مواد پر جائیں

Education technology

حوالہ جاتی نمونہ

Fifty thousand courses, two hundred providers, one schema

A course discovery engine that normalises 200+ provider APIs into one canonical schema and ranks them with a scoring model tuned against real click behaviour.

50K+courses indexed

ایک نظر میں

مدت
52 ہفتے
ٹیم کا حجم
5 افراد
معاہدے کی نوعیت
نئی تعمیر
پروجیکٹ کی قسم
ڈیٹا پلیٹ فارم
شعبہ
تعلیم

صورتحال

مسئلہ

A Coursera specialization and a Udemy course are structurally different products, and 200+ providers meant 200+ inconsistent schemas updating on their own cadences. On top of normalising all of that, search had to feel like Google.

ہم نے کیا کیا

A plugin ingestion pipeline so each provider's weirdness stays contained, then a canonical schema and a scoring model that learns from behaviour.

وہ فیصلے جو اہم تھے

  • One adapter per provider, one schema behind them

    Provider-specific adapters own auth, rate limiting and normalisation; everything downstream sees a canonical course with provider quirks in JSONB. Deduplication happens by fingerprint before indexing.

  • BM25 as a starting point, not an answer

    Custom Elasticsearch scoring layering rating, freshness, provider reputation and enrolment velocity on top of BM25 — with the weights set by A/B test rather than intuition.

کیا بدلا

courses indexed
50K+courses indexed
monthly active learners
500K+monthly active learners
search p95 latency
94mssearch p95 latency
recommendation click-through
3.2xrecommendation click-through
  • 50K+ — with under 0.1% normalisation errors
  • 3.2x — after A/B tested scoring weights

50,000+ courses from 200+ providers at under 0.1% normalisation error, 94ms p95 search, and a 3.2x lift in recommendation click-through.

استعمال شدہ خدمات

  • Plugin ingestion pipeline with 200+ provider adapters
  • Canonical course schema with fingerprint deduplication
  • Custom Elasticsearch scoring model with A/B tested weights

ہم کیا مختلف کرتے

ہر منصوبے میں ایسی ایک بات ہوتی ہے۔ اسے شائع کرنا ہی اصل نکتہ ہے — جس کیس اسٹڈی میں کوئی پچھتاوا نہ ہو وہ ثبوت نہیں، تشہیر ہے۔

Relevance is a product problem before it is an infrastructure one. Instrumenting what people actually clicked turned out to be worth more than any further tuning of the retrieval layer.

استعمال شدہ خدمات

مزید کام

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