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Merge pull request #2158 from qdrant/refinements

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Docs and Course Refinements
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kanungle
2026-02-26 00:08:37 -08:00
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qdrant-landing/content/course/essentials/day-1/chunking-strategies.md
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@@ -54,7 +54,7 @@ This is where chunking comes in. The goal is to have chunks
By breaking a document into focused chunks, each chunk gets its own vector that accurately represents a specific idea. This allows the search to be far more precise.
**Example:** Consider a multi-page Document like the [Qdrant Collection Configuration Guide of day 7](/course/essentials/day-7/collection-configuration-guide/) covering everything from HNSW to sharding and quantization.
**Example:** Consider a multi-page Document like the [Qdrant Collection Configuration Guide of Day 7](/course/essentials/day-7/collection-configuration-guide/) covering everything from HNSW to sharding and quantization.
If a user asks: *"What does the m parameter do?"*
qdrant-landing/content/course/essentials/day-1/movie-search-system.md
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@@ -234,7 +234,7 @@ Query: 'alien invasion'
## Step 6: Advanced Features
Note: If you are already familiar Qdrant's filterable HNSW, you will know that effective filtering and grouping often relies on creating a [payload index](/documentation/concepts/indexing/#payload-index) before building HNSW indexes. To keep things simple in this tutorial, we will do a basic search with filters without payload indexes and talk about proper usage of payload indexes on [day 2](/content/course/essentials/day-2/_index.md) of this course.
Note: If you are already familiar Qdrant's filterable HNSW, you will know that effective filtering and grouping often relies on creating a [payload index](/documentation/concepts/indexing/#payload-index) before building HNSW indexes. To keep things simple in this tutorial, we will do a basic search with filters without payload indexes and talk about proper usage of payload indexes on [Day 2](/content/course/essentials/day-2/_index.md) of this course.
### Filtering by Metadata