June Cohort

Principal QA Engineer

Dilshan Fernando

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.

Startup founders building new businesses, from MVP to scale.

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

Evals aren't your product moat. A continuous improvement flywheel is.

AI Founder & Advisor to F500s | Ex-AWS

Amazon Web Services

Microsoft

University of Oxford

Aishwarya Naresh Reganti

Applied AI @ OpenAI Codex | Ex-Google

Google

Databricks

Samsung

Kiriti Badam

Beyond Evals: Designing Improvement Flywheels for AI Products

Kiriti & Aish

<h3>Why I enrolled</h3>
<p class="p2-tall">Understand &amp; implement AI Evals for the AI system/applications</p>
<p></p>

    <h3>A breakthrough moment</h3><p class="p2-tall">My 'aha' moment was when I understood how to prepare an evaluation strategy/process which can apply for any AI product/application.  What i really like is the way of thinking and how to start the design and implement the evals with the problem first mind. </p>

<p></p>
<h3>What I’ll apply</h3>
<p class="p2-tall">Support my company to evaluate the AI native banking OS</p>
<p></p>

Certificate

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