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Amazon Exam MLA-C01 Topic 4 Question 11 Discussion

Actual exam question for Amazon's MLA-C01 exam
Question #: 11
Topic #: 4
[All MLA-C01 Questions]

An ML engineer needs to use Amazon SageMaker to fine-tune a large language model (LLM) for text summarization. The ML engineer must follow a low-code no-code (LCNC) approach.

Which solution will meet these requirements?

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Suggested Answer: D

by Youlanda at Oct 13, 2025, 07:51 PM

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Hayley
2 days ago
I'm a bit confused on the difference between deploying on EC2 instances versus a custom API endpoint. Can someone clarify which one would be considered more "low-code"?
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Dorsey
8 days ago
I think option D is the way to go here. SageMaker Autopilot should handle the fine-tuning of the LLM, and then we can deploy it using SageMaker JumpStart, which sounds like a pretty low-code approach.
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Adelle
13 days ago
I feel like using SageMaker Studio might be too hands-on for a LCNC approach, but I can't quite remember the details.
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Desmond
19 days ago
I practiced a similar question where JumpStart was mentioned, and it seems like a good fit for quick deployment.
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Tesha
24 days ago
I think the low-code aspect points towards using SageMaker Autopilot, but I can't recall if it specifically needs to be deployed on EC2 or JumpStart.
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Lachelle
1 month ago
I remember studying about SageMaker Autopilot, but I'm not sure if it can be used with JumpStart for LLMs.
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