CAICの実際の学習ガイド資料は、より良いレビューを得るのに役立ちます。これは非常に直感的な標準ですが、包括的ではない場合があるため、テストCAIC認定を取得することの重要性を知っておく必要があります。自分の能力を証明するのに十分な資格を持っている場合にのみ、厳しい現実の中で敵を打ち負かすことができます。 CAICの実際の質問は、CAIC認定試験に合格し、認定資格をより迅速かつ効率的に取得するのに役立つと考えています。
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質問 # 34
Select the INCORRECT statement for DevOps architect.
正解：C
解説：
The incorrect statement is B because business development and planning are not core technical components of a robust DevOps architecture. DevOps architecture mainly focuses on automation, CI/CD pipelines, infrastructure management, deployment strategy, monitoring, alerting, scalability, reliability, security, and disaster recovery. While business planning may influence technology priorities, it is not normally listed as an essential DevOps architecture component.
Monitoring and alerting are essential because they help teams detect failures, performance degradation, service outages, and abnormal system behavior. Disaster recovery is also a critical responsibility because DevOps architects must design systems that can recover from failures with minimal downtime and limited data loss. CI/CD pipeline creation and optimization are central DevOps responsibilities because they enable faster, repeatable, and reliable software delivery. Therefore, options A, C, D, and E are valid DevOps architecture statements, while B is the incorrect one.
質問 # 35
Artificial general intelligence (AGI) is also commonly expressed as ____.
正解：E
解説：
Artificial General Intelligence, or AGI, is commonly referred to as Strong AI because it describes an AI system with human-like cognitive ability across many different tasks and domains. Unlike narrow or weak AI, which is designed to perform a specific task such as image recognition, language translation, recommendation, fraud detection, or chatbot response generation, AGI would be able to understand, learn, reason, adapt, and solve problems broadly in a way similar to human intelligence.
Weak AI is incorrect because it refers to task-specific AI systems that operate within limited boundaries.
General AI is related in meaning, but the commonly used expression for AGI in AI classification is Strong AI.
SuperAI is different because it refers to intelligence that would exceed human intelligence, while ExpertAI is not the standard term for AGI. Therefore, the correct answer is B. Strong AI .
質問 # 36
Which of the following is a step for the Value Engineering Framework?
正解：C
解説：
The correct answer is E. All of the above because the Value Engineering Framework focuses on identifying, delivering, and expanding measurable business value from data and AI initiatives. "Define value creation" is a key step because organizations must first clarify the business problem, expected outcomes, success metrics, stakeholders, and value drivers before investing in an AI solution.
"Realize value creation" is also correct because value must be converted from a planned objective into actual operational or financial impact. This may involve deploying the solution, measuring results, improving processes, reducing cost, increasing revenue, improving risk management, or enhancing customer outcomes.
"Scale value creation" is correct because successful AI initiatives should not remain limited to isolated pilots.
Organizations need to scale proven use cases across teams, business units, workflows, and enterprise platforms to maximize return on investment and long-term impact. Since all three options represent steps in value engineering, the best answer is E. All of the above .
質問 # 37
Which of the following is NOT a common supervised learning model/algorithm?
正解：C
解説：
The correct answer is E. None of the above because K-nearest neighbors, random forest, and decision trees are all common supervised learning models or algorithms. Supervised learning uses labeled data to train a model so it can predict an output label or target value for new data.
K-nearest neighbors is a supervised learning algorithm commonly used for classification and regression. It predicts outcomes by comparing a new data point with the most similar labeled examples in the training data.
Random forest is also a supervised learning algorithm. It builds multiple decision trees and combines their results to improve prediction accuracy and reduce overfitting. Decision trees are supervised models that split data based on feature values to make classification or regression predictions.
Since options A, B, and C are all valid supervised learning algorithms, none of them is the correct example of a model that is NOT commonly supervised. Therefore, the correct answer is E. None of the above .
質問 # 38
Which one of the following should NOT be used while designing the prompt?
正解：E
解説：
The correct answer is E. All of the above because effective prompt design requires clarity, focus, structure, and useful constraints. Information overload should not be used because giving too much unnecessary detail can confuse the model, weaken the main instruction, and reduce the quality of the response. A prompt should include relevant context, but it should avoid excessive or unrelated information.
Open-ended questions should also be avoided when the goal is a specific, controlled, or business-ready answer. Broad prompts often produce vague, incomplete, or inconsistent outputs. Instead, prompts should clearly state the desired task, format, scope, and expected outcome. Lack of constraints is also a poor prompt design practice because constraints guide the model on length, tone, structure, audience, output type, and boundaries. Without constraints, the model may generate responses that are too broad, too long, or misaligned with the user's intent.
Since information overload, overly open-ended questions, and lack of constraints can all weaken prompt quality, the correct answer is E. All of the above .
質問 # 39
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