Python Institute PCAI glossary of AI workflows, datasets, models, evaluation, and deployment terms.
Use this glossary when Certified Associate Python Programmer for AI (PCAI) terms start to blur together. The goal is practical recognition, not encyclopedia coverage.
| Term | Exam meaning |
|---|---|
| Inference | Using a trained model to produce predictions or outputs. |
| Prompt | Instruction or input sent to a generative model. |
| Embedding | Vector representation used for similarity and retrieval. |
| Bias | Systematic unfairness or skew in data, model behavior, or outputs. |
| Evaluation metric | Measure used to judge model or output quality. |
| Human oversight | Human review or control over AI-assisted decisions and outputs. |
| Pair | How to separate them |
|---|---|
| Python foundations for AI vs AI and ML concepts | Ask which layer the scenario is testing, then match the answer to that layer only. |
| Control vs evidence | A control changes behavior; evidence proves behavior or supports investigation. |
| Managed service vs custom build | Managed services win for lower operational effort unless the requirement needs unsupported customization. |
| Prevention vs detection | Prevention blocks or reduces a bad event; detection finds or reports that it happened. |
Do not memorize terms in isolation. For each term, write one scenario where it is the best answer, one scenario where it is a distractor, and one signal that proves it worked.