Section 1 - Instruction

You now understand how different AI companies name their models and what each tier represents. Let's practice matching the right model to real data analytics needs.

Engagement Message

Are you ready to become a data-driven AI matchmaker?

Section 2 - Practice

Type

Multiple Choice

Practice Question

Your data team needs to generate daily summaries from 1,000 customer feedback records. Budget is tight and speed matters. Which model would you choose?

A. OpenAI's o3 for maximum intelligence B. Claude Opus for best reasoning C. GPT-4o Mini for speed and cost-efficiency D. Gemini Ultra for complex analysis

Suggested Answers

  • A
  • B
  • C - Correct
  • D
Section 3 - Practice

Type

Sort Into Boxes

Practice Question

Sort these data analytics scenarios into the correct model category:

Labels

  • First Box Label: Fast & Light Models
  • Second Box Label: Powerful Reasoning Models

First Box Items

  • Data cleaning scripts
  • Quick report generation
  • Simple trend summaries

Second Box Items

  • Statistical modeling
  • Complex data correlation
  • Predictive analytics
Section 4 - Practice

Type

Swipe Left or Right

Practice Question

Match each data analytics need with the most suitable model tier by swiping left or right:

Labels

  • Left Label: Balanced Models (Sonnet/Pro/GPT-4)
  • Right Label: Light Models (Haiku/Flash/Mini)
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