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Amazon AWS Certified AI Practitioner Sample Questions:

1. 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) Import the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.
B) 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.
C) Import the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.
D) Import the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.

2. An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data.
How should the AI practitioner prevent responses based on confidential data?

A) Mask the confidential data in the inference responses by using dynamic data masking.
B) Encrypt the confidential data in the inference responses by using Amazon SageMaker.
C) Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.
D) Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).

3. 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?

A) Amazon Personalize
B) Amazon Lex
C) Amazon Transcribe
D) Amazon Textract

4. An e-commerce company wants to build a solution to determine customer sentiments based on written customer reviews of products.
Which AWS services meet these requirements? (Select TWO.)

A) Amazon Comprehend
B) Amazon Polly
C) Amazon Lex
D) Amazon Bedrock
E) Amazon Rekognition

5. A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company's products.
Which methodology should the company use to meet these requirements?

A) Reinforcement learning from human feedback (RLHF)
B) Supervised learning
C) Unsupervised learning
D) Reinforcement learning

Solutions: