Merge pull request #2053 from qdrant/course/multi-vector-search

Course: multi vector search

qdrant-landing/content/course/essentials/day-2/collection-tuning-demo.md

@@ -2,6 +2,7 @@
 title: "Demo: HNSW Performance Tuning"
 description: Tune Qdrant’s HNSW index for speed and precision. Optimize bulk uploads, test filters, and benchmark performance on a real 100K OpenAI embedding dataset. 
 weight: 4
+isLesson: true
 ---
 
 {{< date >}} Day 2 {{< /date >}}

qdrant-landing/content/course/essentials/day-2/filterable-hnsw.md

@@ -2,6 +2,7 @@
 title: "Combining Vector Search and Filtering"
 description: Learn how Qdrant combines HNSW vector search with payload filtering. Understand Filterable HNSW, query planning, and payload indexing for accurate, high-performance retrieval.
 weight: 3
+isLesson: true
 ---
 
 {{< date >}} Day 2 {{< /date >}}

qdrant-landing/content/course/essentials/day-2/pitstop-project.md

@@ -2,6 +2,7 @@
 title: "Project: HNSW Performance Benchmarking"
 description: Optimize vector search with Qdrant. Test multiple HNSW configurations, time uploads and queries, and evaluate filtering with and without payload indexes to find the best settings for your domain.
 weight: 5
+isLesson: true
 ---
 
 {{< date >}} Day 2 {{< /date >}}

qdrant-landing/content/course/essentials/day-2/what-is-hnsw.md

@@ -2,6 +2,7 @@
 title: "HNSW Indexing Fundamentals"
 description: Learn how HNSW indexing powers fast, scalable vector search in Qdrant. Understand parameters like m, ef_construct, and hnsw_ef to balance recall, speed, and memory efficiency. 
 weight: 2
+isLesson: true
 ---
 
 {{< date >}} Day 2 {{< /date >}}