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[General] AIF-C01 Test Topics Pdf - Valid AIF-C01 Test Dumps

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【General】 AIF-C01 Test Topics Pdf - Valid AIF-C01 Test Dumps

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Amazon AWS Certified AI Practitioner Sample Questions (Q153-Q158):NEW QUESTION # 153
A company has multiple datasets that contain historical dat
a. The company wants to use ML technologies to process each dataset.
Select the correct ML technology from the following list for each dataset. Select each ML technology one time or not at all. (Select THREE.) Computer vision Natural language processing (NLP) Reinforcement learning Time series forecasting

Answer:
Explanation:


NEW QUESTION # 154
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 supports only text data. Nova Lite is optimized for numerical data.
  • B. Nova Micro runs only on CPUs. Nova Lite runs only on GPUs.
  • C. Nova Micro uses transformer-based architectures. Nova Lite does not use transformer-based architectures.
  • D. Nova Micro supports only text. Nova Lite supports images, videos, and text.
Answer: D
Explanation:
The correct answer is C, because Amazon Nova Micro is a smaller, lower-cost foundation model that is text- only, while Nova Lite is a more capable multimodal model that supports images, videos, and text. According to AWS Bedrock documentation, the Nova model family includes variants that differ in capability and cost.
Nova Micro is optimized for lightweight text-based tasks, including summarization, question answering, and basic reasoning. This makes it cheaper to operate and well-suited for cost-sensitive workloads. Nova Lite, on the other hand, is a multimodal FM that can analyze documents, screenshots, photographs, charts, and videos, making it ideal for media companies requiring cross-format understanding. AWS clarifies that both Micro and Lite use transformer-based architectures, and run on managed infrastructure that abstracts hardware considerations. Therefore, the main differentiator is capability-and Nova Micro being text-only is the more cost-effective option. Nova Lite is appropriate only when image or video analysis is required.
Referenced AWS Documentation:
* Amazon Bedrock - Nova Model Family Overview
* AWS Generative AI Model Selection Guide

NEW QUESTION # 155
A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source.
Which solution meets these requirements?
  • A. Develop an anomaly detection system.
  • B. Create a fraud forecasting system.
  • C. Build a speech recognition system.
  • D. Create a natural language processing (NLP) named entity recognition system.
Answer: A
Explanation:
An anomaly detection system is suitable for identifying unusual patterns or behaviors, such as suspicious IP addresses, which might indicate a potential threat.
* Anomaly Detection:
* Anomaly detection uses machine learning algorithms to identify deviations from normal behavior, such as unexpected traffic from a suspicious IP address.
* This is a common approach for identifying potential threats or malicious activity in cybersecurity applications.
* Why Option C is Correct:
* Detects Suspicious Behavior: An anomaly detection system can monitor and detect IP addresses that exhibit unusual or suspicious patterns.
* Real-time Monitoring: Provides continuous analysis of network traffic to identify potential security threats.
* Why Other Options are Incorrect:
* A. Speech recognition system: Is unrelated to detecting suspicious IP addresses.
* B. NLP named entity recognition: Focuses on identifying entities in text, not IP address analysis.
* D. Fraud forecasting system: Generally used for predicting fraud, not directly applicable to identifying suspicious IPs.
Thus, C is the correct answer for detecting suspicious IP addresses.

NEW QUESTION # 156
A company wants to create a chatbot by using a foundation model (FM) on Amazon Bedrock. The FM needs to access encrypted data that is stored in an Amazon S3 bucket.
The data is encrypted with Amazon S3 managed keys (SSE-S3).
The FM encounters a failure when attempting to access the S3 bucket data.
Which solution will meet these requirements?
  • A. Set the access permissions for the S3 buckets to allow public access to enable access over the internet.
  • B. Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key.
  • C. Ensure that the S3 data does not contain sensitive information.
  • D. Use prompt engineering techniques to tell the model to look for information in Amazon S3.
Answer: B
Explanation:
Amazon Bedrock needs the appropriate IAM role with permission to access and decrypt data stored in Amazon S3. If the data is encrypted with Amazon S3 managed keys (SSE-S3), the role that Amazon Bedrock assumes must have the required permissions to access and decrypt the encrypted data.
* Option A (Correct): "Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key": This is the correct solution as it ensures that the AI model can access the encrypted data securely without changing the encryption settings or compromising data security.
* Option B: "Set the access permissions for the S3 buckets to allow public access" is incorrect because it violates security best practices by exposing sensitive data to the public.
* Option C: "Use prompt engineering techniques to tell the model to look for information in Amazon S3" is incorrect as it does not address the encryption and permission issue.
* Option D: "Ensure that the S3 data does not contain sensitive information" is incorrect because it does not solve the access problem related to encryption.
AWS AI Practitioner References:
* Managing Access to Encrypted Data in AWS: AWS recommends using proper IAM roles and policies to control access to encrypted data stored in S3.

NEW QUESTION # 157
A financial company uses a generative AI model to assign credit limits to new customers. The company wants to make the decision-making process of the model more transparent to its customers.
  • A. Use a rule-based system instead of an ML model
  • B. Apply explainable AI techniques to show customers which factors influenced the model's decision
  • C. Increase the accuracy of the model to reduce the need for transparency
  • D. Develop an interactive UI for customers and provide clear technical explanations about the system
Answer: B
Explanation:
Comprehensive and Detailed
Explainable AI (XAI) techniques such as SHAP (SHapley values) or feature attribution provide transparency by showing which input factors influenced decisions.
A is not scalable for complex use cases.
C does not guarantee real interpretability.
D ignores the regulatory need for explainability.
Reference:
AWS SageMaker Clarify - Explainable AI

NEW QUESTION # 158
......
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