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Amazon AI1-C01 Exam Syllabus Topics:

Amazon AWS Certified AI Practitioner Sample Questions:

1. A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately.
Which Amazon SageMaker inference option will meet these requirements?

A) Batch transform
B) Real-time inference
C) Serverless inference
D) Asynchronous inference

2. 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) Root mean squared error (RMSE)
B) Learning rate
C) R-squared score
D) Accuracy

3. A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals.
Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?

A) Moderation logs
B) User-generated content
C) Content moderation guidelines
D) Benchmark datasets

4. A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level.
Which solution will meet these requirements?

A) Increase the temperature parameter.
B) Decrease the epochs.
C) Increase the epochs.
D) Decrease the batch size.

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

A) Use Amazon CloudWatch Logs to make models explainable and to monitor for bias.
B) Design clear and specific prompts. Configure AWS Identity and Access Management (IAM) roles and policies by using least privilege access.
C) Enable Amazon Bedrock automatic model evaluation jobs.
D) Enable AWS Audit Manager for automatic model evaluation jobs.

Solutions: