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| Certification Vendor: | USAII |
|---|---|
| Exam Name: | Certified Artificial Intelligence Consultant |
| Exam Number: | CAIC |
| Passing Score: | 70% |
| Exam Price: | USD 894 |
| Certificate Validity Period: | Lifetime |
| Real Exam Qty: | 35 |
| Exam Format: | Multiple Response, Multiple Choice |
| Related Certifications: | CAIC™ |
| Exam Duration: | 100 minutes |
| Available Languages: | English |
| 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 |
>> New CAIC Braindumps Sheet <<
In the information era, IT industry is catching more and more attention. In the society which has a galaxy of talents, there is still lack of IT talents. Many companies need IT talents, and generally, they investigate IT talents's ability in according to what IT related authentication certificate they have. So having some IT related authentication certificate is welcomed by many companies. But these authentication certificate are not very easy to get. USAII CAIC is a quite difficult certification exams. Although a lot of people participate in USAII CAIC exam, the pass rate is not very high.
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NEW QUESTION # 26
Which of the following is a CORRECT statement for Few-shot learning?
Answer: C
Explanation:
The correct answer is D. a and b only because few-shot learning is a machine learning technique that allows a model to learn or adapt to a new task using only a small number of labeled examples. It is especially useful when collecting large labeled datasets is expensive, slow, or difficult. Instead of requiring thousands or millions of labeled records, few-shot learning depends on prior knowledge learned by the model and applies that knowledge to new examples with limited supervision.
Statement A is correct because few-shot learning is recognized as a machine learning approach. Statement B is also correct because the core idea of few-shot learning is learning from very limited labeled data. Statement C is not correct because learning from unlabeled data is more closely associated with unsupervised learning or semi-supervised learning, not the standard definition of few-shot learning. Therefore, the correct answer is D.
a and b only .
NEW QUESTION # 27
Which of the following is a CORRECT statement for DevOps architect?
Answer: D
Explanation:
The correct answer is D. a and b only because statements A and B correctly describe DevOps and the role of a DevOps architect. DevOps is a collaborative approach that connects software development and IT operations so teams can build, test, deploy, monitor, and improve systems more efficiently. It emphasizes automation, communication, continuous delivery, monitoring, reliability, and faster release cycles.
Statement B is also correct because a DevOps architect is responsible for designing and optimizing CI/CD pipelines. These pipelines support continuous integration, automated testing, continuous deployment, infrastructure automation, and reliable software delivery. A DevOps architect may also consider monitoring, security, scalability, performance, and disaster recovery.
Statement C is incorrect because it describes the goal of advanced AI or artificial general intelligence, not DevOps. DevOps does not focus on creating human-like intelligent systems across multiple domains.
Therefore, the best answer is D. a and b only .
NEW QUESTION # 28
An AI agent learns to play a game by taking actions, receiving rewards for good moves, and penalties for poor moves. Over time, it improves its strategy to maximize total reward. This is an example of ______.
Answer: E
Explanation:
Reinforcement learning is the correct answer because the AI agent learns by interacting with an environment and improving its behavior based on rewards and penalties. The goal of reinforcement learning is to learn a policy or strategy that maximizes cumulative reward over time. This differs from supervised learning, where the model learns from labeled input-output examples. It also differs from unsupervised learning, where the model searches for hidden patterns without labels or rewards. Semi-supervised learning is incorrect because the scenario does not involve a mix of labeled and unlabeled data. Regression learning is also incorrect because regression predicts continuous numerical values, while this example focuses on action selection and reward optimization. Therefore, the correct answer is C. reinforcement learning .
NEW QUESTION # 29
Why is prompt important?
Answer: E
Explanation:
The correct answer is E. a, b and c only because all three statements explain why prompt design is important when working with generative AI and language models. A prompt is the instruction, question, or context given to an AI system to guide its response. When the prompt is clear, specific, and well-structured, the model is more likely to produce useful, relevant, and accurate output. This supports statement A because well- defined prompts help create a successful and productive conversation.
Statement B is also correct because poorly-defined prompts can make the conversation less useful. If the prompt is vague, incomplete, or confusing, the model may produce broad, irrelevant, or low-quality responses. Statement C is correct because unclear prompts can also lead to misleading content, especially when the model fills in missing details or interprets the request incorrectly. Therefore, prompt quality directly affects response quality, usefulness, and reliability, making E the best answer.
NEW QUESTION # 30
Which of the following is NOT a CORRECT element of the Planning and execution phase in the risk framework?
Answer: D
Explanation:
The correct answer is D. Ethics because ethics is not best treated as a single operational element of the planning and execution phase. In an AI risk framework, the planning and execution phase usually focuses on practical implementation activities such as defining the AI use case, aligning the solution with strategy, assessing financial feasibility, designing the product or solution, and preparing it for release. These activities help convert an AI concept into a working business or technical solution.
Conceptualization of the AI use case is correct because every AI initiative must begin with a clearly defined problem, objective, and intended business value. Strategy is also correct because the AI solution must align with organizational goals and risk appetite. Finance is relevant because organizations must consider cost, investment, expected return, and resource allocation. Design and release of the final product or solution is also part of execution.
Ethics is important across the entire AI lifecycle, but it is not the specific planning and execution element listed here. Therefore, the best answer is D. Ethics .
NEW QUESTION # 31
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