Overview
An online practice site for the iPAS certifications run by Taiwan’s Ministry of Economic Affairs, now covering two certifications, seven subjects and 1,972 questions: AI Application Planner at Associate and Intermediate level, plus AIoT Application Engineer at Associate level (IoT track).
Core experience: built on the official past exam papers, it offers three modes — Mock Exam, Drill Practice and New Bank Practice — and uses per-option analyses, a mistake notebook and per-topic statistics to create a repeatable learning loop.
Navigation is layered as certification → level → subject → mode, keeping the two certifications’ banks completely separate rather than mixed together.
Subjects Covered
| Certification | Level | Code | Subject | Exam Time | Mock Exam |
|---|---|---|---|---|---|
| AI Application Planner | Associate | Subject 1 | Foundations of Artificial Intelligence | 75 min | ✅ |
| AI Application Planner | Associate | Subject 2 | Generative AI Applications & Planning | 75 min | ✅ |
| AI Application Planner | Intermediate | Subject 1 | AI Technology Application & Planning | 90 min | ✅ |
| AI Application Planner | Intermediate | Subject 2 | Big Data Processing, Analysis & Application | 90 min | ✅ |
| AI Application Planner | Intermediate | Subject 3 | Machine Learning Technology & Application | 90 min | ✅ |
| AIoT Application Engineer | Associate | Paper 1 | Foundations of AIoT | 75 min | — |
| AIoT Application Engineer | Associate | Paper 2 | IoT Systems & Applications | 75 min | — |
The two AIoT subjects have no mock exam yet: the official prospectus states only “100 points per subject, 70 to pass” without publishing the question count or per-question weighting, so the AI Application Planner’s 50 × 2 rule is not borrowed as a guess.
Question Bank
| Source | Questions | Notes |
|---|---|---|
| Official past exam papers | 779 | Produced from the official PDFs by the parsing pipeline |
| AIoT official study-guide drills | 80 | The official practice set for Paper 1 |
| Supplementary questions | 198 | Cover concepts the past papers miss |
| Topic-classified new bank | 915 | Written per official assessment topic, with per-option analyses |
| Total | 1,972 |
Key Features & Experience
- Mock Exam: 50 randomly drawn questions, timed, scored on submission; 2 points each, 100 total, 70 (35 correct) to pass.
- Drill Practice: choose how many questions, instant correct/incorrect and explanations, untimed; filter by all / wrong / unanswered, jump to a question, resume progress or reset it.
- New Bank Practice: the new bank classified by official assessment topic, where every question carries a per-option analysis explaining why the answer holds and where each of the other three options fails.
- Topic Performance: lists “answered” and “correct” per assessment topic, so weak topics surface instead of hiding behind an overall score.
- Mistake Notebook: wrong answers are collected automatically for focused review.
- Study Topics: exam-prep notes for the 15 AIoT assessment topics with comparison tables, formula blocks and step flows, plus a 120-entry abbreviation reference, a topic index with full-text search, expand/collapse all, a pre-exam cram mode, per-topic jump-into-drill links and read-progress marks.
Sources & Quality Controls
- Transparent bank provenance: the official PDFs stay in a private, un-versioned directory;
pdftotextconverts them to markdown andnpm run parse:papersproduces the committed JSON. Because the output is versioned, re-running the parser and checkinggit diff --exit-codeis a ready-made regression test. - Hand-written layer kept separate from machine output: explanations and per-option analyses live in their own hand-written layer, so fixes survive a re-parse. Reading the official files question by question also turned up three defects in the official PDFs themselves (a question whose options were replaced by explanation text, an answer contradicting its own reasoning, and an explanation answering a different question) — all fixed and tracked in
docs/coverage/bank-defects.md. - The new bank is LLM-authored: the topic-classified questions were written by an LLM with authoring metadata attached and still await human fact-checking; the bank files and project docs say so plainly. The authoring policy sets floors for cognitive level and cross-topic coverage, written into tests as a contract so regressions are blocked.
- CI tests before it builds: GitHub Actions runs the full suite ahead of the build, so the guards on bank integrity, explanation coverage, figure transcription, simplified characters and topic quotas actually gate the deploy.
Tech Stack
TypeScript · Vite · Vitest · GitHub Actions · GitHub Pages
Status
✅ Live - Fully open source and usable directly via GitHub Pages.