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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 All Questions

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Exam AWS Certified Machine Learning Engineer - Associate MLA-C01 topic 1 question 93 discussion

Exam question from Amazon's AWS Certified Machine Learning Engineer - Associate MLA-C01
Question #: 93
Topic #: 1
[All AWS Certified Machine Learning Engineer - Associate MLA-C01 Questions]

A company runs training jobs on Amazon SageMaker by using a compute optimized instance. Demand for training runs will remain constant for the next 55 weeks. The instance needs to run for 35 hours each week. The company needs to reduce its model training costs.

Which solution will meet these requirements?

  • A. Use a serverless endpoint with a provisioned concurrency of 35 hours for each week. Run the training on the endpoint.
  • B. Use SageMaker Edge Manager for the training. Specify the instance requirement in the edge device configuration. Run the training.
  • C. Use the heterogeneous cluster feature of SageMaker Training. Configure the instance_type, instance_count, and instance_groups arguments to run training jobs.
  • D. Opt in to a SageMaker Savings Plan with a 1-year term and an All Upfront payment. Run a SageMaker Training job on the instance.
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Suggested Answer: D 🗳️
by chris_spencer at March 11, 2025, 2 p.m.
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AgboolaKun
2 months, 1 week ago
Selected Answer: D
The correct answer is D: Since the company needs to run training jobs on Amazon SageMaker for 35 hours each week over the next 55 weeks and wants to reduce model training costs, they should opt in to a SageMaker Savings Plan with a 1-year term and make an All Upfront payment. Then, they can run their SageMaker Training jobs on the compute optimized instance. This solution provides the maximum possible discount (up to 64% compared to on-demand pricing) while maintaining the needed computing capacity for their consistent, predictable workload.
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chris_spencer
3 months, 2 weeks ago
Selected Answer: D
SageMaker Savings Plans offer a discount for long-term use of SageMaker instances.
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