Evals 101
Writing evals is a core skill for making AI products that actually work. Evals are our "definition of what good looks like". They are both harder than they seem to get right, and at the same time not rocket science at all - anyone can learn to write evals.
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1. Let's write some evals
Evals intro: set up your accounts
This is what we came for: some hands-on eval writing.
An introduction to evals
What are evals, why do we need them, and why isn't this just QA?
Let's write an eval together
This is the fun part, hands-on writing evals together.
Eval Tips and Common Mistakes
Evals can be tricky, and it's easy to make some very expensive (in terms of quality, end result and cost) mistakes.
Creating Data Sets
There are no evals without data sets. How do we create solid data sets? How many data points are enough? What about synthetic data?
How we define what Good looks like
One reason evals are tricky, is that it can be hard to define what Good looks like when working (as we are) in a team.
What participants say
"This training has provided valuable insights into AI product development methodologies and practical implementation strategies."
— Course Participant
"Highly relevant for our enterprise software organization as we scale AI feature evaluation processes."
— Course Participant
"The evaluation framework training has been instrumental in establishing our AI quality processes."
— Course Participant