Evaluating AI Systems with OpenAI Evals

About this course

Learn to build reliable AI systems by mastering OpenAI's Evals framework — an open-source tool for rigorously testing large language models. This course takes you beyond casual prompting to the engineering discipline of LLM evaluation, taught through OpenAI's battle-tested approach. If you're serious about deploying AI responsibly, this is where you'll gain the skills to measure what actually matters.

What you'll learn

• Design and write custom evaluation scripts using OpenAI's Evals framework
• Distinguish between different evaluation strategies and choose the right one for your use case
• Measure LLM performance on tasks critical to your product or application
• Automate testing workflows to catch model drift and regressions
• Interpret evaluation results and iterate on prompts or fine-tuning based on data
• Build repeatable benchmarks for comparing model versions and providers
• Apply real-world evaluation patterns used by OpenAI's own teams

Who this is for

You're ready for this course if you've worked with LLMs already and want to move beyond guesswork. Whether you're building AI products, integrating LLMs into business workflows, or conducting AI research, you'll learn the systematic approach to validation that separates production-ready systems from experimental prototypes.

• AI engineers and ML practitioners — gain the evaluation toolkit you'll need to benchmark models and justify architectural choices in real projects.
• Product managers and technical founders — understand how to measure LLM quality objectively, de-risk launches, and make data-driven decisions about model selection.

Prerequisites

Comfort with Python and hands-on experience working with LLMs or language models (via API or local models). You should understand what prompts are and have run at least a few LLM calls before. No formal background in machine learning evaluation required.

Why this matters for Indian learners

India's AI startup ecosystem is growing rapidly, and companies building AI-first products — from SaaS platforms to customer-facing applications — urgently need engineers who can evaluate model quality systematically. Major tech employers like Flipkart, Amazon India, and emerging Indian AI startups increasingly hire for AI engineering roles that demand hands-on evaluation skills. LLM evaluation expertise remains a gap in the Indian market, making this a high-demand, differentiated skill that directly improves your hiring prospects and salary negotiation position.

Frequently asked questions

Is this course really free?

Yes — completely free. The GitHub repository and all course materials are open-source.

How long will it take to complete?

Plan for about 5 hours of focused work. You can move through it in a week at a relaxed pace, or over two weeks if you're working through code examples hands-on (which we recommend).

Will I get a certificate?

This course doesn't offer a formal certificate, but you'll build tangible proof of skill — working evaluation code you can show employers or include in a portfolio.