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Amazon Web Services AIF-C01 Dumps

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Total 177 questions

AWS Certified AI Practitioner Exam Questions and Answers

Question 1

A company wants to use a pre-trained generative AI model to generate content for its marketing campaigns. The company needs to ensure that the generated content aligns with the company's brand voice and messaging requirements.

Which solution meets these requirements?

Options:

A.

Optimize the model's architecture and hyperparameters to improve the model's overall performance.

B.

Increase the model's complexity by adding more layers to the model's architecture.

C.

Create effective prompts that provide clear instructions and context to guide the model's generation.

D.

Select a large, diverse dataset to pre-train a new generative model.

Question 2

A bank has fine-tuned a large language model (LLM) to expedite the loan approval process. During an external audit of the model, the company discovered that the model was approving loans at a faster pace for a specific demographic than for other demographics.

How should the bank fix this issue MOST cost-effectively?

Options:

A.

Include more diverse training data. Fine-tune the model again by using the new data.

B.

Use Retrieval Augmented Generation (RAG) with the fine-tuned model.

C.

Use AWS Trusted Advisor checks to eliminate bias.

D.

Pre-train a new LLM with more diverse training data.

Question 3

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?

Options:

A.

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.

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.

Import the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.

Question 4

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

Options:

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\

Question 5

A company wants to build and deploy ML models on AWS without writing any code.

Which AWS service or feature meets these requirements?

Options:

A.

Amazon SageMaker Canvas

B.

Amazon Rekognition

C.

AWS DeepRacer

D.

Amazon Comprehend

Question 6

A student at a university is copying content from generative AI to write essays.

Which challenge of responsible generative AI does this scenario represent?

Options:

A.

Toxicity

B.

Hallucinations

C.

Plagiarism

D.

Privacy

Question 7

A company wants to use generative AI to increase developer productivity and software development. The company wants to use Amazon Q Developer.

What can Amazon Q Developer do to help the company meet these requirements?

Options:

A.

Create software snippets, reference tracking, and open-source license tracking.

B.

Run an application without provisioning or managing servers.

C.

Enable voice commands for coding and providing natural language search.

D.

Convert audio files to text documents by using ML models.

Question 8

A company needs to log all requests made to its Amazon Bedrock API. The company must retain the logs securely for 5 years at the lowest possible cost.

Which combination of AWS service and storage class meets these requirements? (Select TWO.)

Options:

A.

AWS CloudTrail

B.

Amazon CloudWatch

C.

AWS Audit Manager

D.

Amazon S3 Intelligent-Tiering

E.

Amazon S3 Standard

Question 9

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?

Options:

A.

Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support.

B.

Add a role description to the prompt context that instructs the model of the age range that the response should target.

C.

Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user.

D.

Summarize the response text depending on the age of the user so that younger users receive shorter responses.

Question 10

A company wants to create a chatbot by using a foundation model (FM) on Amazon Bedrock. The FM needs to access encrypted data that is stored in an Amazon S3 bucket.

The data is encrypted with Amazon S3 managed keys (SSE-S3).

The FM encounters a failure when attempting to access the S3 bucket data.

Which solution will meet these requirements?

Options:

A.

Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key.

B.

Set the access permissions for the S3 buckets to allow public access to enable access over the internet.

C.

Use prompt engineering techniques to tell the model to look for information in Amazon S3.

D.

Ensure that the S3 data does not contain sensitive information.

Question 11

A company wants to identify harmful language in the comments section of social media posts by using an ML model. The company will not use labeled data to train the model. Which strategy should the company use to identify harmful language?

Options:

A.

Use Amazon Rekognition moderation.

B.

Use Amazon Comprehend toxicity detection.

C.

Use Amazon SageMaker AI built-in algorithms to train the model.

D.

Use Amazon Polly to monitor comments.

Question 12

Which component of Amazon Bedrock Studio can help secure the content that AI systems generate?

Options:

A.

Access controls

B.

Function calling

C.

Guardrails

D.

Knowledge bases

Question 13

A food service company wants to develop an ML model to help decrease daily food waste and increase sales revenue. The company needs to continuously improve the model's accuracy.

Which solution meets these requirements?

Options:

A.

Use Amazon SageMaker AI and iterate with the most recent data.

B.

Use Amazon Personalize and iterate with historical data.

C.

Use Amazon CloudWatch to analyze customer orders.

D.

Use Amazon Rekognition to optimize the model.

Question 14

A company has terabytes of data in a database that the company can use for business analysis. The company wants to build an AI-based application that can build a SQL query from input text that employees provide. The employees have minimal experience with technology.

Which solution meets these requirements?

Options:

A.

Generative pre-trained transformers (GPT)

B.

Residual neural network

C.

Support vector machine

D.

