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AI1-C01 actual exam dumps, Amazon AI1-C01 practice test
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The Amazon AI1-C01 certification exam is an industrial-recognized AWS Certified AI Practitioner Exam (AI1-C01) certificate that is designed to validate candidates' skills, experience, and knowledge quickly. The AWS Certified AI Practitioner Exam (AI1-C01) certification exam has been inspiring Amazon professionals since its beginning. Now this AI1-C01 certification exam has become solid proof of certain skills set and knowledge.
Amazon AWS Certified AI Practitioner Exam Sample Questions (Q60-Q65):
NEW QUESTION # 60
An education provider is building a question and answer application that uses a generative AI model to explain complex concepts. The education provider wants to automatically change the style of the model response depending on who is asking the question. The education provider will give the model the age range of the user who has asked the question.
Which solution meets these requirements with the LEAST implementation effort?
- A. Add a role description to the prompt context that instructs the model of the age range that the response should target.
- B. Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user.
- C. Summarize the response text depending on the age of the user so that younger users receive shorter responses.
- D. Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support.
Answer: A
NEW QUESTION # 61
A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model.
The company needs to perform analysis on internal data and external data.
Which solution will meet these requirements?
- A. Import the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.
- B. Import the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.
- C. Import the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.
- D. Store the data in Amazon S3. Create ML models and demand forecast predictions by using Amazon SageMaker built-in algorithms that use the data from Amazon S3.
Answer: A
Explanation:
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NEW QUESTION # 62
An AI practitioner is using an Amazon Bedrock base model to summarize session chats from the customer service department. The AI practitioner wants to store invocation logs to monitor model input and output data.
Which strategy should the AI practitioner use?
- A. Enable invocation logging in Amazon Bedrock.
- B. Configure model invocation logging in Amazon EventBridge.
- C. Configure AWS CloudTrail as the logs destination for the model.
- D. Configure AWS Audit Manager as the logs destination for the model.
Answer: A
NEW QUESTION # 63
A company has installed a security camera. The company uses an ML model to evaluate the security camera footage for potential thefts. The company has discovered that the model disproportionately flags people who are members of a specific ethnic group.
Which type of bias is affecting the model output?
- A. Measurement bias
- B. Sampling bias
- C. Confirmation bias
- D. Observer bias
Answer: B
NEW QUESTION # 64
A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.
Which business objective should the company use to evaluate the effect of the LLM chatbot?
- A. Corporate social responsibility
- B. Average call duration
- C. Regulatory compliance
- D. Website engagement rate
Answer: B
NEW QUESTION # 65
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