Foundations for AI evaluation work
Essential training for AI evaluation work. Covers how AI writes text, task interfaces, quality standards, automation bias, justification writing and handling patient identifiers.
At a glance
- Duration
- 180 min
- Modules
- 7 (5 lessons)
- Level
- Foundation
- Price
- Free
- Certificate
- On completion
Where every evaluator begins.
Before you score a single AI output, Foundation gives you the shared language and standards the rest of the pathway is built on: what large language models actually do, how RLHF turns expert judgement into safer models, and what separates a high-quality evaluation from a careless one. Finish it and you're ready to calibrate daily.
What you’ll learn.
What large language models are, how they generate text, and why human feedback matters.
Task interfaces, rating mechanics, and what constitutes quality feedback.
Structured rubric evaluation, dimensional scoring, anchoring, consistency and automation bias.
Writing rationales with structured citations, clinical reasoning, and evidence grounding.
Task assignment, turnaround expectations, quality metrics and handling patient identifiers.
Guided exercises across core task types with immediate feedback.
The modules.
7 modules · 180 minutes · work through them at your own pace.
- 01
Understanding AI and LLMs
What large language models are, how they generate text, and why human feedback matters.
Lesson30m - 02
The RLHF workflow
Task interfaces, rating mechanics, and what constitutes quality feedback.
Lesson30m - 03
Quality standards and rubrics
Structured rubric evaluation, dimensional scoring, anchoring, consistency and automation bias.
Lesson30m - 04
Justification writing
Writing rationales with structured citations, clinical reasoning, and evidence grounding.
Lesson30m - 05
Platform mechanics
Task assignment, turnaround expectations, quality metrics and handling patient identifiers.
Lesson15m - 06
Instruction comprehension check
Verify understanding of key concepts before proceeding to practice.
Quiz5m - 07
Practice tasks
Guided exercises across core task types with immediate feedback.
Practice45m
A look inside.
Understanding AI and large language models Learning outcomes By the end of this module you should be able to: 1. Describe how a large language model produces text, and why a fluent answer is not the same as a correct one 2. Recognise five common failure modes in AI-written healthcare content 3.
Register free to access the full course content.
The rest of the pathway.
Ready to begin?
Register free, complete the course, and move on to the calibration that puts a reliability score on your profile.
entertheloopClinicians powering AI alignment, training & safety.Verified against
entertheloopClinicians powering AI alignment, training & safety.