ISTQB Certified AI Tester – Advanced QA with AI & ML – Live Training
The ISTQB Certified AI Tester – Complete Mastery Program is a comprehensive, hands-on training designed to help QA professionals, automation testers, and developers understand and test AI-based systems effectively. This course covers everything from the fundamentals of Artificial Intelligence to AI-specific quality attributes, test techniques, and ethical considerations, aligning with the latest ISTQB Certified AI Tester syllabus.
Learners will explore how AI and Machine Learning systems differ from traditional software, and how to plan, design, and execute effective tests for AI-driven applications. Through a blend of theory, real-world examples, and practical exercises, participants will gain the skills to evaluate AI models, data pipelines, and automated decision-making systems with confidence.
By the end of this program, you’ll not only understand AI-powered testing tools and practices, but also how to leverage AI in test automation to optimize quality, accuracy, and coverage — preparing you for both ISTQB certification and next-generation QA roles.
About the Instructor:
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Yash is a Senior QA Lead at Wrkspot with over 8 years of professional IT experience, having previously worked with top-tier companies like Meesho and Cisco. He brings deep expertise in UI and API automation testing using tools such as Selenium, Playwright, RestAssured, Cucumber, TestNG, Postman, and Python requests. Yash is highly skilled in designing and building robust, data-driven automation frameworks from scratch, with support for cross-browser testing and seamless CI/CD integration. In addition to his automation expertise, Yash has a growing interest and foundational knowledge in AI-powered testing tools and AI-driven automation frameworks. He explores how Artificial Intelligence and Machine Learning can enhance test case generation, defect prediction, and intelligent reporting, integrating these concepts into modern automation strategies. For the past two years, Yash has been actively training and mentoring aspiring automation testers. He has conducted numerous Playwright training sessions and successfully trained a large number of professionals. Passionate about teaching, he enjoys sharing his practical knowledge and industry insights to help learners advance in their automation careers. He also holds intermediate proficiency in DevOps tools like Docker, Docker Swarm, Ansible, and Kubernetes. His long-term vision is to evolve into an Automation/DevOps Engineer who leverages AI-driven testing approaches to drive innovation and excellence in software delivery. |
Videos:
Day 1 Video:
Day 2 Video
Free Day 3 Session On:
28th November @ 8 PM – 9 PM (IST) (Indian Timings)/
28th November @ 9:30 AM – 10:30 AM (EST) (U.S Timings)/
28th November@ 2:30 PM – 3:30 PM (BST) (UK Timings)
Class Schedule:
For Participants in India: Monday to Friday @ 8:00 PM – 9:00 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)
Live Sessions Price:
For LIVE sessions – Offer price after discount is 135 USD 129 99USD Or USD25000 INR 19000 INR 7900 Rupees.
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What student’s have to say about Trainer :
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👩 Aaradhya: Yash sir made complex AI testing concepts so easy to understand. The way he connected real-time automation scenarios with AI-based systems was amazing. I finally feel confident about preparing for the ISTQB AI Tester certification! 👦 Aamir: 👩 Emily: 👦 Rohit: 👩 Zara: 👦 Ethan: |
What will I Learn by end of this course?
- Understand Artificial Intelligence Fundamentals
- Differentiate AI and Conventional Systems
- Explore AI Frameworks, Tools & Hardware
- Understand AI as a Service (AIaaS)
- Master Machine Learning Concepts & Workflows
- Prepare and Label Data for ML Systems
- Evaluate ML Models Using Performance Metrics
- Understand Neural Networks & Perceptrons
- Learn Testing Strategies for AI-Based Systems
- Test AI-Specific Quality Characteristics (Bias, Ethics, Transparency)
- Apply Advanced AI Testing Techniques (Adversarial, Metamorphic, Pairwise)
- Perform Hands-On AI Model Evaluation & Explainability Testing
- Build Real-World Skills in AI System Validation
- Become Industry-Ready as an AI Tester or Engineer
Salient Features:
- 24 Hours of Live Training along with recorded videos
- Lifetime access to the recorded videos
- Course Completion Certificate
Who can enroll in this course?
