

AI, LLM Testing & Generative AI Automation Course with Python, Azure ML, RAG, Playwright – Live Training

(AI, LLM Testing, Generative AI for QA, Python Automation, Playwright UI Testing, LLM Evaluation & AI Project.)

 

Nesara is an accomplished SDET and passionate trainer with a strong focus on AI Testing, Automation, and DevOps. With years of hands-on experience across Playwright, Selenium, Java, C#, and modern testing frameworks, she brings a unique blend of technical depth and teaching excellence. Her expertise extends to validating AI and ML models, ensuring accuracy, fairness, and reliability in intelligent systems — helping testers adapt to the new era of AI-driven quality assurance. As a dedicated mentor, Nesara has successfully trained a large number of professionals, guiding each learner with personal attention and practical insights. Her sessions emphasize real-world scenarios, hands-on practice, and the integration of Generative AI tools in test planning, automation, and continuous testing. Learners appreciate her approachable style, clear explanations, and focus on building job-ready skills. With a passion for continuous learning and innovation, Nesara inspires testers to go beyond traditional testing and embrace AI-powered quality engineering. Her goal is to help QA professionals evolve into future-ready experts capable of testing the next generation of intelligent applications.

Sample Videos:

AI, LLM Testing & Generative AI Automation Course with Python, Azure ML, RAG, Playwright – Demo Video

AI, LLM Testing & Generative AI Automation Course with Python, Azure ML, RAG, Playwright – Day 1 Video

Live Sessions  Price:

For LIVE sessions – Offer price after discount is 300 USD 259 USD 109 USD Or 13000 INR 12900 INR 8900 Rupees

Enroll For Free Demo

OR

WhatsApp

Day 3 Session On:

Indian Timings: 6th March  @8 PM – 9 PM (IST)/

U.S Timings: 6th March  @9:30 AM – 10:30 AM (EST)/

U.K Timings: 6th March  @2:30 PM – 3:30 PM (BST)

Class Schedule:

For Participants in India: Monday to Friday @8 PM – 9 PM (IST)

For Participants in the US: Monday to Friday @9:30 AM – 10:30 AM (EST)

For Participants in the UK: Monday to Friday @2:30 PM – 3:30 PM (BST)

What students have to say about Nesara:

⭐️This course completely changed how I approach testing! The AI & ML fundamentals section helped me finally understand model behavior and the Responsible AI principles were super practical. The hands-on Azure ML and Playwright labs were the best part — very real-world  Anjali R ⭐️Loved the blend of theory and practice. Python lessons were beginner-friendly, and the GenAI modules helped me automate test case generation like never before. The instructors were responsive and gave detailed feedback on our projects.— Rahul M. ⭐️High-quality content and tools. I came in with zero AI background but the structure made it easy to grasp. The LLM evaluation and RAG section was eye-opening — very relevant for modern QA jobs.— Swarna K. ⭐️One of the best QA courses I’ve taken! Real hands-on experience with ChatGPT for testing, Azure services, and Playwright automation made me confident to lead AI testing tasks at work. The final project gave me something concrete to showcase to my manager.— Vikas P. ⭐️Great for career growth. Practical, industry-aligned, and up-to-date. Prompt engineering and GenAI lessons were very relevant. Wish it had a little more time for advanced Python, but overall excellent.— Meera S.

Salient Features:

• 40 Hours of Live Training along with recorded videos
• Lifetime access to the recorded videos
• Course Completion Certificate

Who can enroll for this course?

• Manual QA Testers looking to transition into AI/ML and automation testing
• Automation Test Engineers who want to upskill in AI Testing and Generative AI validation
• Software Test Engineers and QA Analysts working on AI-driven or data-driven applications
• QA Professionals with basic Python knowledge seeking practical automation skills
• DevOps & CI/CD Engineers interested in AI model validation and continuous AI testing
• Developers who want to understand AI testing frameworks, RAG evaluation, and LLM validation
• Tech professionals aiming to grow into AI-powered Quality Engineering roles

What will I learn by the end of this course?

• Understand AI, Machine Learning, and Deep Learning fundamentals and how AI systems differ from traditional software applications
• Test the complete AI lifecycle — from data validation and model training to deployment and monitoring
• Identify and manage AI-specific challenges such as non-deterministic outputs and data drift
• Validate Responsible AI principles including fairness, robustness, accuracy, and explainability
• Configure and execute Azure ML pipelines and work with core AI services
• Write clean, modular Python code tailored for QA automation
• Apply Generative AI techniques, including prompt engineering and AI-driven test case generation
• Use ChatGPT effectively for functional testing and intelligent test data creation
• Automate modern web applications using Playwright
• Evaluate LLM systems using RAG-based validation, faithfulness and relevancy metrics, golden datasets, and LLM-as-Judge techniques
• Design and implement an end-to-end AI testing project covering both UI automation and model output validation

Course syllabus:

📅 Module 1: Foundations of AI & ML Testing (6 Hours)

Topics:

• What is AI, ML, DL – brief overview
• What is Artificial Intelligence?
• Differences between Software Testing & AI Testing
• Foundation for the NLP Service from the Azure
• Foundation for the Computer Vision service from the Azure
• AI Powered information Extraction from the Azure Services
• Foundation for the GenAI and LLM Models
• Foundation for the AI Agents Setup
• AI lifecycle: Data → Model → Deployment → Monitoring.
• Testing challenges in AI/ML (non-determinism, data drift)
• Key quality attributes: Responsible AI Principles, Accuracy, Fairness, Robustness, Explainability etc.

