Amazon AIF-C01 Exam Dumps

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Amazon AIF-C01 Sample Questions

Question # 1

A bank is fine-tuning a large language model (LLM) on Amazon Bedrock to assist customers with questions about their loans. The bank wants to ensure that the model does not reveal any private customer data.Which solution meets these requirements?

A. Use Amazon Bedrock Guardrails.
B. Remove personally identifiable information (PII) from the customer data before fine-tuning the LLM.
C. Increase the Top-K parameter of the LLM.
D. Store customer data in Amazon S3. Encrypt the data before fine-tuning the LLM.



Question # 2

Sentiment analysis is a subset of which broader field of AI?

A. Computer vision
B. Robotics
C. Natural language processing (NLP)
D. Time series forecasting



Question # 3

Which prompting technique can protect against prompt injection attacks?

A. Adversarial prompting
B. Zero-shot prompting
C. Least-to-most prompting
D. Chain-of-thought prompting



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.



Question # 5

A company that streams media is selecting an Amazon Nova foundation model (FM) to process documents and images. The company is comparing Nova Micro and Nova Lite. The company wants to minimize costs.

A. Nova Micro uses transformer-based architectures. Nova Lite does not use transformer-based architectures.
B. Nova Micro supports only text data. Nova Lite is optimized for numerical data.
C. Nova Micro supports only text. Nova Lite supports images, videos, and text.
D. Nova Micro runs only on CPUs. Nova Lite runs only on GPUs.



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