WaveNet

Question 15

A company's large language model (LLM) is experiencing hallucinations.

How can the company decrease hallucinations?

Options:

A.

Set up Agents for Amazon Bedrock to supervise the model training.

B.

Use data pre-processing and remove any data that causes hallucinations.

C.

Decrease the temperature inference parameter for the model.

D.

Use a foundation model (FM) that is trained to not hallucinate.

Question 16

A financial company is developing a fraud detection system that flags potential fraud cases in credit card transactions. Employees will evaluate the flagged fraud cases. The company wants to minimize the amount of time the employees spend reviewing flagged fraud cases that are not actually fraudulent.

Which evaluation metric meets these requirements?

Options:

A.

Recall

B.

Accuracy

C.

Precision

D.

Lift chart

Question 17

A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality.

Which action must the company take to use the custom model through Amazon Bedrock?

Options:

A.

Purchase Provisioned Throughput for the custom model.

B.

Deploy the custom model in an Amazon SageMaker endpoint for real-time inference.

C.

Register the model with the Amazon SageMaker Model Registry.

D.

Grant access to the custom model in Amazon Bedrock.

Question 18

A company wants to create a new solution by using AWS Glue. The company has minimal programming experience with AWS Glue.

Which AWS service can help the company use AWS Glue?

Options:

A.

Amazon Q Developer

B.

AWS Config

C.

Amazon Personalize

D.

Amazon Comprehend

Question 19

A company is using Amazon SageMaker Studio notebooks to build and train ML models. The company stores the data in an Amazon S3 bucket. The company needs to manage the flow of data from Amazon S3 to SageMaker Studio notebooks.

Which solution will meet this requirement?

Options:

A.

Use Amazon Inspector to monitor SageMaker Studio.

B.

Use Amazon Macie to monitor SageMaker Studio.

C.

Configure SageMaker to use a VPC with an S3 endpoint.

D.

Configure SageMaker to use S3 Glacier Deep Archive.

Question 20

A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly.

Which evaluation metric should the company use to measure the model's performance?

Options:

A.

R-squared score

B.

Accuracy

C.

Root mean squared error (RMSE)

D.

Learning rate

Question 21

A retail company wants to build an ML model to recommend products to customers. The company wants to build the model based on responsible practices. Which practice should the company apply when collecting data to decrease model bias?

Options:

A.

Use data from only customers who match the demography of the company's overall customer base.

B.

Collect data from customers who have a past purchase history.

C.

Ensure that the data is balanced and collected from a diverse group.

D.

Ensure that the data is from a publicly available dataset.

Question 22

A security company is using Amazon Bedrock to run foundation models (FMs). The company wants to ensure that only authorized users invoke the models. The company needs to identify any unauthorized access attempts to set appropriate AWS Identity and Access Management (IAM) policies and roles for future iterations of the FMs.

Which AWS service should the company use to identify unauthorized users that are trying to access Amazon Bedrock?

Options:

A.

AWS Audit Manager

B.

AWS CloudTrail

C.

Amazon Fraud Detector

D.

AWS Trusted Advisor

Question 23

An AI practitioner is using a large language model (LLM) to create content for marketing campaigns. The generated content sounds plausible and factual but is incorrect.

Which problem is the LLM having?

Options:

A.

Data leakage

B.

Hallucination

C.

Overfitting

D.

Underfitting

Question 24

A large retail bank wants to develop an ML system to help the risk management team decide on loan allocations for different demographics.

What must the bank do to develop an unbiased ML model?

Options:

A.

Reduce the size of the training dataset.

B.

Ensure that the ML model predictions are consistent with historical results.

C.

Create a different ML model for each demographic group.

D.

Measure class imbalance on the training dataset. Adapt the training process accordingly.

Question 25

An AI practitioner has built a deep learning model to classify the types of materials in images. The AI practitioner now wants to measure the model performance.

Which metric will help the AI practitioner evaluate the performance of the model?

Options:

A.

Confusion matrix

B.

Correlation matrix

C.

R2 score

D.

Mean squared error (MSE)

Question 26

A company wants to create an application to summarize meetings by using meeting audio recordings.

Select and order the correct steps from the following list to create the application. Each step should be selected one time or not at all. (Select and order THREE.)

• Convert meeting audio recordings to meeting text files by using Amazon Polly.

• Convert meeting audio recordings to meeting text files by using Amazon Transcribe.

• Store meeting audio recordings in an Amazon S3 bucket.

• Store meeting audio recordings in an Amazon Elastic Block Store (Amazon EBS) volume.

• Summarize meeting text files by using Amazon Bedrock.

• Summarize meeting text files by using Amazon Lex.

as

Options:

Question 27

A hospital developed an AI system to provide personalized treatment recommendations for patients. The AI system must provide the rationale behind the recommendations and make the insights accessible to doctors and patients.

