- A
Model ensembling
Why wrong: Ensembling combines multiple models for accuracy but does not address data privacy or deletion.
- B
Differential privacy
Differential privacy ensures that the model does not memorize individual data points.
- C
Data retention and deletion policies
Policies ensure data is deleted when no longer needed, complying with GDPR.
- D
Machine unlearning
Unlearning enables removal of specific data points from a trained model.
- E
Federated learning
Why wrong: Federated learning trains models without centralizing data but does not enable deletion of specific data.
Question 905 of 1,000
AI0-001 AI Infrastructure and Technologies Practice Question
This AI0-001 practice question tests your understanding of ai infrastructure and technologies. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is building a secure AI system that must comply with GDPR. They want to allow users to request deletion of their personal data from training sets and model outputs. Which THREE techniques should they implement?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Differential privacy
Differential privacy (B) is correct because it adds calibrated noise to training data or model outputs, ensuring that the inclusion or exclusion of any individual's data does not significantly affect the model's behavior. This provides a mathematical guarantee of privacy, which is essential for GDPR compliance when handling personal data. By limiting information leakage, differential privacy helps protect user data even if deletion requests are not fully implemented.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Model ensembling
Why it's wrong here
Ensembling combines multiple models for accuracy but does not address data privacy or deletion.
- ✓
Differential privacy
Why this is correct
Differential privacy ensures that the model does not memorize individual data points.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Data retention and deletion policies
Why this is correct
Policies ensure data is deleted when no longer needed, complying with GDPR.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Machine unlearning
Why this is correct
Unlearning enables removal of specific data points from a trained model.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Federated learning
Why it's wrong here
Federated learning trains models without centralizing data but does not enable deletion of specific data.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that federated learning alone satisfies GDPR deletion requirements, when in fact it only addresses data locality, not the ability to remove a specific user's influence from a trained model.
Detailed technical explanation
How to think about this question
Differential privacy typically works by adding Laplace or Gaussian noise to gradients during training (as in DP-SGD) or to query results, with privacy loss quantified by epsilon (ε). A lower ε value provides stronger privacy but reduces model utility. In practice, GDPR compliance may require balancing ε to meet both privacy guarantees and model performance, and techniques like Rényi differential privacy can provide tighter accounting for iterative training processes.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
AI Infrastructure and Technologies — study guide chapter
Learn the concepts, then practise the questions
- →
AI Infrastructure and Technologies practice questions
Targeted practice on this topic area only
- →
All AI0-001 questions
1,000 questions across all exam domains
- →
CompTIA AI+ AI0-001 study guide
Full concept coverage aligned to exam objectives
- →
AI0-001 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related AI0-001 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
AI Infrastructure and Technologies practice questions
Practise AI0-001 questions linked to AI Infrastructure and Technologies.
AI Security practice questions
Practise AI0-001 questions linked to AI Security.
AI Concepts and Foundations practice questions
Practise AI0-001 questions linked to AI Concepts and Foundations.
AI Concepts and Techniques practice questions
Practise AI0-001 questions linked to AI Concepts and Techniques.
Machine Learning and Deep Learning practice questions
Practise AI0-001 questions linked to Machine Learning and Deep Learning.
AI Models and Data Engineering practice questions
Practise AI0-001 questions linked to AI Models and Data Engineering.
Implementing AI Solutions practice questions
Practise AI0-001 questions linked to Implementing AI Solutions.
AI Implementation and Operations practice questions
Practise AI0-001 questions linked to AI Implementation and Operations.
AI Security, Ethics and Governance practice questions
Practise AI0-001 questions linked to AI Security, Ethics and Governance.
AI Governance and Ethics practice questions
Practise AI0-001 questions linked to AI Governance and Ethics.
CompTIA A+ hardware practice questions
Practise AI0-001 questions linked to CompTIA A+ hardware.
CompTIA A+ mobile devices practice questions
Practise AI0-001 questions linked to CompTIA A+ mobile devices.
Practice this exam
Start a free AI0-001 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Infrastructure and Technologies — This question tests AI Infrastructure and Technologies — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Differential privacy — Differential privacy (B) is correct because it adds calibrated noise to training data or model outputs, ensuring that the inclusion or exclusion of any individual's data does not significantly affect the model's behavior. This provides a mathematical guarantee of privacy, which is essential for GDPR compliance when handling personal data. By limiting information leakage, differential privacy helps protect user data even if deletion requests are not fully implemented.
What should I do if I get this AI0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.