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PMI CPMAI_v7 Exam - Topic 1 Question 6 Discussion

Actual exam question for PMI's CPMAI_v7 exam
Question #: 6
Topic #: 1
[All CPMAI_v7 Questions]

You are working on the data engineering pipeline for the AI project and you want to make sure to address the creation of pipelines to deal with model iteration. What part of the pipeline best deals with this step?

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Suggested Answer: B

by Peggie at Jun 13, 2025, 10:50 PM

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Keneth
2 months ago
Totally agree with B, it's all about keeping the model fresh!
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Ronnie
2 months ago
Wait, I thought ELT was just for data storage, not iteration?
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Paris
3 months ago
B makes the most sense, but what about C?
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Lorrie
3 months ago
I think A is also important for initial data capture.
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Justa
3 months ago
Definitely B, retraining pipelines are key for model iteration.
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Peggie
3 months ago
I thought the ELT pipeline was more about data transformation rather than model iteration, but I could be mistaken.
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Raina
4 months ago
I’m leaning towards option B, but I vaguely recall something about how data acquisition can also affect the retraining process.
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Ty
4 months ago
I remember a practice question where we discussed how feature engineering impacts model performance, but I feel like retraining is more directly related to iteration.
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Rosalind
4 months ago
I think retraining pipelines are crucial for model iteration, but I'm not entirely sure if that's the only part that matters.
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Xochitl
4 months ago
Retraining Pipelines, for sure. That's the part of the pipeline that's responsible for updating the model as new data comes in or as the requirements change. Gotta stay on top of that model iteration!
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Nu
4 months ago
Okay, let me think this through. The question is asking about the part of the pipeline that deals with model iteration, so that rules out data acquisition and feature engineering. I'm leaning towards the Retraining Pipelines option, but I'll double-check the other choices just to be sure.
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Junita
5 months ago
Hmm, I'm a bit unsure about this one. I know model iteration is important, but I'm not sure if that's the same as the retraining pipeline. Maybe I should think more about the overall data engineering process.
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Art
5 months ago
I think the key here is to focus on the part of the pipeline that deals with model iteration and retraining. That sounds like it would be the Retraining Pipelines option.
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Aleta
7 months ago
Haha, I'd choose D) Retraining Pipelines too. Gotta keep that AI on its toes, you know?
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Dulce
6 months ago
Absolutely, it's important to continuously improve the model with new data.
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Fabiola
6 months ago
Retraining pipelines are crucial for keeping the AI up to date.
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Nakisha
7 months ago
I agree, D) Retraining Pipelines is the way to go. It's the part of the pipeline that keeps your model sharp and up-to-date.
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Juan
8 months ago
Definitely D) Retraining Pipelines. That's where you handle the iterative process of updating your model as new data comes in.
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Stevie
6 months ago
I agree, it's important to continuously update the model with new data.
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Scarlet
7 months ago
D) Retraining Pipelines is crucial for model iteration.
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Sharen
7 months ago
Definitely D) Retraining Pipelines. That's where you handle the iterative process of updating your model as new data comes in.
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Devon
7 months ago
D) Retraining Pipelines
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Rosendo
7 months ago
C) ELT pipeline
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Kimi
7 months ago
B) Data Acquisition / Ingest / Capture
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Shaniqua
7 months ago
A) Feature Engineering
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Oneida
8 months ago
I personally believe that C) ELT pipeline is also important for handling model iteration as it involves extracting, loading, and transforming data.
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Leah
8 months ago
I agree with Glory. Retraining pipelines are crucial for updating the model with new data.
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Glory
8 months ago
I think the best part to deal with model iteration is D) Retraining Pipelines.
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