Which human-centered design principle does this scenario present?

Options:

A.

Explainability

B.

Privacy and security

C.

Fairness

D.

Data governance

Question 28

A company wants to fine-tune an ML model that is hosted on Amazon Bedrock. The company wants to use its own sensitive data that is stored in private databases in a VPC. The data needs to stay within the company's private network.

Which solution will meet these requirements?

Options:

A.

Restrict access to Amazon Bedrock by using an AWS Identity and Access Management (IAM) service role.

B.

Restrict access to Amazon Bedrock by using an AWS Identity and Access Management (IAM) resource policy.

C.

Use AWS PrivateLink to connect the VPC and Amazon Bedrock.

D.

Use AWS Key Management Service (AWS KMS) keys to encrypt the data.

Question 29

A company needs to use Amazon SageMaker AI for model training and inference. The company must comply with regulatory requirements to run SageMaker jobs in an isolated environment without internet access.

Which solution will meet these requirements?

Options:

A.

Run SageMaker training and inference by using SageMaker Experiments.

B.

Run SageMaker training and inference by using network isolation.

C.

Encrypt the data at rest by using encryption for SageMaker geospatial capabilities.

D.

Associate appropriate AWS Identity and Access Management (IAM) roles with the SageMaker jobs.

Question 30

A company has thousands of customer support interactions per day and wants to analyze these interactions to identify frequently asked questions and develop insights.

Which AWS service can the company use to meet this requirement?

Options:

A.

Amazon Lex

B.

Amazon Comprehend

C.

Amazon Transcribe

D.

Amazon Translate

Question 31

A company is using domain-specific models. The company wants to avoid creating new models from the beginning. The company instead wants to adapt pre-trained models to create models for new, related tasks.

Which ML strategy meets these requirements?

Options:

A.

Increase the number of epochs.

B.

Use transfer learning.

C.

Decrease the number of epochs.

D.

Use unsupervised learning.

Question 32

A company is developing an ML model to predict customer churn.

Which evaluation metric will assess the model's performance on a binary classification task such as predicting chum?

Options:

A.

F1 score

B.

Mean squared error (MSE)

C.

R-squared

D.

Time used to train the model

Question 33

A company wants to keep its foundation model (FM) relevant by using the most recent data. The company wants to implement a model training strategy that includes regular updates to the FM.

Which solution meets these requirements?

Options:

A.

Batch learning

B.

Continuous pre-training

C.

Static training

D.

Latent training

Question 34

A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model.

The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.

Which solution will meet these requirements?

Options:

A.

Use Amazon SageMaker Serverless Inference to deploy the model.

B.

Use Amazon CloudFront to deploy the model.

C.

Use Amazon API Gateway to host the model and serve predictions.

D.

Use AWS Batch to host the model and serve predictions.

Question 35

A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output.

Which ML algorithm meets these requirements?

Options:

A.

Decision trees

B.

Linear regression

C.

Logistic regression

D.

Neural networks

Question 36

HOTSPOT

A company is training its employees on how to structure prompts for foundation models.

Select the correct prompt engineering technique from the following list for each prompt template. Each prompt engineering technique should be selected onetime. (SelectTHREE.)

• Chain-of-thought reasoning

• Few-shot learning

• Zero-shot learning

as

Options:

Question 37

A company built a deep learning model for object detection and deployed the model to production.

Which AI process occurs when the model analyzes a new image to identify objects?

Options:

A.

Training

B.

Inference

C.

Model deployment

D.

Bias correction

Question 38

A company is using a generative AI model to develop a digital assistant. The model's responses occasionally include undesirable and potentially harmful content. Select the correct Amazon Bedrock filter policy from the following list for each mitigation action. Each filter policy should be selected one time. (Select FOUR.)

• Content filters

• Contextual grounding check

• Denied topics

• Word filters

as

Options:

Question 39

A social media company wants to use a large language model (LLM) to summarize messages. The company has chosen a few LLMs that are available on Amazon SageMaker JumpStart. The company wants to compare the generated output toxicity of these models.

Which strategy gives the company the ability to evaluate the LLMs with the LEAST operational overhead?

Options:

A.

Crowd-sourced evaluation

B.

Automatic model evaluation

C.

Model evaluation with human workers

D.

Reinforcement learning from human feedback (RLHF)

Question 40

A company wants to use large language models (LLMs) with Amazon Bedrock to develop a chat interface for the company's product manuals. The manuals are stored as PDF files.

Which solution meets these requirements MOST cost-effectively?

Options:

A.

Use prompt engineering to add one PDF file as context to the user prompt when the prompt is submitted to Amazon Bedrock.

B.

