mirror of
https://github.com/qdrant/landing_page.git
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108 lines
3.8 KiB
Markdown
108 lines
3.8 KiB
Markdown
---
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title: "Qdrant Learn Portal"
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description: "Tutorials, Courses, Articles"
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hideTOC: true
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breadcrumb: false
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partition: learn
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feedback: false
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build:
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render: always
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cascade:
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- build:
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list: local
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publishResources: false
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render: never
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content:
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# - partial: documentation/banners/banner-b
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# title: Welcome to Qdrant Learn
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# description: Learn Portal
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# image:
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# src: /img/dev-portal-cloud/dev-portal-cloud-hero.png
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# alt: Qdrant Course
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# startedButton:
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# text: Start Learning
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# url: /courses/essentials
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- partial: documentation/sections/cards-section
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title: Learn
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description: Master vector search with Qdrant through comprehensive documentation, structured courses, and hands-on tutorials.
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cardsPartial: documentation/cards/docs-cards
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cards:
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- id: 1
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image:
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src: /img/dev-portal-learn/articles.png
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alt: Articles
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title: Articles
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description: In-depth technical documentation covering vector search concepts, system architecture, and advanced techniques.
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list:
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title: "Featured articles:"
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elements:
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- Data Exploration with Qdrant's Distance Matrix API
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- Why Vector Search Needs a Dedicated Database
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- Semantic Search As You Type
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link:
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url: /articles/
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text: Browse Articles
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- id: 2
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image:
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src: /img/dev-portal-learn/courses.png
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alt: Courses
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title: Courses
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description: Structured learning paths with progressive difficulty levels, from beginner fundamentals to advanced implementations.
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list:
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title: "Available topics:"
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elements:
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- "Beginner: Vector search basics"
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- "Intermediate: Advanced querying"
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- "Advanced: Production optimization"
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link:
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url: /course/
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text: View Courses
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- id: 3
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image:
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src: /img/dev-portal-learn/tutorials.png
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alt: Tutorials
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title: Tutorials
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description: Step-by-step guides and video content for hands-on learning with practical examples and real-world applications.
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list:
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title: "Tutorial categories:"
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elements:
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- "Search Engineering"
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- "Operations and Scale"
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- "Develop and Implement"
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link:
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url: /documentation/tutorials-lp-overview/
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text: Explore Tutorials
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- partial: documentation/sections/cards-section
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title: Quickstart
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description:
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cardsPartial: documentation/cards/docs-cards
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cardsPerRow: 2
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cards:
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- id: 1
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icon:
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src: /icons/outline/rocket-blue.svg
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alt: Rocket icon
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title: New to Vector Search?
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description: Start with our beginner-friendly exercises on vector embeddings and basic concepts.
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link:
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text: Start Learning
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url: /documentation/tutorials-basics/
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- id: 2
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icon:
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src: /icons/outline/hacker-purple.svg
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alt: Hacker icon
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title: Ready to Build?
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description: Build out practical projects using our example prototypes and integration guides.
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link:
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text: View Examples
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url: /documentation/examples/
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---
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# Learn
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- **[Articles](/articles/index.md)**: Long-form technical pieces covering vector search concepts, system architecture, RAG pipelines, quantization, hybrid retrieval, and Qdrant internals.
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- **[Courses](/course/index.md)**: Structured, self-paced learning paths through Qdrant Academy. Two courses are currently available: *Qdrant Essentials* (9–12 hours) and *Multi-Vector Search* (4–6 hours), with beginner, intermediate, and advanced courses planned. Free, with certification.
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- **[Tutorials](/documentation/tutorials-lp-overview/index.md)**: Step-by-step guides organized into five categories: Basic, Search Engineering, Operations & Scale, Develop & Implement, and Migrate to Qdrant. |