Hands-on:

• Run a simple ML model (Azure ML Pipeline Configuration and Running)

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📅Module 2: Gen AI for QA Engineer (5+ Hours)

Topics:

• Gen-AI for Test Engineer/ QA Engineer.
• Prompt Engineering – Introduction to prompt engineering principles, Techniques for effective prompt creation, Understanding context and intent in prompts, crafting prompts for testing scenarios
• Learn Generative AI & AI Agents in Software Testing
• Generate Test Plan, Test Cases and Test Data using AI
• Functional Testing with ChatGPT.
• How to use ChatGPT in Software Testing and Automation
• LLM API Invocation from different LLM Models.
• Foundation for the Temperature, Top_N, Streaming, Stop etc.
• Implementation of the Concepts in the AI App designing.

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📅 Module 3:  Introduction to Python (5+ hrs)

• Introduction to Python and installation setup
• Understanding variables, data types, and operators
• Control flow: conditional statements and loops
• Working with functions and reusable modules
• Lists, tuples, sets, and dictionaries in test data handling
• String manipulation and regular expressions
• Virtual environments (venv, pip)
• Writing clean, modular Python code
• Mini hands-on tasks for QA automation

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📅 Module 4: AI/LLM Testing Frameworks and Tools (15 hrs along with hands-on)

• Playwright for frontend UI automation (4 hrs)
  • What is Playwright and why it’s popular
  • Setting up playwright
  • Core Playwright Concepts – Locators, assertions, handling dropdowns.
  • Handling the Alert notifications, Iframes
  • Playwright Config services
  • Playwright different reporting types.
  • Page object Models
  • Setting up the test execution flow with different context.
  • Framework building and Integrating with the MCP Server
  • Running the scripts on the CI/CD pipeline using the GitHub, GitHub Actions
• RAG for LLM evaluation (4 hrs)
• What RAG is and where it fits in the AI testing stack
• Key concepts: metrics, test cases, evaluators
• Faithfulness, relevancy, etc
• Core metrics evaluation
• Golden datasets and expected outputs
• LLM as Judge
• Rule based evaluation

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📅 Module 5: AI Project – Hands (5+ hrs along with hands-on)

• Test case generator and Test Script Generator Tool Implementation
• Test automation covering UI and model outputs
• Peer review and instructor feedback

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How can I enroll for this course?

 

Enroll For Free Demo

OR

For any other details, Call me or Whatsapp me on +91-9133190573

 

Live Sessions  Price:

For LIVE sessions – Offer price after discount is 300 USD 259 USD 119 USD Or 13000 INR 12900 INR 9900 Rupees

FAQ – AI/ML & GenAI Testing for QA Engineers – Hands-on Certification Program

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1. What is AI/ML and Generative AI Testing?

AI/ML Testing focuses on validating machine learning models, data quality, model behavior, and deployment pipelines. Generative AI Testing includes validating Large Language Models (LLMs), prompt engineering outputs, RAG systems, fairness, accuracy, and reliability of AI-generated results.

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2. How is AI Testing different from traditional software testing?

Unlike traditional software testing, AI systems are non-deterministic. Outputs may vary for the same input. AI Testing involves validating data quality, model accuracy, bias detection, data drift, explainability, and continuous monitoring across the AI lifecycle.

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3. Who should enroll in this AI Testing course?

This program is ideal for Manual QA Testers, Automation Engineers, QA Analysts, DevOps professionals, Developers, and tech professionals who want to transition into AI-powered Quality Engineering roles.

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4. Is Python mandatory for this course?

Basic Python knowledge is recommended. The course includes Python fundamentals tailored specifically for QA automation, making it suitable for beginners in automation.

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5. Will this course cover Generative AI and LLM testing?

Yes. The course includes prompt engineering, AI-driven test case generation, ChatGPT-based functional testing, RAG evaluation, faithfulness and relevancy metrics, golden datasets, and LLM-as-Judge validation techniques.

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6. What tools and technologies are covered?

The program includes:

• Python for automation

• Playwright for UI automation

• Azure ML pipelines and AI services

• Generative AI testing approaches

• RAG-based LLM evaluation frameworks

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7. Will there be hands-on practice?

Yes. This is a hands-on certification program. You will configure Azure ML pipelines, automate UI applications using Playwright, evaluate LLM outputs, and complete a real-world AI testing project.

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8. What project will I work on?

You will build an end-to-end AI testing solution, including a test case generator tool, UI automation, and AI model output validation.

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9. Does this course provide certification?

Yes. Upon successful completion of the training and project, participants receive a certification validating their AI Testing and Generative AI Quality Engineering skills.

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10. What career opportunities are available after this course?

After completing the program, you can pursue roles such as:

• AI Test Engineer

• AI Quality Engineer

• LLM Validation Engineer

• Automation Engineer (AI-driven systems)

• Model Validation Engineer