AWS Certified AI Practitioner AIF-C01 Practice Test

AWS Certified AI Practitioner AIF-C01 Practice Test practice questions, page 11 of 20, with answer review and explanations.

Question 51

A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company's products. Which methodology should the company use to meet these requirements?

  1. Supervised learning
  2. Unsupervised learning
  3. Reinforcement learning
  4. Reinforcement learning from human feedback (RLHF)

Question 52

An AI practitioner wants to use a foundation model (FM) to design a search application. The search application must handle queries that have text and images. Which type of FM should the AI practitioner use to power the search application?

  1. Multi-modal embedding model
  2. Text embedding model
  3. Multi-modal generation model
  4. Image generation model

Question 53

A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data. Which strategy will successfully fine-tune the model?

  1. Provide labeled data with the prompt field and the completion field.
  2. Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
  3. Purchase Provisioned Throughput for Amazon Bedrock.
  4. Train the model on journals and textbooks.

Question 54

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?

  1. Build a speech recognition system.
  2. Create a natural language processing (NLP) named entity recognition system.
  3. Develop an anomaly detection system.
  4. Create a fraud forecasting system.

Question 55

Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

  1. Integration with Amazon S3 for object storage
  2. Support for geospatial indexing and queries
  3. Scalable index management and nearest neighbor search capability
  4. Ability to perform real-time analysis on streaming data