AI Associate Data for AI Practice Question
A multinational corporation uses Salesforce AI to analyze customer feedback across multiple languages. They have 10,000 English reviews, 2,000 Spanish reviews, and 500 French reviews. The sentiment model performs well on English (F1=0.85) but poorly on French (F1=0.40). The data scientist wants to improve French sentiment performance without collecting new data. What should they do?
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
✓
Apply data augmentation to the French reviews using back-translation (translate to another language and back) to create more training examples.
Data augmentation techniques like back-translation generate synthetic French samples, effectively increasing the minority language's representation and helping the model learn better.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Translate all French reviews to English and train only on English data.
Why it's wrong here
Translating loses language-specific nuances; the model may not generalize to native French customer feedback.
- ✗
Use a multilingual pre-trained model without any additional French data.
Why it's wrong here
The model still has limited French examples; augmentation is more effective to address the specific data sparsity.
- ✗
Remove French data and use only English and Spanish to avoid imbalance.
Why it's wrong here
Removing French data abandons the goal of analyzing French feedback; it does not improve performance for French.
- ✓
Apply data augmentation to the French reviews using back-translation (translate to another language and back) to create more training examples.
Why this is correct
Back-translation generates realistic paraphrases, augmenting the French dataset and improving model performance.
Go deeper
Related to this question
About these practice questions
Courseiva writes every AI Associate question from scratch — 753 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI Associate practice question is part of Courseiva's free Salesforce 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 AI Associate exam.