Cohort 3

Accessibility Technical Manager

Jules Trapp

Product managers who drive strategy, development, and launch of products.

Engineers and engineering leaders who build, deploy, and scale software systems.

Data scientists who apply statistical and ML techniques to extract insights from data.

Measuring and evaluating AI model performance, quality, and reliability for production use cases.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Using data and metrics to measure performance, run experiments, and inform decisions.

Learn how to evaluate, ship, and monitor GenAI products that perform reliably in production.

Head of AI Applied Science

Shopify

Carvana

Harvard University

Stella Liu

Cofounder, AI Evals & Analytics

System1

Uptake

Seasalt.ai

UCLA

University of Washington

Amy Chen

Cofounder at AI Evals & Analytics

AI Evals Certification: Master Building Reliable AI

AI Evals and Analytics

<h3>Why I enrolled</h3>
<ol class="list-decimal ml-8"><li><p class="p2-tall">Learn methodologies for conducting AI evals.</p></li><li><p class="p2-tall">Learn how output from AI evals can be made actionable in design and development decisions.</p></li></ol>
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<h3>What I’ll apply</h3>
<p class="p2-tall">Will leverage the qualitative and quantitative evaluation techniques.</p>
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Certificate

Learn more about this course