We have prepared AWS Certified AI Practitioner (AIF-C01) certification sample questions to make you aware of actual exam properties. This sample question set provides you with information about the AI Practitioner exam pattern, question formate, a difficulty level of questions and time required to answer each question. To get familiar with AWS Certified AI Practitioner exam, we suggest you try our Sample AWS AIF-C01 Certification Practice Exam in simulated AWS certification exam environment.
To test your knowledge and understanding of concepts with real-time scenario based AWS AIF-C01 questions, we strongly recommend you to prepare and practice with Premium AWS AI Practitioner Certification Practice Exam. The premium AWS AI Practitioner certification practice exam helps you identify topics in which you are well prepared and topics in which you may need further training to achieving great score in actual AWS Certified AI Practitioner exam.
AWS AIF-C01 Sample Questions:
01. Which type of learning involves an agent improving its actions based on a system of rewards and penalties?
a) Transfer learning
b) Unsupervised learning
c) Reinforcement learning
d) Supervised learning
02. Your company plans to launch a chatbot to improve customer service using generative AI. Which AWS services and techniques will support this use case?
a) Amazon Bedrock to deploy the chatbot with a pre-trained model.
b) Amazon SageMaker JumpStart for fine-tuning the chatbot model.
c) Amazon Rekognition for visual analysis in the chatbot.
d) Amazon Lex for NLP capabilities.
03. Which practices are essential for selecting datasets to ensure responsible AI?
(Choose two.)
a) Balancing datasets to prevent over-representation of any group.
b) Prioritizing large datasets without regard to representativeness.
c) Using only open-source datasets.
d) Ensuring inclusivity and diversity in dataset sources.
04. You are tasked with building a solution to classify customer reviews as positive or negative. The solution must handle real-time inferencing. Which of the following approaches and services are appropriate?
(Choose three.)
a) Use AWS Lambda for real-time predictions.
b) Use Amazon Polly for text-t o-speech capabilities.
c) Deploy the model using Amazon SageMaker Hosting Services.
d) Use AWS Glue for batch processing.
e) Use Amazon SageMaker to train the model.
05. A healthcare organization plans to use AI to process patient data while adhering to HIPAA regulations. What measures should they implement to secure the AI system?
a) Use Amazon Rekognition to identify patient faces.
b) Employ SageMaker Clarify to ensure fairness in predictive models.
c) Enable AWS PrivateLink for secure data transfer.
d) Configure encryption for data at rest using AWS KMS.
06. What is the purpose of the temperature parameter in generative AI models?
a) Adjusts the speed of inference.
b) Controls the number of tokens generated in a response.
c) Balances between deterministic and creative outputs.
d) Increases the model's accuracy for structured data tasks.
07. Your organization is building an AI-powered e-commerce recommendation engine using foundation models. Which AWS services will you choose for this use case?
a) Amazon OpenSearch for storing embeddings.
b) AWS Glue for transforming recommendation data.
c) Amazon SageMaker for model training and deployment.
d) Amazon Polly for converting recommendations into speech.
e) Amazon Bedrock for pre-trained model access.
08. What is the primary purpose of Amazon SageMaker Model Cards?
a) To automate dataset curation for model training.
b) To enhance the deployment speed of AI models.
c) To document model details for governance and transparency
d) To optimize the hyperparameter tuning process.
09. Which of the following is a key feature of responsible AI systems?
a) Data latency
b) Low cost
c) High throughput
d) Robustness
10. What is the primary role of fine-tuning in the foundation model lifecycle?
a) To evaluate the model against benchmark datasets.
b) To optimize the model for domain-specific tasks.
c) To ensure model safety and explainability.
d) To retrain the model on a general-purpose dataset.
Answers:
Question: 01
Answer: b |
Question: 02
Answer: a, b, d |
Question: 03
Answer: a, d |
Question: 04
Answer: a, c, e |
Question: 05
Answer: b, c, d |
Question: 06
Answer: c |
Question: 07
Answer: a, c, e |
Question: 08
Answer: c |
Question: 09
Answer: d |
Question: 10
Answer: b |
Note: Please update us by writing an email on feedback@vmexam.com for any error in AWS Certified AI Practitioner certification exam sample questions
