Course · 5 chapters
LLM Evaluation
Build runnable LLM evals you can trust: golden datasets, deterministic scorers, calibrated LLM judges, Inspect AI suites, and CI gates. 5 chapters, advanced, for engineers.
What you'll be able to do
- Build a runnable LLM eval from scratch
- Design judge rubrics that resist bias
- Calibrate LLM judges against humans
- Run eval suites with Inspect AI
- Gate bad merges with CI evals
- Set thresholds that survive flaky judges
What's inside
- 1Advanced Evals & LLM Judges: Start Here
A 12-minute orientation to the Advanced Evals skill path — judges, suites, and gates: the three layers that turn eval-by-vibes into a discipline that ships
- 2Eval Foundations: Your First LLM Eval in 30 Minutes
Stop checking outputs by vibes — build a runnable eval with a golden dataset, deterministic scorer, and LLM judge, and read the result like an engineer
- 3LLM-as-Judge: Rubrics, Bias, and Reliability
Design judges that survive CALM biases, calibrate against humans, and earn a place in your CI gate
- 4Inspect AI: Production Eval Suites at Scale
Author, run, and visualize frontier-grade eval suites with UK AISI's open-source framework
- 5Eval Gating in CI: Blocking Bad Merges
Wire per-PR evals into GitHub Actions, pick thresholds that survive flakiness, and decide when a gate belongs on main
Frequently asked questions
- What will I learn in this LLM evaluation course?
- You build evaluation across three layers: a first runnable eval with a golden dataset and scorer, reliable LLM-as-judge rubrics calibrated against human ratings, and eval suites wired into CI as a merge gate. The path uses UK AISI's open-source Inspect AI framework and GitHub Actions.
- Who is this course for?
- It is for engineers building production AI features who need to test LLM outputs rigorously instead of checking them by vibes. The level is advanced, with a focus on software engineering and AI reliability.
- Do I need to code to take this course?
- Yes. This is a hands-on engineering path that involves writing eval scripts, configuring the Inspect AI framework, and setting up GitHub Actions workflows, so comfort with code and CI is expected.
- How long is the course and is there a certificate?
- The path has 5 chapters totaling about 100 minutes, starting with a 12-minute orientation. On completion you earn an AI Academy by Anthropos certificate.
- Is this course free?
- No, this is a paid skill path included with an AI Academy by Anthropos subscription.
Earn a certificate
Complete all chapters to receive your certificate of completion.