ISTQB AI Testing
ISTQB AI Testing
Artificial Intelligence and Machine Learning in particular are used more and more in everyday applications and systems. The ISTQB® AI Testing (CT-AI) certification extends understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI-based systems and using AI in testing, and gives answers to the above questions.
Target group
The Certified Tester AI Testing certification is aimed at anyone involved in testing AI-based systems and/or AI for testing. This includes people in roles such as testers, test analysts, data analysts, test engineers, test consultants, test managers, user acceptance testers, and software developers. This certification is also appropriate for anyone who wants a basic understanding of testing AI-based systems and/or AI for testing, such as project managers, quality managers, software development managers, business analysts, operations team members, IT directors, and management consultants.
Prerequisites
The participants must hold the ISTQB/ISEB Foundation Certificate in Software Testing. As the course material and the certification exam are in English, the participants are expected to have good command of English language.
Course content
Chapter 1: Introduction to AI
- 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)
- Pre-Trained Models
- Standards, Regulations and AI
Chapter 2: Quality Characteristics for AI-Based Systems
- Flexibility and Adaptability
- Autonomy
- Evolution, Bias and Ethics
- Side Effects and Reward Hacking
- Transparency, Interpretability and Explainability
- Safety and AI
Chapter 3: Machine Learning (ML) –Overview
- Forms of ML and ML Workflow
- Selecting a Form of ML
Chapter 4: ML – Data
- Data Preparation as Part of the ML Workflow
- Training, Validation and Test Datasets in the ML Workflow
- Dataset Quality Issues
- Data Quality and its Effect on the ML Model
- Data Labelling for Supervised Learning
Chapter 5: ML Functional Performance Metrics
- Confusion Matrix
- Additional ML Functional Performance Metrics for Classification, Regression and Clustering
- Limitations of ML Functional Performance Metrics
- Selecting ML Functional Performance Metrics
- Benchmark Suites for ML Performance
Chapter 6: ML – Neural Networks and Testing
- Neural Networks
- Coverage Measures for Neural Networks
Chapter 7: Testing AI-Based Systems Overview
- Specification of AI-Based Systems
- Test Levels for AI-Based Systems
- 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
Chapter 8: Testing AI-Specific Quality Characteristics
- 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
- Test Oracles for AI-Based Systems
- Test Objectives and Acceptance Criteria
Chapter 9: Methods and Techniques for the Testing of AI-Based Systems
- Adversarial Attacks and Data Poisoning
- Pairwise Testing
- Back-to-Back Testing
- A/B Testing
- Metamorphic Testing (MT)
- Experience-based testing of AI-based Systems
- Selecting Test Techniques for AI-based Systems
Chapter 10: Test Environments for AI-Based Systems
- Test Environments for AI-Based Systems
- Virtual Test Environments for Testing AI-Based Systems
Chapter 11: Using AI for Testing
- AI Technologies for Testing
- Using AI to Analyze Reported Defects
- Using AI for Test Case Generation
- Using AI for the Optimization of Regression Test Suites
- Using AI for Defect Prediction
- Using AI for Testing User Interfaces
Certificate
After the course, you can take the ISTQB certification exam. The multiple choice exam has 40 questions, and in order to pass the exam, you need to score 31 out of 47 possible points. The duration of the exam is one hour; non-native English-speakers are allowed 15 minutes extra time.
Schedule
Course begins at 9.00 and ends at 16.00 - 16.30. Breakfast is served from 8.15 onwards.
Pricing
TIVIA member price 1 690 € + VAT is valid for TIVIA-s members. Normal price is 1 990 € + VAT. Certification costs are not included in the course price. VAT will be added to all prices,
If you are not yet a member of the TIVIA community, join now and participate in the training at the member's preferential price (membership fees €20–€65)! Check out the corporate membership too !
Cancellation terms
If you cancel the training less than 14 days before the start of the training, we charge 50% of the participation fee. If you cancel the training less than 7 days before the start of the training, we charge the full participation fee. If you do not arrive at the training, we will charge the entire participation fee and any pre-ordered tests.
We reserve the right to make changes to the training courses of our international training partners. Regarding these trainings, we will contact you shortly after your registration.