UniBasel DS Planner

Unofficial University of Basel MSc Data Science curriculum planner.

Short handle: BaselCal (baselcal.vercel.app). The longer name is for search — people looking for Uni Basel, MSc Data Science, ECTS, or Vorlesungsverzeichnis.

Plan four semesters, check official 2026 credit rules, spot timetable clashes, and export ICS / JSON. This is not an official University of Basel tool. Always verify CP rules, module membership, and offerings in the Vorlesungsverzeichnis before you enrol.

Live demo: baselcal.vercel.app

The public demo is a sandbox. Anyone can drag courses, load the example outline, and export a plan. Owner login (no signup) unlocks a private overlay stored in Vercel env vars — that JSON is not shipped in the client bundle.

Board with example outline	Timetable

Course discovery	Owner login

Refresh screenshots with DOCS_SHOTS=1 npx playwright test tests/docs-shots.spec.ts.

Quick start

npm install
npm run dev

Dev server: http://localhost:5179

The board starts empty. Drag courses from the catalog, or click Load example outline for a sample 120 CP Master’s plan (no admission / Auflagen courses).

Your personal details stay local

Admission conditions (Auflagen), your real plan, and an optional home pin are not part of the public default.

1. Copy the example config:

   cp config/student.example.json config/student.local.json

2. Edit config/student.local.json:

   • admissionTarget — CP from your Zulassungsbescheid (0 if none)
   • seedPlan — true to fill the board on first visit
   • plan / allocations — course IDs per semester
   • home — optional map pin (lat / lng); leave null to set it in the browser

3. Restart npm run dev. The file is gitignored.

On Vercel, keep STUDENT_CONFIG as a server env var (used only by /api/unlock). Also set PLANNER_USER and PLANNER_PASSWORD. Do not commit them. Public builds never bake that JSON into JavaScript.

You can also change Auflagen CP in the header at any time; that value is stored only in this browser.

Accuracy checks

npm run validate               # catalog CP rules + example outline + time/room vs VV snapshot
npm run validate:details       # title, CP, times, rooms vs saved VV snapshots
npm run validate:details:live  # same checks against live Vorlesungsverzeichnis
npm run validate:details:plan  # only example outline + local student plan
npm run audit:modules          # refresh the Fall 2026 module-tree snapshot
npm run refresh:catalog        # scrape every catalog VV page and apply times/rooms
npm run audit:catalog          # scrape every catalog VV page, snapshot only
npm test
npm run build

Degree rules

Official MSc Data Science 2026 targets (see degree_rules.json):

Bucket	Rule
Mathematical Foundations	min 18 CP
Machine Learning Foundations	min 18 CP
Systems Foundations	min 18 CP
Foundations combined	min 64 CP
Electives in Data Science	exactly 20 CP
Thesis block	exactly 36 CP
Master's total	exactly 120 CP
Admission (Auflagen)	your letter (default 0)

Grand total = 120 + admission. Exact buckets fail on overshoot.

Docs

• CONTRIBUTING.md
• DATA.md — catalog and VV sources
• agent.md — domain rules for contributors

License

MIT