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| Certification Vendor: | USAII (United States Artificial Intelligence Institute) |
|---|---|
| Exam Name: | Certified Artificial Intelligence Consultant |
| Exam Number: | CAIC |
| Exam Format: | Multiple-choice, Single or multiple correct answers, Computer-based |
| Passing Score: | 70% |
| Exam Price: | US $894 |
| Related Certifications: | CAIS™ (Certified Artificial Intelligence Specialist) CAIE™ (Certified Artificial Intelligence Engineer) |
| Real Exam Qty: | 70 |
| Exam Duration: | 100 minutes |
| Available Languages: | English |
| Certificate Validity Period: | 3 years |
| Recommended Training: | Official CAIC Learning Material |
| Exam Registration: | USAII Official Registration |
| Sample Questions: | USAII CAIC Sample Questions |
| Exam Way: | Online remote proctored or onsite computer-based exam |
| Pre Condition: | 4 eligibility paths: 1) Associate/Diploma + 6 years programming experience; 2) Bachelor's + 2 years relevant experience; 3) Master's (current/completed) + basic proficiency preferred; 4) CAIE certification + 1–4 years experience (depending on degree) |
| Official Syllabus URL: | https://www.usaii.org/artificial-intelligence-certifications/certified-artificial-intelligence-consultant |
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問題 #32
A healthcare organization has a small number of labeled medical images and a much larger number of unlabeled images. The AI model uses both datasets to improve disease classification accuracy. This is an example of ______.
答案：A
解題說明：
Semi-supervised learning is the correct answer because the model is trained using a combination of labeled and unlabeled data. This approach is useful when labeled data is expensive, time-consuming, or difficult to obtain, which is common in healthcare because medical images often require expert annotation. The small labeled dataset provides guidance, while the larger unlabeled dataset helps the model learn broader patterns and improve classification performance. Supervised learning is not the best answer because the scenario does not rely only on labeled data. Unsupervised learning is incorrect because the goal is disease classification, and some labeled examples are available. Reinforcement learning is incorrect because there are no rewards, actions, or environment-based feedback. Rule-based learning is also incorrect because the model is learning from data, not from manually coded rules. Therefore, the correct answer is D. semi-supervised learning .
問題 #33
Which of the following is the CORRECT basic brain components?
答案：D
解題說明：
The correct answer is E. All of the above because the listed terms are associated with major functional or structural areas of the human brain often discussed when explaining cognition, intelligence, decision-making, emotions, perception, and behavior. The neocortex is linked with higher-order thinking, reasoning, language, planning, perception, and conscious decision-making. The limbic system is strongly associated with emotion, memory, motivation, and behavioral responses. The midbrain is involved in sensory processing, movement control, visual and auditory responses, and alertness. The brainstem supports essential automatic functions such as breathing, heart rate, sleep-wake regulation, and basic survival processes.
In artificial intelligence learning, these brain components are often introduced to help explain how human intelligence works and how AI attempts to model certain cognitive functions. Since neocortex, limbic, midbrain, and brainstem are all valid basic brain-related components, the best answer is E. All of the above .
問題 #34
Select the most CORRECT risk-scoring methodology function statement for prospective risk.
答案：E
解題說明：
The correct answer is C because prospective risk is forward-looking. It focuses on estimating future model risk by using the most current risk condition, present indicators, and existing risk posture of the model. In AI governance and model risk management, prospective risk assessment helps organizations anticipate possible future issues such as performance degradation, bias, drift, compliance exposure, operational failure, or business impact before those risks become actual problems.
Option A is not the most correct because analyzing historical model performance is more closely linked with retrospective risk assessment. Historical performance can support risk analysis, but it does not fully define prospective risk. Option B is not accurate because "upcoming model performance" is not directly available for analysis; future performance must be predicted, not already analyzed. Option E is incorrect because A and B are not both accurate statements. Therefore, the most correct statement is C. Prospective risk leverages the most current risk of the model to predict the overall model risk for future cycles .
問題 #35
Choose the INCORRECT statement for Industry Architect.
答案：D
解題說明：
The incorrect statement is B because it describes DevOps, not an Industry Architect. A collaborative approach that bridges development and operations teams is the core idea of DevOps, where software development, IT operations, automation, continuous integration, continuous deployment, monitoring, and delivery practices are aligned to improve speed and reliability.
An Industry Architect, on the other hand, focuses on designing technology and business solutions for a specific industry or vertical, such as healthcare, finance, retail, manufacturing, or telecommunications. This role requires strong domain knowledge, awareness of industry regulations, understanding of business processes, and the ability to translate industry-specific requirements into practical technical solutions. Industry Architects work with executives, subject matter experts, business teams, and technology teams to ensure that solutions meet business goals and industry expectations. Therefore, options A, C, D, and E correctly describe the Industry Architect role, while B is the incorrect statement.
問題 #36
Which type of AI mimics the human brain by building networks of artificial neurons?
答案：D
解題說明：
The correct answer is C. Neural Networks . Neural networks are AI and machine learning models inspired by the structure and function of the human brain. They are built using interconnected artificial neurons, also called nodes, which process input data, apply weights and activation functions, and pass information through layers to produc e an output. This structure allows neural networks to learn complex patterns from data.
Fuzzy logic is incorrect because it deals with reasoning under uncertainty using degrees of truth rather than artificial neurons. Genetic algorithms are optimization methods inspired by natural selection and evolution, not the brain's neuron-based structure. Expert systems use rules and knowledge bases to make decisions, but they do not mimic the brain through networks of artificial neurons. Since the question specifically asks about AI that mimics the human brain by building artificial neuron networks, the correct answer is C. Neural Networks .
問題 #37
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