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HomeCertificationsAIF-C01TopicsAI and ML Fundamentals
Free · No Signup RequiredAmazon Web Services · AIF-C01

AIF-C01 AI and ML Fundamentals Practice Questions

20+ practice questions focused on AI and ML Fundamentals — one of the most tested topics on the AWS Certified AI Practitioner AIF-C01 exam. Each question includes a detailed explanation so you learn why the right answer is correct.

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Exam Domains

Applications of Foundation ModelsAI and ML FundamentalsSecurity, Compliance, and Governance for AI SolutionsFundamentals of AI and MLFundamentals of Generative AIGenerative AI and Foundation ModelsGuidelines for Responsible AIAll domains →

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Sample AI and ML Fundamentals Questions

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1.

A data scientist needs to predict house prices based on features like square footage, number of bedrooms, and location. Which type of machine learning is most appropriate for this task?

A.Classification
B.Reinforcement learning
C.Regression
D.Clustering

Explanation: Regression is the correct choice because the task involves predicting a continuous numerical value (house price) based on input features. Unlike classification, which predicts discrete categories, regression models the relationship between independent variables and a continuous target, making it ideal for price prediction.

2.

A machine learning model achieves 99% accuracy on the training set but only 65% on the test set. Which phenomenon is the model experiencing?

A.Bias-variance tradeoff
B.Data leakage
C.Overfitting
D.Underfitting

Explanation: The model's high accuracy on the training set (99%) but significantly lower accuracy on the test set (65%) indicates that it has memorized the training data, including noise and outliers, rather than learning generalizable patterns. This is the classic symptom of overfitting, where the model performs well on seen data but fails to generalize to unseen data.

3.

A financial services firm must extract text from scanned loan application forms to automate data entry. The forms are in various languages. Which combination of AWS AI services should be used?

A.Amazon Transcribe and Amazon Polly
B.Amazon Kendra and Amazon Lex
C.Amazon Textract and Amazon Translate
D.Amazon Rekognition and Amazon Comprehend

Explanation: Amazon Textract is designed to extract text and data from scanned documents, including forms, using OCR (Optical Character Recognition). Amazon Translate then converts the extracted text from various languages into a target language, enabling automated data entry across multilingual loan applications. Together, they directly address the requirement of extracting text from scanned forms in multiple languages.

4.

A company wants to build a recommendation system for its e-commerce website. Historical data includes user purchase history, product categories, and ratings. Which AWS service is most suitable for this task?

A.Amazon Personalize
B.Amazon Forecast
C.Amazon SageMaker built-in algorithms
D.Amazon Comprehend

Explanation: Amazon Personalize is the correct choice because it is a fully managed AWS service specifically designed to build real-time recommendation systems using user-item interaction data, such as purchase history, product categories, and ratings. It uses machine learning to train and deploy personalized recommendation models without requiring you to manage infrastructure or write custom ML code, making it ideal for e-commerce recommendation scenarios.

5.

A binary classification model outputs probabilities. The default threshold of 0.5 results in high precision but low recall. Which action would likely increase recall while maintaining acceptable precision?

A.Use F1 score instead of accuracy
B.Decrease the threshold to 0.3
C.Apply oversampling to the minority class
D.Increase the threshold to 0.7

Explanation: Decreasing the threshold to 0.3 makes the model classify more instances as positive, which increases recall (more true positives captured) but may also increase false positives. The goal is to shift the precision-recall trade-off toward higher recall while keeping precision at an acceptable level, which is directly achieved by lowering the decision threshold.

+15 more AI and ML Fundamentals questions available

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How to master AI and ML Fundamentals for AIF-C01

1. Baseline your knowledge

Start with 10 questions to gauge your current understanding of AI and ML Fundamentals. This tells you whether you need a concept refresher or just practice.

2. Review every explanation

For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.

3. Focus on exam traps

AI and ML Fundamentals questions on the AIF-C01 frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.

4. Reach 80% consistently

Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.

Frequently asked questions

How many AIF-C01 AI and ML Fundamentals questions are on the real exam?

The exact number varies per candidate. AI and ML Fundamentals is tested as part of the AWS Certified AI Practitioner AIF-C01 blueprint. Practicing with targeted AI and ML Fundamentals questions ensures you can handle any format or difficulty that appears.

Are these AIF-C01 AI and ML Fundamentals practice questions free?

Yes. Courseiva provides free AIF-C01 practice questions across all exam topics and domains. The platform includes topic-based practice, mock exams, missed-question review, bookmarked questions, and readiness tracking — no account required.

Is AI and ML Fundamentals one of the harder AIF-C01 topics?

Difficulty is subjective, but AI and ML Fundamentals is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.

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Topic Info

Topic

AI and ML Fundamentals

Exam

AIF-C01

Questions available

20+