feat: personalized course recommendation engine

[BABAT-CODE]

Summary

Adds a hybrid recommendation engine that surfaces personalized course suggestions for each
user.

Changes

• RecommendationEngineService — orchestrates collaborative + content-based signals into a
  ranked list
• CollaborativeFilteringService — user-based Jaccard similarity over enrollment co-occurrence
• ContentBasedFilteringService — category preference profile + price proximity scoring
• RecommendationsController — GET /recommendations/:userId?limit=10
• Redis caching (5 min TTL) to meet the <100ms performance target
• Cold-start fallback to recently published courses for new users

Endpoint

GET /recommendations/:userId?limit=10

Testing

• 9 unit tests covering engine, collaborative filter, and content-based filter
• All tests passing

Acceptance Criteria

• Recommendation engine created
• Collaborative filtering
• Content-based filtering
• Performance optimized (<100ms via Redis cache)

close #568

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