Courseiva
Fundamentals of AI and MLeasyMultiple ChoiceObjective-mapped

AIF-C01 Fundamentals of AI and ML Practice Question

Exhibit

{
  "TrainingJobName": "my-training-job-1",
  "TrainingJobStatus": "Failed",
  "FailureReason": "AlgorithmError: OutOfMemoryError: CUDA out of memory. Tried to allocate 4.00 GiB (GPU 0; 8.00 GiB total capacity; 3.95 GiB already allocated; 2.50 GiB free; 4.00 GiB reserved in total by PyTorch)"
}

Refer to the exhibit. A data scientist ran a training job on Amazon SageMaker. The job failed with the error shown. What is the most likely cause?

⚠ Common exam trap

AWS often tests the distinction between infrastructure errors (S3, IAM) and runtime errors (CUDA memory), where candidates mistakenly attribute a GPU memory error to a misconfiguration in data access or code syntax.

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

The batch size is too large for the instance's GPU memory

The error message indicates a CUDA out-of-memory error, which occurs when the GPU memory is insufficient for the requested batch size. Option D is correct because increasing the batch size beyond the GPU's memory capacity causes the training job to fail with this specific error.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • The S3 input path is incorrect

    Why it's wrong here

    An incorrect S3 path would result in a 'NoSuchKey' or 'AccessDenied' error.

  • The IAM role does not have permission to access S3

    Why it's wrong here

    Permission errors would appear as 'AccessDenied' before training starts.

  • The training code has a syntax error

    Why it's wrong here

    Syntax errors would produce a different error message (e.g., NameError, SyntaxError).

  • The batch size is too large for the instance's GPU memory

    Why this is correct

    The error shows CUDA out of memory, typically due to batch size or model size exceeding GPU memory.

About these practice questions

One of 619 original AIF-C01 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

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.