- Software Testers and QA Engineers
- Automation Testers Looking to Upskill in AI
- AI & ML Enthusiasts Seeking Practical Testing Knowledge
- Developers Interested in Testing AI-Based Applications
- Performance Engineers Exploring AI Testing Concepts
- Students and Fresh Graduates in Computer Science or IT
- Professionals Preparing for ISTQB Certified AI Tester Exam
- Anyone Passionate About Ensuring Quality in AI Systems
Course syllabus:
Introduction to AI (105 minutes)
- Definition of AI and AI Effect
- Narrow, General and Super AI
- AI-Based and Conventional Systems
- AI Technologies
- AI Development Frameworks
- Hardware for AI-Based Systems
- AI as a Service (AIaaS)
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- Contracts for AI as a Service
- AIaaS Examples
- Pre-Trained Models
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- Introduction to Pre-Trained Models
- Transfer Learning
- Risks of using Pre-Trained Models and Transfer Learning
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Standards, Regulations and AI
Quality Characteristics for AI-Based Systems (105 minutes)
- Flexibility and Adaptability
- Autonomy
- Evolution
- Bias
- Ethics
- Side Effects and Reward Hacking
- Transparency, Interpretability and Explainability
- Safety and AI
Machine Learning (ML) – Overview (145 minutes)
- Forms of ML
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- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- ML Workflow
- Selecting a Form of ML
- Factors Involved in ML Algorithm Selection
- Overfitting and Underfitting
- Overfitting
- Underfitting
- Hands-On Exercise: Demonstrate Overfitting and Underfitting
ML – Data (230 minutes)
- Data Preparation as Part of the ML Workflow
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- Challenges in Data Preparation
- Hands-On Exercise: Data Preparation for ML
- Training, Validation and Test Datasets in the ML Workflow
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- Hands-On Exercise: Identify Training and Test Data and Create an ML Model
- Dataset Quality Issues
- Data Quality and its Effect on the ML Model
- Data Labelling for Supervised Learning
- Approaches to Data Labelling
- Mislabeled Data in Datasets
ML Functional Performance Metrics (120 minutes)
- Confusion Matrix
- Additional ML Functional Performance Metrics for Classification, Regression and Clustering
- Limitations of ML Functional Performance Metrics
- Selecting ML Functional Performance Metrics
- Hands-On Exercise: Evaluate the Created ML Model
- Benchmark Suites for ML
ML – Neural Networks and Testing (65 minutes)
- Neural Networks
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- Hands-On Exercise: Implement a Simple Perceptron
- Coverage Measures for Neural Networks
Testing AI-Based Systems Overview (115 minutes)
- Specification of AI-Based Systems
- Test Levels for AI-Based Systems
- Input Data Testing
- ML Model Testing
- Component Testing
- Component Integration Testing
- System Testing
- Acceptance Testing
- Test Data for Testing AI-based Systems
- Testing for Automation Bias in AI-Based Systems
- Documenting an AI Component
- Testing for Concept Drift
- Selecting a Test Approach for an ML System
Testing AI-Specific Quality Characteristics (150 minutes)
- Challenges Testing Self-Learning Systems
- Testing Autonomous AI-Based Systems
- Testing for Algorithmic, Sample and Inappropriate Bias
- Challenges Testing Probabilistic and Non-Deterministic AI-Based Systems
- Challenges Testing Complex AI-Based Systems
- Testing the Transparency, Interpretability and Explainability of AI-Based Systems
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- Hands-On Exercise: Model Explainability
- Test Oracles for AI-Based Systems
- Test Objectives and Acceptance Criteria
Methods and Techniques for the Testing of AI-Based Systems (245 minutes)
- Adversarial Attacks and Data Poisoning
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- Adversarial Attacks
- Data Poisoning
- Pairwise Testing
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- Hands-On Exercise: Pairwise Testing
- Back-to-Back Testing
- A/B Testing
- 9.5 Metamorphic Testing (MT)
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- Hands-On Exercise: Metamorphic Testing
- Experience-Based Testing of AI-Based Systems
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- Hands-On Exercise: Exploratory Testing and Exploratory Data Analysis (EDA)
- Selecting Test Techniques for AI-Based Systems
How can I enroll for this course?
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For any other details, Call me or Whatsapp me on +91-9133190573
Live Sessions Price:
For LIVE sessions – Offer price after discount is 135 USD 129 99 USD Or USD25000 INR 19000 INR 7900 Rupees.
Sample Course Completion Certificate:
Your course completion certificate looks like this……
Important Note:
To maintain the quality of our training and ensure smooth progress for all learners, we do not allow batch repetition or switching between courses. Once you enroll in a batch, please make sure to attend the classes regularly as per the schedule. We kindly request you to plan your learning accordingly. Thank you for your support and understanding.