Free Amazon AIF-C01 Exam Questions

Become Amazon Certified with updated AIF-C01 exam questions and correct answers

Page: 1 / 148

Total 737 Questions | Updated On: May 12, 2026

Add To Cart

Question 1

Which option is a characteristic of AI governance frameworks for building trust and deploying humancentered AI technologies?

A : Expanding initiatives across business units to create long-term business value

B : Ensuring alignment with business standards, revenue goals, and stakeholder expectations

C : Overcoming challenges to drive business transformation and growth

D : Developing policies and guidelines for data, transparency, responsible AI, and compliance\

Answer: D

Question 2

Which of the following aptly summarizes the capabilities of Foundation Models?

A : Foundation models are limited to simple data processing tasks and cannot handle complex operations

B : Foundation models are designed to work exclusively with structured data and cannot process unstructured data like text or images

C : Foundation models can only perform a single task they were specifically trained for

D : Foundation models can perform a wide range of tasks across different domains by leveraging their extensive pre-training on large datasets

Answer: D

Question 3

A company uses a generative model to analyze animal images in the training dataset to record variables like different ear shapes, eye shapes, tail features, and skin patterns.Which of the following tasks can the generative model perform?

A : The model can classify multiple species of animals such as cats, dogs, etc

B : The model can identify any image from the training dataset

C : The model can recreate new animal images that were not in the training dataset

D : The model can classify a single species of animals such as cats

Answer: C

Question 4

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?

A : Hyperparameters are values that define a model and its behavior in interpreting input and generating responses. Model parameters are values that can be adjusted for model customization to control the training process

B : Both Hyperparameters and model parameters are values that define a model and its behavior in interpreting input and generating responses

C : Model parameters are values that define a model and its behavior in interpreting input and generating responses. Hyperparameters are values that can be adjusted for model customization to control the training process

D : Both Hyperparameters and model parameters are values that can be adjusted for model customization to control the training process

Answer: C

Question 5

How does the inference parameter Top P influence the model response for Amazon Bedrock?

A : Influences the likelihood of the model selecting lower-probability outputs, thereby impacting the creativity of the model’s output

B : Influences the number of most-likely candidates that the model considers for the next token

C : Specifies the sequences of characters that stop the model from generating further tokens

D : Influences the percentage of most-likely candidates that the model considers for the next token

Answer: D

Page: 1 / 148

Total 737 Questions | Updated On: May 12, 2026

Add To Cart