lrnitFor ML engineers

Learn LLM evaluation in a course built only for you — and actually retain it.

The discipline that separates AI products that improve from ones that quietly rot: golden sets, LLM-as-judge, regression gates, and eval-driven iteration.

Free to start · no account needed

Built around your goal — not a catalog

What your course could open with

lrnit interviews you first — what you know, why you’re learning, how you think — then generates every lesson for that. Sample lessons from a course like yours:

01Why accuracy is the wrong metric: defining quality for generative outputs
02Golden sets: building your first hundred labeled examples
03LLM-as-judge: when it works, when it lies, and how to calibrate it
04Regression gates in CI: catching quality drops before users do
…and the rest is generated for you: your gaps, your pace, your job.

Measured, not watched

By the end, you’ll be able to

Build an eval suite for any generative feature
Calibrate automated judges against human judgment
Wire quality regression checks into your deploy pipeline

Every lesson ends in assessment. Mastery is tracked per concept with spaced review, and the course adapts to what you actually retain — finishing means a timed final exam and a verifiable certificate, not a completion badge.

“It felt like the course already knew what I did for a living.”

Early lrnit learner

Your version of this course doesn’t exist yet.

Free to start · no account needed