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| Certification Vendor: | Amazon Web Services (AWS) |
|---|---|
| Exam Name: | AWS Certified AI Practitioner |
| Exam Number: | AIF-C01 |
| Passing Score: | 700 / 1000 |
| Exam Price: | USD 100 |
| Related Certifications: | AWS Certified Data Engineer - Associate AWS Certified Cloud Practitioner AWS Certified Machine Learning Engineer - Associate |
| Certificate Validity Period: | 3 years |
| Exam Format: | Multiple response, Multiple choice |
| Exam Duration: | 90 minutes |
| Real Exam Qty: | 80 |
| Available Languages: | Korean, Portuguese (Brazil), Japanese, Simplified Chinese, English |
| Sample Questions: | Amazon AIF-C01 Sample Questions |
| Exam Way: | Online proctored exam (Pearson VUE) or in-person testing center |
| Pre Condition: | None required. Recommended: General IT cloud knowledge and basic understanding of AI/ML concepts. AWS Cloud Practitioner certification is a recommended prerequisite but not mandatory. |
| Official Syllabus URL: | https://aws.amazon.com/certification/certified-ai-practitioner/ |
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NEW QUESTION # 97
A company wants to collaborate with several research institutes to develop an AI model. The company needs standardized documentation of model version tracking and a record of model development.
Which solution meets these requirements?
Answer: B
NEW QUESTION # 98
A medical company wants to develop an AI application that can access structured patient records, extract relevant information, and generate concise summaries.
Which solution will meet these requirements?
Answer: C
NEW QUESTION # 99
A company is building a job recommendation system based on job posting data and job seeker user profiles. The system shows bias in job recommendations based on gender for user profiles that are otherwise equivalent.
Which principle should the company follow to address this issue, according to AWS best practices for responsible AI?
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact AWS AI documents:
Fairness is a core principle of AWS Responsible AI. It requires that AI systems:
Do not produce biased or discriminatory outcomes
Treat individuals and groups equitably
Are evaluated and mitigated for bias across protected attributes
AWS Responsible AI guidance specifically highlights fairness as the principle used to identify, measure, and mitigate bias in AI systems such as recommendation engines.
Why the other options are incorrect:
Governance (A) focuses on oversight and policies.
Explainability (B) explains decisions but does not directly mitigate bias.
Controllability (C) focuses on human oversight and intervention.
AWS AI document references:
AWS Responsible AI Principles
Bias and Fairness in ML Systems
Responsible AI Best Practices on AWS
NEW QUESTION # 100
A company used Amazon Bedrock to build an AI assistant. The AI assistant received a user prompt that instructed the assistant to provide the guidelines that the company used to configure the assistant. The prompt also instructed the assistant to display the full text of the initial setup. The AI assistant revealed its system prompt in the response.
Which type of prompt attack has occurred?
Answer: A
Explanation:
The attack is specifically prompt leakage because the user's objective is to obtain confidential system-level instructions or configuration information from the AI application. AWS defines prompt leakage as user prompts designed to "extract or reveal the system prompt, developer instructions, or other confidential configuration details." The scenario precisely matches this definition. The user asks the assistant to disclose the guidelines used to configure it and to reproduce the complete initial setup. The assistant then reveals its system prompt. The defining outcome is therefore unauthorized disclosure of protected prompt instructions.
Prompt leakage is related to the broader category of prompt attacks, and a leakage attempt can involve prompt-injection techniques. However, when AWS asks for the specific type of attack and the attacker is intentionally trying to expose the hidden system prompt or developer instructions, prompt leakage is the more precise classification.
A jailbreak generally attempts to bypass model safeguards or restrictions so the model performs behavior that would normally be prohibited. Although jailbreaks and prompt leakage can overlap, the core purpose in this scenario is disclosure of system configuration rather than simply bypassing a safety policy.
Prompt injection is the broader technique of introducing malicious instructions designed to override or manipulate existing instructions. For example, an attacker might tell the application to ignore previous instructions. AWS includes jailbreaks, prompt injections, and prompt leakages within its prompt-attack filtering capabilities.
A denied topic violation occurs when content concerns a topic explicitly configured as prohibited in Amazon Bedrock Guardrails. It does not describe system-prompt disclosure.
AWS recommends protecting generative AI applications by using Bedrock Guardrails prompt-attack detection, clearly defined system instructions, controlled access to tools and resources, input evaluation, output validation, and security testing.
NEW QUESTION # 101
HOTSPOT
Select the correct AI term from the following list for each statement. Each AI term should be selected one time. (Select THREE.)
* AI
* Deep learning
* ML
Answer:
Explanation:
Explanation:
Artificial Intelligence (AI) is the broad field focused on simulating human problem-solving and cognitive abilities, including reasoning, perception, and decision-making.
(Reference: AWS Certified AI Practitioner Official Study Guide)
Machine Learning (ML) is a subset of AI that uses data-driven algorithms to identify patterns and make predictions without explicit programming for each specific task.
(Reference: AWS Machine Learning Overview)
Deep learning is a subset of ML that uses neural networks with many layers (deep neural networks) to process complex data and extract high-level features.
(Reference: AWS Deep Learning on AWS)
NEW QUESTION # 102
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