Ezanne Grobler, iOCO Quality Assurance Competency Director.
iOCO has launched one of South Africa’s first locally developed ISTQB-compliant AI testing e-learning courses to upskill quality assurance testers on the latest best practices in AI system testing.
Designed by iOCO subject matter expert Aysha Sassman, this course follows the International Software Testing Qualification Board (ISTQB) Certified Tester-AI Testing (CT-AI) syllabus, a globally recognized benchmark for testing professionals.
iOCO is preparing its Testing AI Fundamentals course to be certified by SASTQB.
Meet your AI-specific testing skill needs
“This new course responds to the growing market need for AI-specific training for testers, developers and business stakeholders,” said Ezanne Grobler, Head of Quality Assurance Competency at iOCO.
Grobler says, “Traditional testing skills alone are not enough for AI testing; additional skills, characteristics, and techniques are also required. Many AI systems do not have a single, deterministic, expected outcome for each input, and their behavior can change over time as the model retrains or data drifts. Therefore, alternative ways to define oracles and acceptance criteria are needed. Traditional systems and intelligent The key difference between systems is the mere fact that traditional systems provide the expected results, so that system-based accuracy can be verified and verified.”Many intelligent systems do not have a single definitive expected result for each input, and their behavior can change over time as the model is retrained or the data distribution changes. Therefore, testing intelligent systems is completely different. ”
“Traditional testing uses techniques such as boundary value analysis and equivalence partitioning because they have clear specifications and can predict expected results. For AI systems, testing methods must also look for things like bias, hallucinations, and model or data drift. As these systems learn from data and are often retrained or used in changing environments, their behavior can gradually drift away from their original intent if the data and feedback they learn is not actively monitored and managed.” AI Understanding system quality assurance is equally important for QA testers, developers, data analysts, and business stakeholders, she added.
Comprehensive course content
iOCO’s new Testing AI Fundamentals e-learning course is designed to make AI and AI quality assurance and testing practical and easy to understand.
Grobler explains that the course was initially developed over a year to upskill internal staff. “However, we found this to be such a comprehensive and important guide that we decided to make it available as a self-paced e-learning course for the broader IT and business community,” she says.
“We have done a lot of training and lectures, but this is our first e-learning course,” she says. Grobler believes the course is unique as an e-learning offering because it includes exclusive access to a private community forum, allowing learners to connect with like-minded experts working on AI testing. She expects interest from people all over South Africa, other parts of Africa and even internationally.
At recent meetings in Johannesburg and Cape Town, the soft launch of the course was well received, with the majority of participants expressing interest in taking part in the training.
“In-house testers who completed the training acknowledged that it was a difficult course, but responded positively to the use of case studies, visuals, and videos to turn theory into practical, testable knowledge. This course equips participants with the skills they need to assess the quality of AI and reduce AI-related risks in their organizations,” she says.
Grobler added, “You can benefit from this course as it gives you insight into the layers of artificial intelligence systems and helps you understand the risks associated with AI, the governance required for AI, and how to mitigate those risks through testing, validation, and validation.”
This course does not require any prior experience in AI or QA. Learn the basic concepts of AI, how quality is defined in AI, and how to apply modern techniques such as adversarial testing, back-to-back testing, metamorphic testing, and exploratory testing.
Although the course is self-study and can be completed at your own pace, Grobler estimates that it requires approximately 40 hours of intensive study. The learning journey includes modules such as Introduction to AI, Quality Characteristics of AI Systems, Fundamentals of Machine Learning, Testing of AI-based Systems, Data Processing, and Performance Metrics. Learners will gain practical insights through interactive content and quizzes, and gain a comprehensive understanding of AI from a business and technical perspective, within a globally recognized framework for testing and assurance of AI systems. Upon completion of the course, participants will be on the path to the ISTQB CT-AI certification.
Grobler said: “Although we do not have an ISTQB certification yet, we follow the syllabus, so once you complete the course you will have a strong foundation to write the ISTQB exam unless you already have an ISTQB Foundation Level (CTFL) certification.”
This course will be continuously updated as AI evolves and the ISTQB syllabus changes. “As the AI environment continues to evolve, ISTQB recently launched a new specialized syllabus on the use of generative AI to enhance software testing (CT-GenAI). In the same spirit, you can expect AI-related course content to be reviewed and updated more frequently than traditional testing content, which typically changes less.”
iOCO is currently running a special program to launch the Testing AI Fundamentals e-learning course. of The first 100 people to register will receive a 50% discount and can register for only R2 475.
Click here to register. Click on the “Login” button, scroll down to “Create a new account” and follow the process until the point of payment.
