AWS Certified AI Practitioner (AIF-C01)

The AWS Certified AI Practitioner (AIF-C01) were last updated on today.

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Viewing questions 21-25 out of 120 questions

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Topic 1 - Exam A

Question #21 Topic 1

A company is using custom models in Amazon Bedrock for a generative AI application. The company wants to use a company managed encryption key to encrypt the model artifacts that the model customization jobs create. Which AWS service meets these requirements?

A AWS Key Management Service (AWS KMS)
B Amazon Inspector
C Amazon Macie
D AWS Secrets Manager

Suggested Answer: A
NOTE: 根据提供的文本，公司希望使用由公司管理的加密密钥来加密生成AI应用程序自定义模型作业所创建的模型工件。AWS Key Management Service (AWS KMS) 提供了管理加密密钥的能力，并且适用于这种场景。

Question #22 Topic 1

An AI practitioner wants to predict the classification of flowers based on petal length, petal width, sepal length, and sepal width. Which algorithm meets these requirements?

A K-nearest neighbors (k-NN)
B K-mean
C Autoregressive Integrated Moving Average (ARIMA)
D Linear regression

Suggested Answer: A
NOTE: The task involves predicting the classification of flowers, which is a supervised learning problem with categorical output. K-nearest neighbors (k-NN) is suitable for classification tasks and can use the provided features (petal length, petal width, sepal length, and sepal width) to classify the flowers. K-means is an unsupervised learning algorithm used for clustering, not classification. ARIMA is used for time series forecasting, and linear regression is used for predicting continuous values, not for classification.

Question #23 Topic 1

A company has developed a generative text summarization model by using Amazon Bedrock. The company will use Amazon Bedrock automatic model evaluation capabilities. Which metric should the company use to evaluate the accuracy of the model?

A Area Under the ROC Curve (AUC) score
B F1 score
C BERTScore
D Real world knowledge (RWK) score

Suggested Answer: C
NOTE: 公司需要评估生成式文本摘要模型的准确性。在给定的选项中，BERTScore 是一种用于自然语言处理任务的评估指标，特别适用于文本生成任务，因为它考虑了语义相似度。而其他选项如 AUC、F1 分数和 RWK 分数可能不专门针对文本生成或文本摘要任务。

Question #24 Topic 1

A company is developing an ML model to make loan approvals. The company must implement a solution to detect bias in the model. The company must also be able to explain the model's predictions. Which solution will meet these requirements?

A Amazon SageMaker Clarify
B Amazon SageMaker Data Wrangler
C Amazon SageMaker Model Cards
D AWS AI Service Cards

Suggested Answer: A
NOTE: The question asks for a solution that can detect bias in the ML model and explain its predictions. Amazon SageMaker Clarify is specifically designed to help detect and mitigate bias in machine learning models, as well as provide model explanations. The other options do not directly address these requirements.

Question #25 Topic 1

A company is developing a mobile ML app that uses a phone's camera to diagnose and treat insect bites. The company wants to train an image classification model by using a diverse dataset of insect bite photos from different genders, ethnicities, and geographic locations around the world. Which principle of responsible AI does the company demonstrate in this scenario?

A Fairness
B Explainability
C Governance
D Transparency

Suggested Answer: A
NOTE: 选择答案 A '公平性'，因为公司在使用多样化的数据集来训练图像分类模型时，展示了对不同性别、种族和地理位置的考虑。这体现了负责任的人工智能中的公平性原则，确保不同群体都能得到公正对待。