Cohort 1

Senior Data Scientist

Ning Hua

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>
<ul class="list-disc ml-8"><li><p class="p2-tall">Learn practical evaluation frameworks and methodologies for LLM-based products.</p></li><li><p class="p2-tall">Develop internal AI evaluation capabilities within my organisation.</p></li><li><p class="p2-tall">Create an evaluation playbook and guidelines for my current AI projects, and put them into practice.</p></li></ul>
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<h3>What I’ll apply</h3>
<p class="p2-tall">Apply quantitative evaluation in our dev phase.</p>
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Certificate

Learn more about this course