ISTQB® AI Testing
Do you not only want to understand AI, but also want to go one step further and also ensure its quality and learn how to test ML models? This training first takes you through AI and machine learning basics as well as different specifications, data and metrics. You will then learn techniques and testing procedures to test AI systems.
Your learning objectives
Target group
Course content
- Definition of AI and AI effects
- 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
- AI standards and regulations
- Flexibility and adaptability
- autonomy
- evolution
- Bias
- ethics
- Side effects and reward hacking
- Transparency, interpretation and explainability
- Security and AI
- Forms of machine learning
- ML workflow
- Select a form of ML
- Factors influencing the selection of ML algorithms
- Overfitting and underfitting
- Data preparation as part of the ML workflow
- Training, validation and testing datasets in the ML workflow
- Quality problems in the data set
- Data quality and its impact on the ML model
- Data labeling for supervised learning
- Confusion Matrix
- ML performance metrics for classification, regression, and clustering
- Limitations of ML performance metrics
- Select ML performance metrics
- Benchmark suites for ML performance metrics
- Specification of AI-based systems
- Test levels for AI-based systems
- Test data for testing AI-based systems
- Testing automation bias in AI-based systems
- Document AI elements
- Test concept drift
- Choosing a testing approach for an ML system
- Challenges when testing self-learning systems
- Testing autonomous self-learning systems
- Test algorithmic, sampling, and inappropriate bias
- Challenges in testing probabilistic and non-deterministic AI-based systems
- Challenges in testing complex AI-based systems
- Testing the transparency, interpretation and explainability of AI-based systems
- Test oracle for AI-based systems
- Test objectives and acceptance criteria
- Adversarial attacks and data poisoning
- Pairwise testing
- A/B testing
- Back-to-back testing
- Metamorphic Testing (MT)
- Experience-based testing of AI-based systems
- Selection of testing techniques for AI-based systems
- Test environments for AI-based systems
- Virtual test environments to test AI-based systems
- AI technologies for testing
- Using AI to analyze bug reports
- Use of AI to generate test cases
- Using AI to optimize regression testing
- Use of AI for error prediction
- Using AI for user interface testing
Certification
Certification according to ISTQB is possible for this training.
More about certificationsWhat we recommend after this course
Course at a glance
-
Certification ISTQB® certification possible
-
Level Advanced
-
Duration 4 days
-
Price EUR 1,650.-- excl. VAT excl. examination fee
ISTQB® Test Manager & Tester
Back to the roleUpcoming Dates & Registration
ISTQB® AI Testing
| Date | Code | Location | Course language | Duration | Price | Book this date |
|---|---|---|---|---|---|---|
| – | QM 15 | Webinar | English | 4 days | EUR 1,650.-- excl. VAT | Book this date |
| – | QM 15 | Webinar | English | 4 days | EUR 1,650.-- excl. VAT | Book this date |
| – | QM 15 | Webinar | English | 4 days | EUR 1,650.-- excl. VAT | Book this date |
| – | QM 15 | Webinar | English | 4 days | EUR 1,650.-- excl. VAT | Book this date |
All course dates are quoted excluding the examination fee.
All dates at one location: Online Trainings & Live Webinars
Certified trainings
Internationally recognized certifications for your career.
Experienced trainers
Learn from competent experts with practical experience.
Flexible formats
Webinars, video trainings or on-site – entirely according to your needs.
Ask us a question
Not sure yet which training fits, or do you need an offer for several participants? Write to us — we will answer within one to two business days.