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| Certification Vendor: | USAII |
|---|---|
| Exam Name: | Certified Artificial Intelligence Consultant |
| Exam Number: | CAIC |
| Exam Format: | Multiple Choice, Multiple Response |
| Related Certifications: | CAIC™ |
| Passing Score: | 70% |
| Exam Duration: | 100 minutes |
| Certificate Validity Period: | Lifetime |
| Real Exam Qty: | 35 |
| Available Languages: | English |
| Exam Price: | USD 894 |
| Sample Questions: | USAII CAIC Sample Questions |
| Exam Way: | Online |
| Pre Condition: | Programming skills are not mandatory to apply for CAIC™ certification. |
| Official Syllabus URL: | https://www.usaii.org/artificial-intelligence-certifications/caic |
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問題 #72
What is a prompt?
答案：C
解題說明：
The correct answer is D. a and b only because a prompt is the input provided by a user to a generative AI model. In natural language systems such as ChatGPT and other language models, the prompt is usually written as text in natural language. It may be a question, instruction, command, description, context, example, or task requirement that guides the model toward producing a response.
Statement A is correct because prompts are the user-provided input that generative models use to produce outputs. Statement B is also correct because, for ChatGPT and similar models, prompts commonly appear as natural language text. Statement C is not fully correct because prompts are an important way to guide model output, but they are not the only possible control mechanism. Outputs can also be influenced by system instructions, model settings, retrieval context, fine-tuning, guardrails, and application design. Therefore, the best answer is D. a and b only .
問題 #73
A model is trained using historical customer records where each record already contains the correct outcome, such as "churn" or "not churn." The model then predicts whether future customers are likely to churn. This is an example of ______.
答案：C
解題說明：
Supervised learning is used when a machine learning model is trained on labeled data. In this case, the historical customer records already include the correct outcome labels, such as "churn" or "not churn." The model learns the relationship between customer attributes and the known outcome, then applies that learned relationship to predict outcomes for new customers. This is a classic classification problem. Unsupervised learning is incorrect because it works with unlabeled data and is commonly used for clustering or discovering hidden patterns. Reinforcement learning is incorrect because there is no reward-based decision-making environment described. Generative learning is not the best answer because the task is prediction, not creating new content. Therefore, the correct answer is A. supervised learning .
問題 #74
Which of the following is a common supervised learning model/algorithm?
答案：E
解題說明：
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 .
問題 #75
What type of AI system does not have self-awareness or consciousness?
答案：B
解題說明：
The correct answer is C. Narrow AI . Narrow AI, also called Weak AI, is designed to perform specific tasks within a limited domain. Examples include recommendation systems, chatbots, image recognition tools, fraud detection systems, voice assistants, and predictive analytics models. These systems can appear intelligent because they process data, detect patterns, make predictions, or generate responses, but they do not possess self-awareness, consciousness, emotions, independent understanding, or human-like general reasoning.
General AI and Strong AI refer to the idea of an AI system that could reason, learn, and adapt across many different tasks in a human-like way. These terms are associated with broader intelligence rather than task- specific automation. Human AI is not a standard AI category in this context. Since the question asks for the type of AI that does not have self-awareness or consciousness and operates only within defined limits, the correct choice is C. Narrow AI .
問題 #76
Select the MOST CORRECT statement for Few-shot learning.
答案：B
解題說明：
The correct answer is E. b and c only because few-shot learning means a model learns or adapts to a new task using only a small number of examples. In generative AI and large language model usage, few-shot prompting often provides a few demonstrations so the model can understand the expected pattern, format, classification logic, or response style. Option B is correct because few-shot learning uses a limited number of examples rather than a large training dataset.
Option C is also correct because few-shot learning depends on the model's prior knowledge learned during pretraining. The model uses that existing knowledge to generalize from the small set of examples and apply the same logic to new inputs. Option A is not the best statement because "a large number of examples" does not match the idea of few-shot learning. Therefore, the most correct answer is E. b and c only .
問題 #77
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