AI0-001 AI Models and Data Engineering Practice Question
A team is developing a natural language processing model to classify customer feedback. The dataset contains text in multiple languages. Which THREE preprocessing steps are essential to ensure the model performs well across all languages?
⚠ Common exam trap
CompTIA often tests the distinction between preprocessing steps (like lowercasing, tokenization, stop word removal) and feature engineering techniques (like one-hot encoding), leading candidates to mistakenly include one-hot encoding as a preprocessing step when it is actually a vectorization method applied after preprocessing.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Lowercasing
Lowercasing is essential because it normalizes text across languages by converting all characters to the same case, reducing vocabulary size and ensuring that words like 'Good' and 'good' are treated identically. This prevents the model from learning separate representations for case variations, which is critical for multilingual datasets where case usage may differ (e.g., German capitalizes nouns). Without lowercasing, the model's performance degrades due to sparsity and increased feature space.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
One-hot encoding
Why it's wrong here
One-hot encoding is a representation step, not a preprocessing step; also ignores relationships between words.
- ✓
Lowercasing
Why this is correct
Lowercasing reduces vocabulary size and helps generalize across different cases.
- ✓
Tokenization
Why this is correct
Tokenization is fundamental for breaking text into units for further processing.
- ✗
Stemming
Why it's wrong here
Stemming can be language-specific and may not work well for all languages.
- ✓
Removing stop words
Why this is correct
Stop words are common across languages and often do not contribute to classification.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.