AIF-C01 TEST CRAM: AWS CERTIFIED AI PRACTITIONER & AIF-C01 VCE DUMPS & AIF-C01 RELIABLE BRAINDUMPS

AIF-C01 Test Cram: AWS Certified AI Practitioner & AIF-C01 VCE Dumps & AIF-C01 Reliable Braindumps

AIF-C01 Test Cram: AWS Certified AI Practitioner & AIF-C01 VCE Dumps & AIF-C01 Reliable Braindumps

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Amazon AWS Certified AI Practitioner Sample Questions (Q69-Q74):

NEW QUESTION # 69
What are tokens in the context of generative AI models?

  • A. Tokens are the basic units of input and output that a generative AI model operates on, representing words, subwords, or other linguistic units.
  • B. Tokens are the mathematical representations of words or concepts used in generative AI models.
  • C. Tokens are the pre-trained weights of a generative AI model that are fine-tuned for specific tasks.
  • D. Tokens are the specific prompts or instructions given to a generative AI model to generate output.

Answer: A


NEW QUESTION # 70
A hospital is developing an AI system to assist doctors in diagnosing diseases based on patient records and medical images. To comply with regulations, the sensitive patient data must not leave the country the data is located in.
Which data governance strategy will ensure compliance and protect patient privacy?

  • A. Data enrichment
  • B. Data quality
  • C. Data residency
  • D. Data discoverability

Answer: C

Explanation:
Data residency is the principle and practice of ensuring that data remains within a specific geographic location or jurisdiction, often to comply with local regulations and privacy laws (such as HIPAA, GDPR, or national healthcare laws). Data residency policies prevent sensitive data (such as patient records) from being transferred or accessed outside the designated country, thus protecting privacy and ensuring regulatory compliance.
A is correct:
"Data residency refers to where data is stored geographically, and often organizations need to ensure that certain data does not leave a particular country or region to comply with legal or regulatory requirements." (Reference: AWS Data Residency Whitepaper, AWS Responsible AI & Data Privacy)
"Data residency refers to where data is stored geographically, and often organizations need to ensure that certain data does not leave a particular country or region to comply with legal or regulatory requirements." (Reference: AWS Data Residency Whitepaper, AWS Responsible AI & Data Privacy) B (data quality) refers to the accuracy and reliability of data, not its location.
C (data discoverability) is about being able to find and access data, not restricting its movement.
D (data enrichment) is about enhancing data with additional information.
"Maintaining data residency is critical in healthcare and regulated industries to ensure data does not leave the prescribed jurisdiction." (Reference: AWS Data Residency)
"Maintaining data residency is critical in healthcare and regulated industries to ensure data does not leave the prescribed jurisdiction." (Reference: AWS Data Residency)


NEW QUESTION # 71
A company has a database of petabytes of unstructured data from internal sources. The company wants to transform this data into a structured format so that its data scientists can perform machine learning (ML) tasks.
Which service will meet these requirements?

  • A. Amazon Kinesis Data Streams
  • B. Amazon Rekognition
  • C. Amazon Lex
  • D. AWS Glue

Answer: D

Explanation:
AWS Glue is the correct service for transforming petabytes of unstructured data into a structured format suitable for machine learning tasks.
* AWS Glue:
* A fully managed extract, transform, and load (ETL) service that makes it easy to prepare and transform unstructured data into a structured format.
* Provides a range of tools for cleaning, enriching, and cataloging data, making it ready for data scientists to use in ML models.
* Why Option D is Correct:
* Data Transformation: AWS Glue can handle large volumes of data and transform unstructured data into structured formats efficiently.
* Integrated ML Support: Glue integrates with other AWS services to support ML workflows.
* Why Other Options are Incorrect:
* A. Amazon Lex: Used for building chatbots, not for data transformation.
* B. Amazon Rekognition: Used for image and video analysis, not for data transformation.
* C. Amazon Kinesis Data Streams: Handles real-time data streaming, not suitable for batch transformation of large volumes of unstructured data.


NEW QUESTION # 72
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. Accuracy
  • B. Learning rate
  • C. Root mean squared error (RMSE)
  • D. R-squared score

Answer: A


NEW QUESTION # 73
A company has a database of petabytes of unstructured data from internal sources. The company wants to transform this data into a structured format so that its data scientists can perform machine learning (ML) tasks.
Which service will meet these requirements?

  • A. Amazon Kinesis Data Streams
  • B. Amazon Rekognition
  • C. Amazon Lex
  • D. AWS Glue

Answer: D


NEW QUESTION # 74
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