AIF-C01 Fundamentals of AI and ML Practice Question
A team trained a deep learning model that achieves 99% accuracy on training data but only 70% on validation data. What is the most likely issue?
⚠ Common exam trap
The AIF-C01 exam often tests the distinction between overfitting and underfitting by presenting a scenario where training accuracy is high but validation accuracy is low, tempting candidates to incorrectly choose underfitting if they focus only on the low validation score.
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
✓
Overfitting
The model performs exceptionally well on training data (99% accuracy) but significantly worse on validation data (70% accuracy). This large gap indicates the model has memorized the training data, including noise and irrelevant patterns, rather than learning generalizable features — a classic symptom of overfitting.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Underfitting
Why it's wrong here
Underfitting results in poor performance on both training and validation data, not high training accuracy.
- ✓
Overfitting
Why this is correct
Overfitting occurs when the model learns training data too well, including noise, failing to generalize to validation data.
- ✗
Data leakage
Why it's wrong here
Data leakage can inflate training performance but would also affect validation if leakage is present.
- ✗
Feature scaling
Why it's wrong here
Feature scaling affects model convergence but not the training-validation accuracy gap.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIF-C01 exam.