This MLA-C01 practice question tests your understanding of ml model development. 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.
A data scientist is building a text classification model using Amazon SageMaker. The dataset is stored as a CSV file in Amazon S3. The scientist wants to use the SageMaker built-in BlazingText algorithm. Which of the following steps are required to prepare the data for training? (Choose TWO.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Convert the CSV file to the format of a single file with one instance per line.
Option C is correct because BlazingText expects input data in a single file where each line represents one training instance. This is a specific requirement of the algorithm's input format, not a general SageMaker practice. The CSV file must be converted to this line-per-instance format for BlazingText to process it correctly.
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.
✗
Convert the text to one-hot encoded vectors.
Why it's wrong here
Not required for BlazingText.
✗
Tokenize and remove stop words from the text.
Why it's wrong here
BlazingText can handle raw text.
✓
Convert the CSV file to the format of a single file with one instance per line.
Why this is correct
BlazingText expects a single file with one instance per line.
Related concept
Read the scenario before looking for a memorised answer.
✗
Upload the data to an Amazon SageMaker notebook instance.
Why it's wrong here
Data can stay in S3.
✓
Ensure each line in the training file contains a single text instance with the label prefixed by '__label__'.
Why this is correct
Required format for BlazingText.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume general NLP preprocessing (like tokenization or stop word removal) is always required, but BlazingText is designed to handle raw text and expects a specific line format, not preprocessed vectors.
Detailed technical explanation
How to think about this question
BlazingText uses a modified Word2Vec or fastText architecture that expects each line to contain a label (prefixed with '__label__') followed by the text tokens. The algorithm automatically tokenizes the input by splitting on whitespace, so no external tokenization is needed. In production, you would typically use SageMaker Processing or a custom script to convert a CSV into this format, ensuring the label column is moved to the front with the '__label__' prefix.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
ML Model Development — This question tests ML Model Development — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Convert the CSV file to the format of a single file with one instance per line. — Option C is correct because BlazingText expects input data in a single file where each line represents one training instance. This is a specific requirement of the algorithm's input format, not a general SageMaker practice. The CSV file must be converted to this line-per-instance format for BlazingText to process it correctly.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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