Free Amazon AIF-C01 Exam Questions
Absolute Free AIF-C01 Exam Practice for Comprehensive Preparation
-
Amazon AIF-C01 Exam Questions
-
Provided By: Amazon
- Exam: AWS Certified AI Practitioner
- Certification: AWS Certified Foundational
-
Total Questions: 460
-
Updated On: Jan 21, 2025
-
Rated: 4.9 |
-
Online Users: 920
-
Question 1
-
Which of the following aptly summarizes the capabilities of Foundation Models?
Answer: D
-
Which of the following aptly summarizes the capabilities of Foundation Models?
-
Question 2
-
A company is using Amazon Bedrock and it wants to set an upper limit on the number of tokens returned in the model's response.Which of the following inference parameters would you recommend for the given use case?
Answer: A
-
A company is using Amazon Bedrock and it wants to set an upper limit on the number of tokens returned in the model's response.Which of the following inference parameters would you recommend for the given use case?
-
Question 3
-
Consider a scenario where a fully-managed AWS service needs to be used for automating the extraction of insights from legal briefs such as contracts and court records.What do you recommend?
Answer: B
-
Consider a scenario where a fully-managed AWS service needs to be used for automating the extraction of insights from legal briefs such as contracts and court records.What do you recommend?
-
Question 4
-
A security company is evaluating Amazon Rekognition to enhance its Machine Learning (ML) capabilities. However, the data science team needs to identify scenarios where Amazon Rekognition may not be the most suitable solution. Understanding these limitations will help the team select the right tools for different aspects of their security system.Given this context, which of the following use cases is NOT the right fit for Amazon Rekognition?
Answer: B
-
A security company is evaluating Amazon Rekognition to enhance its Machine Learning (ML) capabilities. However, the data science team needs to identify scenarios where Amazon Rekognition may not be the most suitable solution. Understanding these limitations will help the team select the right tools for different aspects of their security system.Given this context, which of the following use cases is NOT the right fit for Amazon Rekognition?
-
Question 5
-
A machine learning team at a tech company is developing a generative AI model to automate text generation for customer support. As part of optimizing the model’s performance, the team needs to adjust both model parameters and hyperparameters but wants to clearly understand the distinctions between the two. Understanding these differences is crucial for fine-tuning the model and improving its output.Which of the following highlights the key differences between model parameters and hyperparameters in the context of generative AI?
Answer: C
-
A machine learning team at a tech company is developing a generative AI model to automate text generation for customer support. As part of optimizing the model’s performance, the team needs to adjust both model parameters and hyperparameters but wants to clearly understand the distinctions between the two. Understanding these differences is crucial for fine-tuning the model and improving its output.Which of the following highlights the key differences between model parameters and hyperparameters in the context of generative AI?