Winter Special Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: myex65

Home > Amazon Web Services > AWS Certified AI Practitioner > AIF-C01

AIF-C01 AWS Certified AI Practitioner Exam Question and Answers

Question # 4

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.

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.

Full Access
Question # 5

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?

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.

Full Access
Question # 6

A pharmaceutical company wants to analyze user reviews of new medications and provide a concise overview for each medication. Which solution meets these requirements?

A.

Create a time-series forecasting model to analyze the medication reviews by using Amazon Personalize.

B.

Create medication review summaries by using Amazon Bedrock large language models (LLMs).

C.

Create a classification model that categorizes medications into different groups by using Amazon SageMaker.

D.

Create medication review summaries by using Amazon Rekognition.

Full Access
Question # 7

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?

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.

Full Access
Question # 8

A company is using few-shot prompting on a base model that is hosted on Amazon Bedrock. The model currently uses 10 examples in the prompt. The model is invoked once daily and is performing well. The company wants to lower the monthly cost.

Which solution will meet these requirements?

A.

Customize the model by using fine-tuning.

B.

Decrease the number of tokens in the prompt.

C.

Increase the number of tokens in the prompt.

D.

Use Provisioned Throughput.

Full Access
Question # 9

What are tokens in the context of generative AI models?

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.

Full Access
Question # 10

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

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.

Full Access
Question # 11

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?

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.

Full Access
Question # 12

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?

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.

Full Access
Question # 13

A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents.

Which solution meets these requirements?

A.

Build an automatic named entity recognition system.

B.

Create a recommendation engine.

C.

Develop a summarization chatbot.

D.

Develop a multi-language translation system.

Full Access
Question # 14

A company needs to choose a model from Amazon Bedrock to use internally. The company must identify a model that generates responses in a style that the company's employees prefer.

What should the company do to meet these requirements?

A.

Evaluate the models by using built-in prompt datasets.

B.

Evaluate the models by using a human workforce and custom prompt datasets.

C.

Use public model leaderboards to identify the model.

D.

Use the model InvocationLatency runtime metrics in Amazon CloudWatch when trying models.

Full Access
Question # 15

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?

A.

Data leakage

B.

Hallucination

C.

Overfitting

D.

Underfitting

Full Access
Question # 16

A company uses Amazon SageMaker for its ML pipeline in a production environment. The company has large input data sizes up to 1 GB and processing times up to 1 hour. The company needs near real-time latency.

Which SageMaker inference option meets these requirements?

A.

Real-time inference

B.

Serverless inference

C.

Asynchronous inference

D.

Batch transform

Full Access
Question # 17

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?

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.

Full Access
Question # 18

A company wants to display the total sales for its top-selling products across various retail locations in the past 12 months.

Which AWS solution should the company use to automate the generation of graphs?

A.

Amazon Q in Amazon EC2

B.

Amazon Q Developer

C.

Amazon Q in Amazon QuickSight

D.

Amazon Q in AWS Chatbot

Full Access
Question # 19

A company has a database of petabytes of unstructured data from internal sources. The company wants to transform this data into a structured format so that its data scientists can perform machine learning (ML) tasks.

Which service will meet these requirements?

A.

Amazon Lex

B.

Amazon Rekognition

C.

Amazon Kinesis Data Streams

D.

AWS Glue

Full Access
Question # 20

A company wants to assess the costs that are associated with using a large language model (LLM) to generate inferences. The company wants to use Amazon Bedrock to build generative AI applications.

Which factor will drive the inference costs?

A.

Number of tokens consumed

B.

Temperature value

C.

Amount of data used to train the LLM

D.

Total training time

Full Access
Question # 21

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?

A.

Confusion matrix

B.

Correlation matrix

C.

R2 score

D.

Mean squared error (MSE)

Full Access
Question # 22

A company has built a chatbot that can respond to natural language questions with images. The company wants to ensure that the chatbot does not return inappropriate or unwanted images.

Which solution will meet these requirements?

A.

Implement moderation APIs.

B.

Retrain the model with a general public dataset.

C.

Perform model validation.

D.

Automate user feedback integration.

Full Access
Question # 23

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?

A.

Generative pre-trained transformers (GPT)

B.

Residual neural network

C.

Support vector machine

D.

WaveNet

Full Access
Question # 24

A company wants to deploy a conversational chatbot to answer customer questions. The chatbot is based on a fine-tuned Amazon SageMaker JumpStart model. The application must comply with multiple regulatory frameworks.

Which capabilities can the company show compliance for? (Select TWO.)

A.

Auto scaling inference endpoints

B.

Threat detection

C.

Data protection

D.

Cost optimization

E.

Loosely coupled microservices

Full Access
Question # 25

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?

A.

R-squared score

B.

Accuracy

C.

Root mean squared error (RMSE)

D.

Learning rate

Full Access
Question # 26

A company wants to use language models to create an application for inference on edge devices. The inference must have the lowest latency possible.

Which solution will meet these requirements?

A.

Deploy optimized small language models (SLMs) on edge devices.

B.

Deploy optimized large language models (LLMs) on edge devices.

C.

Incorporate a centralized small language model (SLM) API for asynchronous communication with edge devices.

D.

Incorporate a centralized large language model (LLM) API for asynchronous communication with edge devices.

Full Access
Question # 27

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.

Observer bias

D.

Confirmation bias

Full Access