便利なCAIC最新問題一回合格-権威のあるCAIC試験復習
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Certified Artificial Intelligence Consultantテストの準備は、主に当社のクライアントは、CAIC試験に合格するのを助けると認証を得ることができます。この認証は、クライアントに大きなメリットをもたらします。クライアントは大企業に参入し、高給を稼ぐことができます。 CAIC試験に合格すると、給与を2倍にすることができます。認定資格を所有している場合、CAICクイズトレントを十分にマスターし、優れた能力を所有していることを証明し、会社または工場で尊敬されます。あなたの仕事を変えたいなら、それはあなたにとっても良いことです。
USAII CAIC 認定試験の出題範囲:
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CAIC試験復習、CAIC一発合格
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USAII Certified Artificial Intelligence Consultant 認定 CAIC 試験問題 (Q16-Q21):
質問 # 16
Choose the CORRECT example of Supervised Learning.
- A. None of the above
- B. ChatGPT
- C. Driverless car
- D. House price prediction
- E. All of the above
正解:D
解説:
The correct answer is B. House price prediction . Supervised learning is a machine learning approach where a model is trained using labeled data. In a house price prediction problem, the training data usually contains property features such as size, location, number of rooms, age of the house, and past selling prices. The known selling price acts as the label or target value. The model learns the relationship between the input features and the price, then predicts prices for new houses.
A driverless car is not the best single example because autonomous driving uses a combination of AI techniques, including supervised learning, reinforcement learning, computer vision, sensor fusion, planning, and control systems. ChatGPT is a generative AI language model and is not typically used as the basic example of supervised learning in this context. Since house price prediction directly represents supervised learning with labeled input-output data, the correct answer is B .
質問 # 17
Which of the following is the CORRECT key areas as ethical principles?
- A. a, b and c only
- B. Prevention of harm
- C. Explicability
- D. Respect for human autonomy
- E. a and c only
正解:A
解説:
The correct answer is E. a, b and c only because respect for human autonomy, prevention of harm, and explicability are all recognized ethical principles in responsible AI. Respect for human autonomy means AI systems should support human decision-making rather than unfairly manipulate, replace, or override people in ways that remove meaningful human control. This is especially important in business, healthcare, finance, hiring, and other high-impact AI use cases.
Prevention of harm is also a core ethical principle because AI systems should be designed and deployed to reduce physical, psychological, financial, social, operational, and reputational risks. Organizations must consider safety, reliability, misuse prevention, bias reduction, and risk controls.
Explicability is correct because AI decisions should be understandable, explainable, and auditable where appropriate. Stakeholders should be able to understand how and why an AI system produces important outputs. Since all three listed items are valid ethical principles, the correct answer is E. a, b and c only .
質問 # 18
Choose the CORRECT statement for SOFT Launch.
- A. A soft launch is to select a group of people who have been handpicked by the company.
- B. a, b and c only
- C. The goal of a soft launch is to gauge customer reactions and measure customer acquisition costs CACs.
- D. a and b only
- E. A soft launch is a controlled and limited release of your new product or service.
正解:B
解説:
The correct answer is E. a, b and c only because all three statements correctly describe a soft launch. A soft launch is a limited and controlled release of a new product, service, platform, or feature before a full public launch. Organizations use it to test the product in a real or semi-real market environment while reducing risk and maintaining control over the launch process.
Statement A is correct because a soft launch is not a large-scale public release; it is usually restricted to a smaller audience, region, user group, or market segment. Statement B is also correct because companies may handpick early users, beta testers, internal customers, loyal customers, or selected market participants to try the product first. Statement C is correct because a soft launch helps the company observe customer reactions, collect feedback, identify defects, test adoption, validate messaging, and estimate customer acquisition costs.
Since A, B, and C are all accurate, the best answer is E. a, b and c only .
質問 # 19
Which of the following is a common supervised learning model/algorithm?
- A. Linear regression models
- B. None of the above
- C. All of the above
- D. Naive Bayes classifier
- E. Support vector machine SVM
正解:C
解説:
The correct answer is D. All of the above because Naive Bayes classifier, Support Vector Machine, and linear regression are all commonly used supervised learning algorithms. Supervised learning uses labeled training data, where the model learns the relationship between input features and known output labels or target values.
Naive Bayes is a supervised classification algorithm commonly used for text classification, spam detection, sentiment analysis, and document categorization. Support Vector Machine is also a supervised learning algorithm used for classification and regression tasks by finding an optimal boundary or hyperplane between classes. Linear regression is a supervised learning model used for predicting continuous numeric values, such as sales, prices, demand, or costs, based on input variables.
Since all three listed options are valid examples of supervised learning models or algorithms, the most complete and correct answer is D. All of the above .
質問 # 20
Which of the following statement is CORRECT for RNN?
- A. a, b and c only
- B. One prominent drawback of RNNs is that they cannot remember more than a few time steps.
- C. Long Short-Term Memory LSTM networks are an extension of RNNs that encapsulate long-term memory.
- D. RNN lacks long-term memory.
- E. a and b only
正解:A
解説:
The correct answer is E. a, b and c only because all three statements correctly describe Recurrent Neural Networks and their limitation. RNNs are neural network models designed for sequential data such as text, speech, time-series data, and ordered events. They process information step by step and use previous hidden states to influence later outputs.
Statement A is correct because a major drawback of traditional RNNs is their difficulty in remembering information over many time steps. This happens mainly because of vanishing gradient problems during training. Statement B is also correct because standard RNNs generally struggle with long-term dependencies, meaning they may fail to retain important information from earlier parts of a sequence. Statement C is correct because Long Short-Term Memory networks are a specialized extension of RNNs designed to handle long- term memory more effectively using gates that control what information is stored, forgotten, and passed forward.
Therefore, the best answer is E. a, b and c only .
質問 # 21
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