AI Output Evaluation and Quality Assurance

Build representative test sets, score material errors and decide whether an AI workflow is ready for its stated use.

What you will build

An evaluation dataset specification, rubric and release decision.

Before you start: Talent Engineering Fundamentals, or equivalent recruitment experience.

74 min estimated, including practice. 4 written lessons.

What you will learn

• Define the evaluation question
• Build a representative and challenging case set
• Score outputs with an auditable rubric
• Make a release and regression decision

Course lessons

1. Define the evaluation question
2. Build a representative and challenging case set
3. Score outputs with an auditable rubric
4. Make a release and regression decision

Complete the lessons and pass the five-question knowledge assessment at 80% to earn a free course certificate. Exercises are self-directed, not independently graded.