PDE Preparing and Using Data for Analysis Practice Question
You want to train a custom TensorFlow model on Vertex AI using a managed Jupyter notebook environment. Which service should you use?
⚠ Common exam trap
PDE often tests the rebranding of AI Platform Notebooks to Vertex AI Workbench; candidates may pick the outdated name or confuse the notebook environment with the training service.
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
✓
Vertex AI Workbench
Vertex AI Workbench is Google Cloud's managed Jupyter notebook environment integrated with Vertex AI, allowing you to develop and train custom TensorFlow models directly. It provides pre-built containers, GPU support, and seamless integration with Vertex AI Training and Pipelines.
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 this is correct
Vertex AI Workbench provides managed Jupyter notebook instances with native integration into Vertex AI training, letting you author and launch custom TensorFlow training jobs from the same environment. It satisfies the managed notebook constraint without provisioning or patching your own compute.
- ✗
Cloud Datalab
Why it's wrong here
Cloud Datalab is a deprecated, separately deployed interactive analysis tool, not a Vertex AI managed notebook service. It is tempting because it offered Jupyter-based notebooks for data exploration and model development, and would have suited ad-hoc analysis before Vertex AI Workbench replaced it.
- ✗
Vertex AI Training
Why it's wrong here
Vertex AI Training runs packaged training jobs on managed compute; it provides no Jupyter notebook interface for interactive development. It is tempting because it does execute custom TensorFlow training on Vertex AI, and would be correct for submitting a containerised training application rather than authoring code in a notebook.
- ✗
AI Platform Notebooks
Why it's wrong here
AI Platform Notebooks is the previous-generation managed notebook product, superseded by Vertex AI Workbench, so it does not satisfy a Vertex AI managed notebook requirement. It is tempting because it genuinely provided managed Jupyter environments for TensorFlow development, and would have been correct before Vertex AI consolidated these services.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PDE 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 PDE exam.