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MLA-C01 Practice Question: Using SageMaker to train a neural network for…
A company is using SageMaker to train a neural network for image classification. The training job is taking too long. The team wants to reduce training time without sacrificing model accuracy. Which approach should they recommend?
⚠ Common exam trap
AWS often tests the misconception that any change to hyperparameters or architecture can reduce training time without side effects, but the trap here is that candidates confuse 'reducing training time' with 'improving convergence speed'—only hardware acceleration (GPU) directly reduces wall-clock time without risking accuracy degradation.
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
✓
Use a GPU-based instance such as ml.p3.2xlarge
GPU-based instances like ml.p3.2xlarge are specifically designed for parallel processing of matrix operations, which are fundamental to neural network training. By offloading compute-intensive tensor operations to GPU cores, training time can be significantly reduced without altering the model architecture or data, thus preserving accuracy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the batch size to the maximum possible
Why it's wrong here
Very large batch sizes can degrade model accuracy and may not fit in memory.
- ✓
Use a GPU-based instance such as ml.p3.2xlarge
Why this is correct
GPUs accelerate matrix operations in neural networks, reducing training time.
- ✗
Use a learning rate scheduler that reduces the learning rate over time
Why it's wrong here
Schedulers help convergence but do not directly reduce training time.
- ✗
Add more convolutional layers to the model
Why it's wrong here
Adding layers increases computation, slowing training.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-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 MLA-C01 exam.