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Real And Valid AIF-C01 Exam Questions & Answers

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Posted on: 01/20/25

Amazon provides the most reliable and authentic Amazon AIF-C01 Exam prep material there is. The 3 kinds of Amazon AIF-C01 Preparation formats ensure that there are no lacking points in a student when he attempts the actual AIF-C01 exam.

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iPassleader is one of the leading platforms that has been helping AWS Certified AI Practitioner (AIF-C01) exam candidates for many years. Over this long time period we have helped AIF-C01 exam candidates in their preparation. They got help from iPassleader AWS Certified AI Practitioner practice questions and easily got success in the final AIF-C01 Certification Exam. You can also trust iPassleader AIF-C01 exam dumps and start preparation with complete peace of mind and satisfaction.

Amazon AIF-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Fundamentals of AI and ML: This domain covers the fundamental concepts of artificial intelligence (AI) and machine learning (ML), including core algorithms and principles. It is aimed at individuals new to AI and ML, such as entry-level data scientists and IT professionals.
Topic 2
  • Fundamentals of Generative AI: This domain explores the basics of generative AI, focusing on techniques for creating new content from learned patterns, including text and image generation. It targets professionals interested in understanding generative models, such as developers and researchers in AI.
Topic 3
  • Applications of Foundation Models: This domain examines how foundation models, like large language models, are used in practical applications. It is designed for those who need to understand the real-world implementation of these models, including solution architects and data engineers who work with AI technologies to solve complex problems.
Topic 4
  • Security, Compliance, and Governance for AI Solutions: This domain covers the security measures, compliance requirements, and governance practices essential for managing AI solutions. It targets security professionals, compliance officers, and IT managers responsible for safeguarding AI systems, ensuring regulatory compliance, and implementing effective governance frameworks.
Topic 5
  • Guidelines for Responsible AI: This domain highlights the ethical considerations and best practices for deploying AI solutions responsibly, including ensuring fairness and transparency. It is aimed at AI practitioners, including data scientists and compliance officers, who are involved in the development and deployment of AI systems and need to adhere to ethical standards.

Amazon AWS Certified AI Practitioner Sample Questions (Q29-Q34):

NEW QUESTION # 29
A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment.
Which Amazon Bedrock pricing model meets these requirements?

  • A. Model customization
  • B. Provisioned Throughput
  • C. Spot Instance
  • D. On-Demand

Answer: D


NEW QUESTION # 30
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 Lex
  • C. AWS Glue
  • D. Amazon Rekognition

Answer: C


NEW QUESTION # 31
A company is building an ML model. The company collected new data and analyzed the data by creating a correlation matrix, calculating statistics, and visualizing the data.
Which stage of the ML pipeline is the company currently in?

  • A. Data pre-processing
  • B. Feature engineering
  • C. Exploratory data analysis
  • D. Hyperparameter tuning

Answer: C


NEW QUESTION # 32
A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts.
An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders.
What should the AI practitioner include in the report to meet the transparency and explainability requirements?

  • A. Code for model training
  • B. Sample data for training
  • C. Model convergence tables
  • D. Partial dependence plots (PDPs)

Answer: D


NEW QUESTION # 33
Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?

  • A. Calculate the total cost of resources used by the model.
  • B. Assess the color accuracy of images processed by the model.
  • C. Measure the model's accuracy against a predefined benchmark dataset.
  • D. Count the number of layers in the neural network.

Answer: C


NEW QUESTION # 34
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