Which hardware consideration is most likely to be a trade-off when choosing between a powerful GPU and a more energy-efficient option for an AI system?

Model accuracy vs. training time

Processing power vs. energy consumption

Memory capacity vs. storage speed

A company is deploying an AI model for real-time object detection on a fleet of autonomous drones. The drones have limited battery and processing power. Which hardware is most appropriate for running the model on the drones?

Edge device with a specialized AI accelerator

A financial firm wants to detect fraudulent transactions in real time. The data is highly structured (transaction amount, time, merchant, etc.) and the volume is moderate. The team has experience with traditional statistical models and wants to avoid the complexity of deep learning. Which approach and hardware is most appropriate?

Machine learning with gradient boosting on CPUs

Machine learning with support vector machines on TPUs

Deep learning with a neural network on GPUs

Expert system with if-then rules on edge devices

A company is building a chatbot to handle customer service inquiries. The chatbot needs to understand user intent and extract entities like dates and product names. The team is considering using an NLP framework. Which approach is most appropriate?

Build a rule-based system with regular expressions

Use a simple bag-of-words model with logistic regression

Use a pre-trained language model with fine-tuning

Use a computer vision model to process text

Certified Tester AI Testing

Domain 1Objective 2

AI Technologies and Frameworks CT-AI Practice Questions (Page 1)

Part of the Domain 1: Introduction to AI domain, which makes up ~7% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~2–3 in this domain), expect 1–1 from this objective — we provide 28 practice questions to prepare you well beyond it. (estimate)

28questions here

6free pages

7concepts

Questions 1–5

1application · medium
A research team is prototyping a novel neural network architecture that requires dynamic computation graphs and frequent experimentation. They value Pythonic syntax and easy debugging. Which framework should they choose?
Select an answer first
2foundation · easy
Which hardware consideration is most likely to be a trade-off when choosing between a powerful GPU and a more energy-efficient option for an AI system?
Select an answer first
3application · medium
A company is deploying an AI model for real-time object detection on a fleet of autonomous drones. The drones have limited battery and processing power. Which hardware is most appropriate for running the model on the drones?
Select an answer first
4application · medium
A financial firm wants to detect fraudulent transactions in real time. The data is highly structured (transaction amount, time, merchant, etc.) and the volume is moderate. The team has experience with traditional statistical models and wants to avoid the complexity of deep learning. Which approach and hardware is most appropriate?
Select an answer first
5expert · hard
A company is building a chatbot to handle customer service inquiries. The chatbot needs to understand user intent and extract entities like dates and product names. The team is considering using an NLP framework. Which approach is most appropriate?
Select an answer first

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AI Technologies and Frameworks CT-AI Practice Questions (Page 1)

Questions 1–5

A research team is prototyping a novel neural network architecture that requires dynamic computation graphs and frequent experimentation. They value Pythonic syntax and easy debugging. Which framework should they choose?

Which hardware consideration is most likely to be a trade-off when choosing between a powerful GPU and a more energy-efficient option for an AI system?

A company is deploying an AI model for real-time object detection on a fleet of autonomous drones. The drones have limited battery and processing power. Which hardware is most appropriate for running the model on the drones?

A company is building a chatbot to handle customer service inquiries. The chatbot needs to understand user intent and extract entities like dates and product names. The team is considering using an NLP framework. Which approach is most appropriate?

Keep studying — Domain 1: Introduction to AI