Practice exams for Generative AI Leader

50 questions · 90 min

  • Google Cloud's gen AI offerings 18 questions
  • Fundamentals of gen AI 15 questions
  • Techniques to improve gen AI model output 10 questions
  • Business strategies for a successful gen AI solution 7 questions
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How to prepare for Generative AI Leader with InfraPrep

The 50 questions cover 4 domains: Google Cloud's gen AI offerings, Fundamentals of gen AI, Techniques to improve gen AI model output, Business strategies for a successful gen AI solution. 25 of them are free, without an account.

Study mode

Answer at your pace: each answer is corrected straight away, with an explanation and the link to the documentation it relies on.

Exam mode

A timed exam of 90 minutes, with a question map to flag and come back to questions before you submit.

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Your score is broken down by domain, so you know what to review first.

Original questions

Every question is written from the public documentation, never copied from the exam. You can contest an answer from study mode.

Sample question

Fundamentals of gen AI

A retail chain has years of raw purchase records with no categories or tags attached. The marketing director wants to discover groups of shoppers who tend to buy related products, without deciding the groups in advance. Which machine learning approach fits this goal?

  1. Unsupervised learning, because the model finds patterns in data that carries no labels
  2. Reinforcement learning, because the model is rewarded each time a shopper buys a product
  3. Supervised learning, because the model predicts a known label for each shopper
  4. Supervised learning, because the model can train on a small sample of the records
Show the answer and the explanation

Correct answer: A

Unsupervised learning works on unlabeled data and is suited to discovering new patterns and groupings, such as buyer groups that purchase related products together (customer segmentation).

Source: official documentation

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