This course teaches role prompting, constraints, examples, and evaluation so you can get more reliable answers from any AI model.
Includes practical lessons, exercises, and a clear next step after you enroll.
About this course
Curriculum
Lessons are listed in order. Each one has a goal, a walkthrough, practice, and a short check before you continue.
- 01A prompt is a specRequirements, examples, and tests — not poetry.
- 02Patterns: role, few-shot, and chain of stepsUse patterns on purpose, not as superstition.
- 03Delimiter, context packing, and instruction orderPut the instruction where the model will not bury it.
- 04Eval: a tiny suite you rerun after every changeFive to twenty examples beat a vibe check.
- 05Failure modes and repairsRefusal, ramble, schema break, and sycophancy — with a fix for each.
- 06Versioning prompts like codeName, date, owner, and what the last eval said.
- 07Workshop: a complete pass on a real taskCombine the earlier lessons into one working example you can keep.
- 08Quality bar, common mistakes, and a 30-day planLock in a checklist so the skill survives after the course ends.