ISTQB® AI Testing course

This course is designed for you if you are:

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Involved in testing AI‑based systems and/or use AI for testing

basic understanding of testing AI-based systems

Looking to acquire a basic
understanding of testing AI-based systems and/or use AI for testing

Anyone working with AI-based systems

Anyone working with AI-based systems

official ISTQB® Certified Tester AI Testing certification

Interested in obtaining the official
ISTQB® Certified Tester AI Testing certification

Plans and Pricing

If you would like to register your interest in the course and/or learn more, please pick your preferred plan and submit your details via one of the forms below.
We will be in touch as soon as the course is ready to launch.

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Autonomous

Guided

Enterprise

Course format Monthly course subscription 6-week course (with additional 2 weeks of access to materials) Are you limited on time or have specific requests based on your current project? Let us adjust the course to your needs.
Access to the training materials library
Chat support
Access to 250+ test questions
Mock Exam at the end of the course, to track your progress
Certificate upon course completion
Tips on how to pass the exam
20+ Q&A sessions with accredited expert
6 hands-on Python workshops
Enrolment dates Continuous enrolment 13 January
Price £99/month £800
 

Enrol Now

Register

Still not sure?

Access the first chapter of the course via a one-week trial – check videos, slides, reading materials and test questions at no charge.

Get your trial - Access the first chapter at no cost.

Why choose us?

* Available in Guided and Enterprise plans

Our Team

Iosif Itkin, CEO and co-founder, Exactpro

Course Director

Iosif Itkin

 

CEO and co-founder, Exactpro

GASQ

ISTQB® Certified Tester AI Testing
A4Q 20-AIFL-171752-43

GASQ

ISTQB® Certified Tester Foundation Level
iSQI 19-CTFL-151899-12

Iuliia Emelianova

Course Developer

Iuliia Emelianova

 

AI Tester, Data Scientist, Researcher

GASQ

ISTQB® Certified Tester AI Testing
GASQ ID 370555

GASQ

ISTQB® Certified Tester Foundation Level
GASQ ID 77734

Dmitrii Degtiarenko, Creative Manager, Exactpro

Course Developer

Dmitrii Degtiarenko

 

Creative Manager

GASQ

ISTQB® Certified Tester Foundation Level
GASQ ID 34720

Elena Treshcheva

Course Developer

Elena Treshcheva

 

Program Manager

GASQ

ISTQB® Certified Tester AI Testing
ASTQB - ISTQB 24-CT-AI-00023-USA

GASQ

ISTQB® Certified Tester Foundation Level
GASQ ID 759389

Janna Zabolotnaya, Marketing Manager

Course Administrator

Janna Zabolotnaya

 

Marketing Manager

Anna-Maria Lukina, Marketing Director, Exactpro

Outreach Director

Anna-Maria Lukina

 

Marketing Director

GASQ

ISTQB® Certified Tester Foundation Level
GASQ ID 17465

Learning Goals

1

Discover ways to leverage the power of AI tools

2

Identify key points influencing the quality of ML models

3

Acquire a deep understanding of the testing complexity of AI systems

4

Gain hands-on experience

5

Apply different test strategies specific to AI systems

6

Develop and execute test cases for AI systems

7

Stay current with the latest AI advancements and emerging trends

8

Get better prepared for the official ISTQB® CT-AI Tester Exam

Information Hub

Read on to learn more about what to expect from the course.

At the end of the course, you will have the opportunity to take the Mock Exam to check your knowledge. Please mind that the official ISTQB® Certified Tester AI Testing (CT-AI) Exam is not included in the price.

The ISTQB® Certified Tester- AI Testing training course covers 11 chapters of the certification syllabus:

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
  • Pre-trained models
  • Standards, regulations and AI

Chapter 2: Quality Characteristics for AI-Based Systems

  • Flexibility and adaptability
  • Autonomy
  • Evolution
  • Bias
  • Ethics
  • Side effects and reward hacking
  • Transparency, interpretability and explainability
  • Safety and AI

Chapter 3: Machine Learning (ML) - Overview

  • Forms of ML
  • ML workflow
  • Selecting a form of ML
  • Factors involved in ML algorithm selection
  • Overfitting and underfitting

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

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 complex AI-based systems
  • Challenges testing probabilistic and non-deterministic 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
  • A/B testing
  • Back-to-back testing
  • Metamorphic testing
  • 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 analyse reported defects
  • Using AI for test case generation
  • Using AI for the optimisation of regression test suites
  • Using AI for defect prediction
  • Using AI for testing user interfaces

You can get the Course certificate after successfully completing the Mock Exam (with the pass mark of 65%) which you can place on Linkedin. Please note that this is not an official ISTQB® Certified Tester AI Testing (CT-AI) certificate.

Exactpro is an ISTQB®-accredited Training Provider for the Specialist Certified Tester AI Testing certification.

We recommend following the official ISTQB® Certified Tester AI Testing (CT-AI) Syllabus.

Exactpro is an award-winning provider of AI-enabled software testing and development services for mission-critical technology of the global financial markets.

Exactpro team has successfully tested and released into live service such complex financial systems as trading, clearing and settlement platforms, market data, collateral and risk management systems, as well as regulatory reporting systems. We are happy to share years of experience with you on this course.

Our specialists regularly conduct global educational events. Learn more about Exactpro at exactpro.com.

ISTQB_AccreditedTrainingProvider
Exactpro’s AI Testing Training Course Awarded Most Innovative Professional Development Initiative by A-Team Group
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