試験の準備方法-実用的なAIF-C01関連資料試験-効果的なAIF-C01過去問

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Amazon AIF-C01 Exam Overview:

Certification Vendor:	Amazon Web Services (AWS)
Exam Name:	AWS Certified AI Practitioner (AIF-C01)
Exam Number:	AIF-C01
Passing Score:	700/1000
Available Languages:	Japanese, Simplified Chinese, Korean, Spanish, English, Portuguese (Brazil)
Real Exam Qty:	65
Exam Price:	$100 USD
Related Certifications:	AWS Certified Cloud Practitioner
Exam Format:	Multiple response, Multiple choice
Certificate Validity Period:	3 years
Exam Duration:	90 minutes
Recommended Training:	AWS Skill Builder - AI Practitioner Learning Plan AWS Certified AI Practitioner Official Exam Guide
Exam Registration:	AWS Training and Certification Registration AWS Certification Portal
Sample Questions:	Amazon AIF-C01 Sample Questions
Exam Way:	Online proctored exam or in-person test center
Pre Condition:	No formal prerequisites required. Recommended: basic understanding of cloud computing and general AI/ML concepts.
Official Syllabus URL:	https://aws.amazon.com/certification/certified-ai-practitioner/

>> AIF-C01関連資料 <<

Amazon AIF-C01過去問 & AIF-C01試験復習赤本

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Amazon AIF-C01 認定試験の出題範囲：

トピック	出題範囲
トピック 1	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.
トピック 2	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.
トピック 3	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.
トピック 4	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.
トピック 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 認定 AIF-C01 試験問題 (Q212-Q217):

質問 # 212
A company wants to use Amazon Q Business for its data. The company needs to ensure the security and privacy of the data.
Which combination of steps will meet these requirements? (Select TWO.)

A. Configure Amazon Inspector for authentication.
B. Allow public access to the Amazon Q index.
C. Configure AWS Identity and Access Management (IAM) for authentication.
D. Set up cross-account access to the Amazon Q index.
E. Enable AWS Key Management Service (AWS KMS) keys for the Amazon Q Business enterprise index.

正解：C、E

解説：
Comprehensive and Detailed Explanation From Exact AWS AI documents:
To secure data in Amazon Q Business, AWS recommends:
* AWS KMS (A) to encrypt data at rest and manage encryption keys.
* AWS IAM (E) to control authentication and authorization for users and services.
Together, these services ensure:
* Strong access control
* Data confidentiality
* Compliance with enterprise security requirements
Why the other options are incorrect:
* Cross-account access (B) does not inherently ensure privacy.
* Amazon Inspector (C) is for vulnerability scanning, not authentication.
* Public access (D) violates security best practices.
AWS AI document references:
* Amazon Q Business Security Overview
* Data Protection with AWS KMS
* Access Control with AWS IAM

質問 # 213
A company has terabytes of data in a database that the company can use for business analysis. The company wants to build an AI-based application that can build a SQL query from input text that employees provide. The employees have minimal experience with technology.
Which solution meets these requirements?

A. Generative pre-trained transformers (GPT)
B. Residual neural network
C. WaveNet
D. Support vector machine

正解：A

質問 # 214
A company wants to develop an educational game where users answer questions such as the following: "A jar contains six red, four green, and three yellow marbles. What is the probability of choosing a green marble from the jar?" Which solution meets these requirements with the LEAST operational overhead?

A. Use supervised learning to create a regression model that will predict probability.
B. Use reinforcement learning to train a model to return the probability.
C. Use code that will calculate probability by using simple rules and computations.
D. Use unsupervised learning to create a model that will estimate probability density.

正解：C

解説：
The problem involves a simple probability calculation that can be handled efficiently by straightforward mathematical rules and computations. Using machine learning techniques would introduce unnecessary complexity and operational overhead.
* Option C (Correct): "Use code that will calculate probability by using simple rules and computations": This is the correct answer because it directly solves the problem with minimal overhead, using basic probability rules.
* Option A: "Use supervised learning to create a regression model" is incorrect as it overcomplicates the solution for a simple probability problem.
* Option B: "Use reinforcement learning to train a model" is incorrect because reinforcement learning is not needed for a simple probability calculation.
* Option D: "Use unsupervised learning to create a model" is incorrect as unsupervised learning is not applicable to this task.
AWS AI Practitioner References:
* Choosing the Right Solution for AI Tasks: AWS recommends using the simplest and most efficient approach to solve a given problem, avoiding unnecessary machine learning techniques for straightforward tasks.

質問 # 215
A company is developing a new image classification model by using a dataset of photos. The dataset must follow the AWS principles of responsible AI.
Which characteristics should the dataset have to meet this requirement?

A. The dataset should be diverse, sourced from reputable sources, and have balanced categories.
B. The dataset should contain over 5 million photos, and 1% of photos should be labeled.
C. The dataset should include photos from a limited source.
D. The dataset should be curated entirely by the company's own engineers and researchers.

正解：A

解説：
Comprehensive and Detailed Explanation (AWS AI documents):
AWS Responsible AI principles stress the importance of fairness, robustness, and accountability, which begin with the quality of the data used to train models. A responsible dataset should:
* Be diverse, representing different populations, environments, and conditions to reduce bias
* Be sourced from reputable and appropriate sources, ensuring data quality and ethical use
* Have balanced categories, preventing the model from favoring one class over others and reducing the risk of discriminatory outcomes These characteristics help ensure that the resulting image classification model behaves fairly, performs reliably across groups, and aligns with AWS Responsible AI best practices.
Why the other options are incorrect:
* B focuses on dataset size rather than quality, balance, or representativeness.
* C increases the risk of bias and poor generalization.
* D limits diversity and does not inherently ensure fairness or accountability.
AWS AI Study Guide References:
* AWS Responsible AI principles: fairness and data quality
* AWS guidance on dataset selection and preparation for responsible ML

質問 # 216
An online media streaming company wants to give its customers the ability to perform natural language-based image search and filtering. The company needs a vector database that can help with similarity searches and nearest neighbor queries.
Which AWS service meets these requirements?

A. Amazon Polly
B. Amazon Personalize
C. Amazon OpenSearch Service
D. Amazon Comprehend

正解：C

質問 # 217
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