1. Question 1

Which option is best when a business wants to code their own ML environment, training, and deployment?

• ✅ Custom training

• ❌ Pre-trained APIs

• ❌ AutoML

• ❌ BigQuery ML

Explanation:
Custom training gives full control over coding, environment setup, and deployment.

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2. Question 2

BigQuery ML lets users…

• ✅ Build and evaluate machine learning models in BigQuery using SQL.

• ❌ Build ML models in Python/Java

• ❌ Export small amounts of data

• ❌ Connect with a data science team

Explanation:
BigQuery ML enables ML model creation directly using SQL.

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3. Question 3

Retailer wants image-based product search. Which API?

• ❌ Natural Language API

• ❌ Video Intelligence API

• ✅ Vision API

• ❌ Speech-to-Text API

Explanation:
Vision API analyzes images, detects objects, and supports image search.

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4. Question 4

Media company wants AI-based content moderation. Which API?

• ❌ Vision API

• ❌ Natural Language API

• ❌ Speech-to-Text API

• ✅ Video Intelligence API

Explanation:
Video Intelligence API detects unsafe or inappropriate content in videos.

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5. Question 5

Which Vertex AI feature enables no-code model building via GUI?

• ✅ AutoML

• ❌ MLOps

• ❌ Custom training

• ❌ Managed ML environment

Explanation:
AutoML provides a GUI-based, no-code ML model training environment.

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6. Question 6

Google’s ASIC chip for ML workloads:

• ❌ CPU

• ❌ VPU

• ✅ TPU (Tensor Processing Unit)

• ❌ GPU

Explanation:
TPUs are designed by Google to accelerate ML model training/inference.

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7. Question 7

Which Google Cloud AI solution improves customer service?

• ❌ Discovery AI for Retail

• ✅ Contact Center AI

• ❌ Document AI

• ❌ Cloud Talent Solution

Explanation:
Contact Center AI provides AI-powered virtual agents and customer support tools.

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8. Question 8

Which Google solution automates document processing?

• ❌ Contact Center AI

• ❌ Discovery AI for Retail

• ✅ Document AI

• ❌ Cloud Talent Solution

Explanation:
Document AI extracts structured data from documents using ML.

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🧾 Summary Table

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