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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
Certificate Validity Period:3 years
Real Exam Qty:65
Exam Duration:90 minutes
Exam Price:$100 USD
Available Languages:English, Simplified Chinese, Japanese, Korean, Spanish, Portuguese (Brazil)
Exam Format:Multiple choice, Multiple response
Related Certifications:AWS Certified Cloud Practitioner
Passing Score:700/1000
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/

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Amazon AIF-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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.
Topic 5
  • 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.

Amazon AWS Certified AI Practitioner Sample Questions (Q185-Q190):

NEW QUESTION # 185
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?

Answer: C


NEW QUESTION # 186
What Is the benefit of fine-tuning a foundation model (FM)?

Answer: C


NEW QUESTION # 187
A company wants to use generative AI to increase developer productivity and software development. The company wants to use Amazon Q Developer.
What can Amazon Q Developer do to help the company meet these requirements?

Answer: C

Explanation:
Amazon Q Developer is a tool designed to assist developers in increasing productivity by generating code snippets, managing reference tracking, and handling open-source license tracking. These features help developers by automating parts of the software development process.
Option A (Correct): "Create software snippets, reference tracking, and open-source license tracking": This is the correct answer because these are key features that help developers streamline and automate tasks, thus improving productivity.
Option B: "Run an application without provisioning or managing servers" is incorrect as it refers to AWS Lambda or AWS Fargate, not Amazon Q Developer.
Option C: "Enable voice commands for coding and providing natural language search" is incorrect because this is not a function of Amazon Q Developer.
Option D: "Convert audio files to text documents by using ML models" is incorrect as this refers to Amazon Transcribe, not Amazon Q Developer.
AWS AI Practitioner Reference:
Amazon Q Developer Features: AWS documentation outlines how Amazon Q Developer supports developers by offering features that reduce manual effort and improve efficiency.


NEW QUESTION # 188
A bank is building a chatbot to answer customer questions about opening a bank account. The chatbot will use public bank documents to generate responses. The company will use Amazon Bedrock and prompt engineering to improve the chatbot's responses.
Which prompt engineering technique meets these requirements?

Answer: A

Explanation:
Directional stimulus prompting guides the foundation model to produce outputs aligned with business context. It's particularly effective for aligning responses with public documents and improving coherence. From Bedrock Prompt Engineering Techniques documentation:
"Directional stimulus prompting provides structured prompts to steer the model output towards desired formats or behaviors using specific linguistic cues."


NEW QUESTION # 189
A financial company is developing a generative AI application for loan approval decisions. The company needs the application output to be responsible and fair.

Answer: A


NEW QUESTION # 190
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