Python Institute PCEI glossary of AI fundamentals, model usage, and integration terms.
Use this glossary when Certified Entry-Level Python Programmer for AI (PCEI) 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.