1,650 €−165 €1,485 €
What this module delivers.
How the training runs
- Method
- Build models, evaluate them, and make them fail on purpose
- Basis
- Official ISTQB syllabus 2.0
- Outcome
- 40 questions, 29 of 44 points, exam booked separately
Dates & booking
Choose a date that fits
2 dates
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Fit
Who this module is designed for
Typical roles
- You test a system whose behaviour comes out of training data rather than out of code.
- You are accountable for the quality of the data a model is trained on.
- You have to justify when a model is good enough to go into production.
Prerequisites
Formal prerequisites
- For exam admission: the ISTQB Certified Tester Foundation Level certificate.
What helps you in the course
- Around six months of hands-on testing, development or data science work, as the syllabus recommends.
Consider instead CT-GenAI · ISTQB® - Certified Tester Testing with Generative AI Training Puts generative AI to work in testing, where CT-AI examines AI-based systems.
Curriculum
ISTQB CT-AI Course in Detail
Syllabus 2.0 splits CT-AI into seven chapters across at least 19.5 hours of instruction. It runs from the fundamentals of AI through machine learning to the three levels the testing happens on: input data, the model, and the development toolchain.
01Introduction to Artificial Intelligence
This chapter settles what exactly the rest of the course is talking about.
- AI-based against conventional systems; narrow, general and super AI
- The different types of AI technology, and generative AI
- Hardware, development and hosting of AI models
- Machine learning development frameworks, regulations and standards
02Quality Characteristics for AI-Based Systems
The short part that fixes what an AI system is measured against at all.
- AI-specific quality characteristics under ISO/IEC 25059, and what sets them apart from classic ones
- AI and safety
- Acceptance criteria for AI-based systems
03Machine Learning
The longest chapter, and the most practical: here you build a model yourself.
- The forms of machine learning, and the machine learning workflow
- Pretrained models, fine-tuning and retrieval-augmented generation
- Data preparation, and calculating the functional performance metrics
- How a deep neural network works, and coverage measures for one
04Testing AI-Based Systems
This is where the case for testing AI systems differently gets made.
- Locked against adaptive AI-based systems
- Why the test approach has to be statistical, and what works as a test oracle
- Testing generative AI, and red teaming
- Test levels and risk-based testing for machine learning systems
05Input Data Testing for Machine Learning Systems
The first of the three levels the testing happens on: what goes into the model.
- Input data risks and the mitigations against them
- Testing for bias and for data representativeness
- Data pipeline testing and dataset constraint testing
- Checking the labels for correctness
06Model Testing for Machine Learning Systems
The second level, and the toolkit for defects with no single correct answer.
- Model risks, model documentation and review
- Functional performance testing of probabilistic systems, and adversarial testing
- Metamorphic testing, A/B testing and back-to-back testing
- Drift testing, and testing for overfitting and underfitting
07Machine Learning Development Testing
The third level: the tooling and the deployment, not the model itself.
- Risks from frameworks and their APIs, and the tests against them
- Installability and rollback testing ahead of deployment
- Canary and shadow testing in production
Outcome
What you will be able to do afterwards
- 01
You tell AI-based systems from conventional ones and place the technology in use.
- 02
You formulate acceptance criteria along the AI-specific quality characteristics defined in ISO/IEC 25059.
- 03
You evaluate model performance with a confusion matrix, precision, recall and F1 score.
- 04
You judge coverage measures for neural networks and what they actually tell you.
- 05
You justify the statistical approach to testing and define test oracles for AI systems.
- 06
You test input data for bias, representativeness and correct labelling.
- 07
You surface model defects with metamorphic testing, A/B tests and back-to-back tests.
- 08
You recognise data drift and concept drift, and plan the testing against them.
Certified Tester AI Testing
Once you pass, you receive the official ISTQB certificate at Specialist Level. It is valid for life and never needs renewing.
Certification terms istqb.org ↗Examination
ISTQB CT-AI examination
40Questions
- Working time
- 60 min
- Pass mark
- 29 / 44
- Format
- Multiple Choice
- Conditions
- Closed Book
The examination is administered by our exam partners iSQI and Brightest, not by tecnovy. The syllabus's hands-on exercises are compulsory in the course but explicitly not examinable. If you do not sit the exam in your native language you can apply for 25 percent more time; the application has to be in at least one week before the exam date.
Official examination rules istqb.org ↗Proof of attendance
Certificate of participation
≥80%attendance
The tecnovy certificate of participation records your attendance of the CT-AI training, not a passed ISTQB examination.
Open the Certificate Showroom tecnovy → Offer scope
What the course price does not cover
Not included
- Fee for the ISTQB certification examinationThe exam fee is charged by the exam partner, not by tecnovy: CHF 250 excl. VAT, around EUR 270. The euro amount is converted at the daily rate and shown in the booking step.
Trainers
Why tecnovy
What you get on top with us
01
Certification Guarantee
We have an impressive pass rate on the certification exam, so we're pretty confident you'll pass the exam on the first try. However, we're giving you the 2nd try for free. Promised!
02
Certificate Showroom
Get your certificate of participation and, if you have one, add your exam certificate from E-Learning. Fully automated, beautifully designed. Just for you, only at tecnovy.
03
Flexible Date Change
If you are not able to attend the course, you can rebook your training free of charge up to one week before the start of the training.
04
Attend Twice, Pay Once
You are welcome to visit the training course online again within a year as a refresher or exam preparation.
05
No Slideshow, Hands-On!
Promised: no PowerPoint marathon. We work in groups, tie theory to practice, and you get real project examples from our experienced trainers plus the exchange with like-minded people.
06
Learn from Experts
We always guarantee you the use of didactically and methodically first-class qualified trainers who draw their knowledge from training experience as well as professional practical and project experience.
FAQs
Frequently asked questions
01What is the difference between CT-AI and CT-GenAI?
02Which syllabus version does the CT-AI training run on?
03I hold CT-AI 1.0. Do I have to sit the new examination?
04What do I need in order to sit the CT-AI examination?
05How is the CT-AI examination structured?
06Is the examination part of the tecnovy CT-AI training?
07Do I have to do calculations in the exam?
08What do I actually do hands-on in the CT-AI training?
09Why does the CT-AI training run for three days?
What does your training at tecnovy look like?