The Analytics Mindset Behind Effective AI Evals

Hosted by Stella Liu

Wed, Jun 24, 2026

7:00 PM UTC (30 minutes)

Virtual (Zoom)

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163 students

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AI Evals and Analytics Playbook
Stella Liu and Amy Chen
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What you'll learn

Reframe AI evals as an applied data problem

Define behaviors, risks, and decisions instead of just chasing scores.

Use data science thinking to design better evals

Apply analytical skills and build more practical evaluations.

Connect offline evals to real-world product learning

Understand how evals and analytics work together to improve AI systems over time.

Why this topic matters

AI evals can feel like a brand-new discipline, but many of the core skills already exist in data science. Learning how to transfer those skills helps you move beyond surface-level scores and build evals that better reflect product goals, model behavior, and real-world performance.

You'll learn from

Stella Liu

Head of Applied Scientist, AI Evals

Stella Liu is an AI Evaluation practitioner and researcher, specializing in frameworks for large language models and AI-powered products.


Since 2023, she has led real-world AI evaluation projects in EdTech, where she established the first AI product evaluation framework for Higher Education and continues to advance research on the safe and responsible use of AI. Her work combines academic rigor with hands-on product experience, bringing proven evaluation methods into both enterprise and educational contexts.


Earlier in her career, Stella worked at Shopify and Carvana, where she built large-scale data-driven automation systems that powered product innovation and operational efficiency at scale.


Stella also writes an AI Evals newsletter on Substack: https://datasciencexai.substack.com/


Follow Stella on LinkedIn

Previously at

Shopify.com
Carvana
Harvard University
UT Austin
See all products from AI Evals and Analytics

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