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Amazon MLA-C01 Exam - Topic 1 Question 14 Discussion

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?
D) Use SageMaker Autopilot to fine-tune an LLM that is deployed by SageMaker JumpStart.
A) Use SageMaker Studio to fine-tune an LLM that is deployed on Amazon EC2 instances.
B) Use SageMaker Autopilot to fine-tune an LLM that is deployed by a custom API endpoint.
C) Use SageMaker Autopilot to fine-tune an LLM that is deployed on Amazon EC2 instances.

Amazon MLA-C01 Exam - Topic 1 Question 14 Discussion

Actual exam question for Amazon's MLA-C01 exam
Question #: 14
Topic #: 1
[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?

Show Suggested Answer Hide Answer
Suggested Answer: D

by Candra at Jan 05, 2026, 05:16 AM

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Kristel
1 month ago
I'm leaning towards B. Custom API endpoints offer flexibility.
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Laurene
1 month ago
I agree, D makes sense. LCNC is key here.
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Cecil
1 month ago
I think option D is the best choice. SageMaker JumpStart simplifies deployment.
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Casie
2 months ago
Not sure about D, seems too easy.
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Paola
2 months ago
Wait, can SageMaker JumpStart really handle LLMs?
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Donette
2 months ago
Definitely going with D, makes the most sense!
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Han
2 months ago
I think C could work too, but not as user-friendly.
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Sabrina
2 months ago
Option D is the best choice for LCNC.
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Renea
3 months ago
I'm just glad I don't have to manually deploy the LLM on EC2 instances. Option D for the win!
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Julio
3 months ago
Haha, I bet the engineers at AWS had a field day coming up with "JumpStart" as a product name. Gotta love the marketing team.
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Jose
3 months ago
Option D is the clear winner. I'm all about that low-code life, baby!
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Keneth
3 months ago
D is the answer. Anything that reduces the amount of code I have to write is a win in my book.
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Leota
4 months ago
Option D is the way to go. Gotta love that low-code no-code approach!
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Leonora
4 months ago
I agree, D seems like the best choice here. Autopilot and JumpStart make it easy to fine-tune and deploy the LLM.
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Rashad
4 months ago
Option D looks good. SageMaker Autopilot and JumpStart seem like a low-code no-code approach.
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Yoko
4 months ago
I feel like Autopilot is the key here, but I’m uncertain if it can work with EC2 instances or if JumpStart is the better choice.
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Elouise
4 months ago
I practiced a similar question where we had to choose between EC2 and JumpStart, but I can't recall the specific benefits of using JumpStart for fine-tuning.
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Micheline
5 months ago
I think option D sounds right because JumpStart is designed for quick deployments, but I’m a bit confused about the LCNC aspect.
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Beula
5 months ago
I remember we discussed SageMaker Autopilot in class, but I'm not sure if it can be used with JumpStart for LLMs.
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An
5 months ago
This is a great question to test our understanding of SageMaker's capabilities. I'm feeling confident I can identify the best solution.
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Natalya
5 months ago
I think I've got a good handle on the key requirements. I'll walk through each option and evaluate how well it meets the criteria.
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Pamella
5 months ago
Option D seems like the most straightforward approach to meet the LCNC requirement. I'll focus on understanding how SageMaker JumpStart works.
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Tina
5 months ago
Hmm, I'm a bit confused by the LCNC requirement. I'll need to make sure I understand what that means for the solution.
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Maybelle
6 months ago
This looks like a tricky one. I'll need to carefully review the options and think through the requirements.
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