The answer is to use SageMaker Managed Spot Training to reduce training costs and to leverage incremental training when updating models with new data. Incremental training in SageMaker is a best practice because it allows you to continue training an existing model on fresh data that shares the same schema and feature space, avoiding the need to retrain from scratch. This preserves previously learned patterns while saving significant time and compute resources, making it ideal for steady streams of similar data. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this concept tests your understanding of cost optimization and efficient model iteration—common traps include confusing incremental training with full retraining or forgetting that Spot Training requires checkpointing for fault tolerance. A helpful memory tip: think of incremental training as "adding a new chapter to a book" rather than rewriting the entire book, and remember that Spot Training is like "booking a discounted flight" that might get bumped, so always pack your checkpoints.
MLS-C01 Modeling Practice Question
This MLS-C01 practice question tests your understanding of modeling. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO options are best practices for training machine learning models using SageMaker? (Choose TWO.)
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use incremental training when you have new data that is similar to the original training data
Option B is correct because SageMaker's incremental training allows you to continue training an existing model with new data that shares the same schema and feature space, without retraining from scratch. This is a best practice when you have a steady stream of similar data, as it saves time and compute resources while preserving previously learned patterns.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Train the final model on the combined training and test sets to maximize data usage
Why it's wrong here
The test set should be kept separate to evaluate generalization.
✓
Use incremental training when you have new data that is similar to the original training data
Why this is correct
Incremental training saves time by starting from an existing model.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use SageMaker Managed Spot Training to reduce training costs
Why this is correct
Spot instances are cost-effective for fault-tolerant training.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Always use the largest possible instance type to minimize training time
Why it's wrong here
Larger instances may lead to diminishing returns and higher costs.
✗
Always enable checkpointing to save the model after every epoch
Why it's wrong here
Checkpointing is optional and depends on the training needs.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that 'more data is always better' (Option A) or that 'bigger instances are always faster' (Option D), when in reality best practices prioritize data integrity, cost efficiency, and appropriate resource scaling.
Detailed technical explanation
How to think about this question
SageMaker Managed Spot Training (Option C) leverages AWS EC2 Spot Instances, which can be reclaimed with a 2-minute termination notice, to reduce training costs by up to 90%. SageMaker automatically handles checkpointing and resumption when using spot instances, making it a robust cost-saving practice. Incremental training (Option B) works by loading a pre-trained model artifact and continuing gradient descent on new data, which is particularly useful for time-series models or when data arrives in batches.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use incremental training when you have new data that is similar to the original training data — Option B is correct because SageMaker's incremental training allows you to continue training an existing model with new data that shares the same schema and feature space, without retraining from scratch. This is a best practice when you have a steady stream of similar data, as it saves time and compute resources while preserving previously learned patterns.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.
Question Discussion
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