Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

CertNexus AIP-210 Exam - Topic 1 Question 60 Discussion

When should the model be retrained in the ML pipeline?
B) Concept drift is detected in the pipeline.
A) A new monitoring component is added.
C) More data become available for the training phase.
D) Some outliers are detected in live data.

CertNexus AIP-210 Exam - Topic 1 Question 60 Discussion

Actual exam question for CertNexus's AIP-210 exam
Question #: 60
Topic #: 1
[All AIP-210 Questions]

When should the model be retrained in the ML pipeline?

Show Suggested Answer Hide Answer
Suggested Answer: B

When concept drift is detected in the pipeline, it means that the model performance has degraded over time due to changes in the underlying data generating process. This requires retraining the model with new data that reflects the current situation and updating the model parameters accordingly. Reference:Use pipeline parameters to retrain models in the designer - Azure Machine Learning | Microsoft Learn,Retraining Model During Deployment: Continuous Training and Continuous Testing


by Kaycee at Jun 26, 2026, 10:51 PM

Limited Time Offer

25%

Off

Get Premium AIP-210 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Louann
3 days ago
A new monitoring component? That’s not a strong reason to retrain.
upvoted 0 times
...
Kristofer
8 days ago
True, but if the model is drifting, it needs retraining first.
upvoted 0 times
...
Marjory
13 days ago
C is also important. More data can improve accuracy.
upvoted 0 times
...
Quiana
18 days ago
Agreed! B is definitely the top choice.
upvoted 0 times
...
Dorethea
23 days ago
I think B is crucial. Concept drift means the model is outdated.
upvoted 0 times
...
Scot
28 days ago
I agree with B, but C is a close second for me!
upvoted 0 times
...
Nieves
1 month ago
Wait, outliers in live data? Shouldn't we just handle those instead?
upvoted 0 times
...
Casie
1 month ago
A new monitoring component? Not sure that warrants retraining.
upvoted 0 times
...
Florinda
1 month ago
I think C is also important. More data can improve accuracy.
upvoted 0 times
...
Tran
2 months ago
Definitely B! Concept drift means the model needs an update.
upvoted 0 times
...
Latia
2 months ago
Adding a new monitoring component seems like it wouldn’t necessarily require retraining, so I’m leaning towards B or C.
upvoted 0 times
...
Phung
2 months ago
I feel like we had a practice question about outliers, but I can't recall if that means we should retrain.
upvoted 0 times
...
Hyun
2 months ago
I’m not entirely sure, but I think retraining is also important when new data comes in, like option C.
upvoted 0 times
...
Janine
2 months ago
I remember we discussed concept drift in class, so I think option B might be the right answer.
upvoted 0 times
...

Save Cancel