AI Associate AI Fundamentals Practice Question
A data analyst is preparing data for a machine learning model. They notice that many records have missing values for the 'industry' field. What is the best first step?
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
✓
Replace missing values with a placeholder or impute them
Data quality is critical. Missing values must be handled (imputed or removed) to avoid garbage-in-garbage-out.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Delete all records with missing values
Why it's wrong here
Deleting may remove valuable data; imputation is often better.
- ✓
Replace missing values with a placeholder or impute them
Why this is correct
Correct. Imputation or placeholder ensures data completeness.
- ✗
Ignore the missing values and train the model as is
Why it's wrong here
Most models cannot handle missing values; ignoring leads to errors.
- ✗
Use a model that automatically handles missing data
Why it's wrong here
While some models handle missing data, it's not a best practice; cleaning is recommended.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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