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AI Concepts and FoundationsmediumMultiple ChoiceObjective-mapped

AI0-001 AI Concepts and Foundations Practice Question

Exhibit

Epoch 10/10 - loss: 0.01 - accuracy: 0.99 - val_loss: 0.45 - val_accuracy: 0.85

Refer to the exhibit. A data scientist observes the training output. Which issue is most likely?

⚠ Common exam trap

CompTIA often tests the distinction between overfitting and underfitting by showing a loss curve where training loss is low but validation loss rises, tricking candidates who focus only on the low training loss without checking validation performance.

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 exhibit shows training loss decreasing while validation loss increases after a certain epoch, which is the classic signature of overfitting. The model is memorizing the training data rather than learning generalizable patterns, leading to poor performance on unseen data.

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

    Incorrect; underfitting would have low accuracy on both training and validation.

  • Data augmentation failure

    Why it's wrong here

    Incorrect; data augmentation would affect training data diversity, not directly indicated.

  • Overfitting

    Why this is correct

    Correct; high training accuracy with lower validation accuracy suggests overfitting.

  • Model compression

    Why it's wrong here

    Incorrect; model compression reduces model size, not shown here.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.