Amazon AI1-C01

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Amazon AWS Certified AI Practitioner Sample Questions:

1. A company is building an ML model. The company collected new data and analyzed the data by creating a correlation matrix, calculating statistics, and visualizing the data.
Which stage of the ML pipeline is the company currently in?

A) Feature engineering
B) Data pre-processing
C) Exploratory data analysis
D) Hyperparameter tuning

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

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

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

5. An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort.
Which strategy meets these requirements?

A) Object detection
B) Inpainting
C) Named entity recognition
D) Anomaly detection

Solutions: