easyMultiple Select
PMLE Practice Question: A data analyst wants to use low-code ML to…
A data analyst wants to use low-code ML to analyze text data. Which TWO Google Cloud services are appropriate?
⚠ Common exam trap
Many candidates confuse BigQuery ML's sentiment analysis feature (which is SQL-based and not a dedicated low-code service) with a standalone low-code ML service, or mistakenly think Vertex AI Workbench is low-code when it actually requires coding in Python or other languages.
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
✓
Cloud Natural Language API
Cloud Natural Language API is a low-code ML service that provides pre-trained models for analyzing text, including sentiment analysis, entity recognition, and syntax analysis, without requiring custom model training. It is appropriate for a data analyst who wants to quickly extract insights from text data using simple API calls.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Vertex AI Workbench
Why it's wrong here
Wrong: Requires coding, not low-code.
- ✗
Document AI
Why it's wrong here
Wrong: For document processing, not general text analysis.
- ✓
Cloud Natural Language API
Why this is correct
Correct: Pre-trained sentiment and entity analysis via API.
- ✓
AutoML Natural Language
Why this is correct
Correct: No-code text classification and entity extraction.
- ✗
BigQuery ML for sentiment
Why it's wrong here
Wrong: BigQuery ML does not directly support text sentiment models.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.