ISTQB CT-AI Exam With Confidence Using Practice Dumps

The syllabus defines clustering as:

“Clustering: This is when the problem requires the identification of similarities in input data points that allows them to be grouped based on common characteristics or attributes. For example, clustering is used to categorize different types of customers for the purpose of marketing.”

(Reference: ISTQB CT-AI Syllabus v1.0, Section 3.1.2, page 26 of 99)

Section1.6.3 – Reinforcement Learningof the ISTQB CT-AI syllabus states that reinforcement learning (RL) is based on anagent interacting with an environment, performing actions, and receivingrewards or penalties. The core concept is thereward function, which guides the agent’s learning process. The syllabus emphasizes that training in RL isdriven by rewards, and the agent aims to maximize cumulative reward over time. Therefore, OptionCdirectly reflects the correct description: the agent learns by being rewarded for successful actions .

Option A is incorrect because RL doesnotuse labeled data; that applies to supervised learning. Option B contradicts the syllabus definition: RL fundamentallyrequiresinteraction with the environment. Option D is incorrect because the reward function isdefined by humans, not learned by the agent; the agent learns apolicy, not the reward function itself.

Thus, OptionCis the only statement consistent with RL as defined in the syllabus.

The syllabus describes exploratory testing as especially useful when there are poor specifications or test oracle problems:

“Exploratory testing is especially useful when there are poor specifications or test oracle problems, which is often the case for AI-based systems.”

(Reference: ISTQB CT-AI Syllabus v1.0, Section 9.6, page 70 of 99)