Use prompt engineering to add all the PDF files as context to the user prompt when the prompt is submitted to Amazon Bedrock.

C.

Use all the PDF documents to fine-tune a model with Amazon Bedrock. Use the fine-tuned model to process user prompts.

D.

Upload PDF documents to an Amazon Bedrock knowledge base. Use the knowledge base to provide context when users submit prompts to Amazon Bedrock.

Question 41

What are tokens in the context of generative AI models?

Options:

A.

Tokens are the basic units of input and output that a generative AI model operates on, representing words, subwords, or other linguistic units.

B.

Tokens are the mathematical representations of words or concepts used in generative AI models.

C.

Tokens are the pre-trained weights of a generative AI model that are fine-tuned for specific tasks.

D.

Tokens are the specific prompts or instructions given to a generative AI model to generate output.

Question 42

A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to know how much information can fit into one prompt.

Which consideration will inform the company's decision?

Options:

A.

Temperature

B.

Context window

C.

Batch size

D.

Model size

Question 43

A company trained an ML model on Amazon SageMaker to predict customer credit risk. The model shows 90% recall on training data and 40% recall on unseen testing data.

Which conclusion can the company draw from these results?

Options:

A.

The model is overfitting on the training data.

B.

The model is underfitting on the training data.

C.

The model has insufficient training data.

D.

The model has insufficient testing data.

Question 44

Which option describes embeddings in the context of AI?

Options:

A.

A method for compressing large datasets

B.

An encryption method for securing sensitive data

C.

A method for visualizing high-dimensional data

D.

A numerical method for data representation in a reduced dimensionality space

Question 45

Which AWS feature records details about ML instance data for governance and reporting?

Options:

A.

Amazon SageMaker Model Cards

B.

Amazon SageMaker Debugger

C.

Amazon SageMaker Model Monitor

D.

Amazon SageMaker JumpStart

Question 46

A medical company is customizing a foundation model (FM) for diagnostic purposes. The company needs the model to be transparent and explainable to meet regulatory requirements.

Which solution will meet these requirements?

Options:

A.

Configure the security and compliance by using Amazon Inspector.

B.

Generate simple metrics, reports, and examples by using Amazon SageMaker Clarify.

C.

Encrypt and secure training data by using Amazon Macie.

D.

Gather more data. Use Amazon Rekognition to add custom labels to the data.

Question 47

What does an F1 score measure in the context of foundation model (FM) performance?

Options:

A.

Model precision and recall

B.

Model speed in generating responses

C.

Financial cost of operating the model

D.

Energy efficiency of the model's computations

Question 48

A financial company is using ML to help with some of the company's tasks.

Which option is a use of generative AI models?

Options:

A.

Summarizing customer complaints

B.

Classifying customers based on product usage

C.

Segmenting customers based on type of investments

D.

Forecasting revenue for certain products

Question 49

A company manually reviews all submitted resumes in PDF format. As the company grows, the company expects the volume of resumes to exceed the company's review capacity. The company needs an automated system to convert the PDF resumes into plain text format for additional processing.

Which AWS service meets this requirement?

Options:

A.

Amazon Textract

B.

Amazon Personalize

C.

Amazon Lex

D.

Amazon Transcribe

Question 50

Which technique involves training AI models on labeled datasets to adapt the models to specific industry terminology and requirements?

Options:

A.

Data augmentation

B.

Fine-tuning

C.

Model quantization

D.

Continuous pre-training

Question 51

Which functionality does Amazon SageMaker Clarify provide?

Options:

A.

Integrates a Retrieval Augmented Generation (RAG) workflow

B.

Monitors the quality of ML models in production

C.

Documents critical details about ML models

D.

Identifies potential bias during data preparation

Question 52

How can companies use large language models (LLMs) securely on Amazon Bedrock?

Options:

A.

Design clear and specific prompts. Configure AWS Identity and Access Management (IAM) roles and policies by using least privilege access.

B.

Enable AWS Audit Manager for automatic model evaluation jobs.

C.

Enable Amazon Bedrock automatic model evaluation jobs.

D.

Use Amazon CloudWatch Logs to make models explainable and to monitor for bias.

Question 53

A medical company wants to develop an AI application that can access structured patient records, extract relevant information, and generate concise summaries.

Which solution will meet these requirements?

Options:

A.

Use Amazon Comprehend Medical to extract relevant medical entities and relationships. Apply rule-based logic to structure and format summaries.

B.

Use Amazon Personalize to analyze patient engagement patterns. Integrate the output with a general purpose text summarization tool.

C.

Use Amazon Textract to convert scanned documents into digital text. Design a keyword extraction system to generate summaries.

D.

Implement Amazon Kendra to provide a searchable index for medical records. Use a template-based system to format summaries.

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Total 177 questions