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Generative AI Leader Practice Question: A financial services firm needs to fine-tune a…

A financial services firm needs to fine-tune a large language model on proprietary financial data. They require data to never leave their VPC and need full audit logging. Which Gemini access method should they use?

⚠ Common exam trap

Many candidates confuse Google AI Studio's free-tier accessibility with enterprise-grade security, overlooking that Vertex AI is the only option with VPC controls and audit logging for fine-tuning proprietary data.

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

Vertex AI is the correct access method because it is the only option that allows fine-tuning of Gemini models within a customer's VPC (Virtual Private Cloud) with full audit logging via Cloud Audit Logs. This ensures proprietary financial data never leaves the secure network boundary, meeting strict compliance and data residency requirements.

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

    Why this is correct

    Vertex AI offers VPC Service Controls, audit logging, and data isolation.

  • ✗

    Google AI Studio

    Why it's wrong here

    Google AI Studio is for prototyping and does not support VPC controls or audit logging.

  • ✗

    Gemini API directly via Cloud Endpoints

    Why it's wrong here

    No VPC or audit capabilities.

  • ✗

    Model Garden in Colab

    Why it's wrong here

    Colab does not provide VPC or audit logging.

About these practice questions

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This Generative AI Leader 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 Generative AI Leader exam.