ISTQB CT-AI Exam With Confidence Using Practice Dumps

The syllabus explains that input changes that arein the same domainas what was used for training are expected to be handled with adaptability:

"Adaptability refers to the ability of a system to adjust its behavior in response to changes in its environment or inputs. This includes changes to the inputs which are still within the expected operational range of the system, such as resolution changes in images or sensor data."

(Reference: ISTQB CT-AI Syllabus v1.0, Section 7.6 and 8.2)

The syllabus explains:

"Where the internal structure of an AI-based system is too complex for humans to understand, the system can only be tested as a black box. Even when the internal structure is visible, this provides no additional useful information to help with testing."

This confirms that black-box testing is chosen because the tester does not need to understand the system’s internal structure.

(Reference: ISTQB CT-AI Syllabus v1.0, Section 8.5, page 61 of 99)

The ISTQB CT-AI syllabus describes severaldata quality aspectsthat affect ML performance. In Section2.2 – Data Preparation, it explains that datasets may suffer from issues such asincomplete data,irrelevant data,incorrect data,unbalanced data, or data lacking preprocessing. “Incomplete data” means thatportions of the required data are missing, often because some time periods, records, or sources were not captured. This aligns exactly with Option A, which correctly identifies missing intervals as incomplete data.

Option B is incorrect: “data not preprocessed” refers to data that has not undergone normalization, cleaning, or transformation—not data recorded incorrectly. Option C is wrong because irrelevant datadoesnegatively affect ML models by introducing noise and unnecessary features. The syllabus explicitly states that including irrelevant features can degrade model learning. Option D is incorrect: “unbalanced data” relates todisproportionate class distribution, not recency or freshness of data.

Thus, OptionAis the only statement that correctly matches the syllabus definition of this data quality aspect.