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Deploy
Ecosystem
Learn
API Reference

Qdrant Beginner Course

Module 0: Setting Up Dependencies
Module 1: Let's Understand Search
Module 2: First Principles of Vector Search
Module 3: Sparse vs Dense vs Hybrid Search
Module 4: Designing a Vector Search System
Module 5: Multimodal Supplier Risk Intelligence
Module 6: Beyond Similarity (Bonus)
Qdrant Beginner Certification

Qdrant Essentials Course

Day 0: Setup and First Steps
Day 1: Vector Search Fundamentals
Day 2: Indexing and Performance
Day 3: Hybrid Search
Day 4: Optimization and Scale
Day 5: Advanced APIs
Day 6: Final Project - Building a Production-Grade Search Engine
- Final Project: Production-Ready Documentation Search Engine
- Course Completion and Next Steps
Day 7: Partner Ecosystem Integrations (Bonus)
Qdrant Essentials Certification
Qdrant Essentials FAQs

Multi-Vector Search Course

Module 0: Setting Up Dependencies
- Qdrant Setup
- Installing Dependencies
Module 1: Multi-Vector Representations for Textual Data
Module 2: Multi-Vector Representations for Multi-Modal Data
Module 3: Scalability and Optimization
Qdrant Multi-Vector Certification

Qdrant Beginner Course

3%

Course Overview

Module 0: Setting Up Dependencies

Module Overview

Implementing a Basic Vector Search

Module 1: Let's Understand Search

Module Overview

What Is Search?

Why Keyword Search Struggles

How Traditional Search Improved

How It Works: Embeddings

Comparing Meaning: Distance Metrics

Why Similarity Alone Is Not Enough

When a System Needs Both

Further Reading

Module 2: First Principles of Vector Search

Module Overview

From Idea to System

Core Data Model

Distance Metrics

Top-K Retrieval

Fast Approximate Search: HNSW

Payload Filtering

Chunking Strategies

Ingestion Pipeline: End-to-End

Further Reading

Module 3: Sparse vs Dense vs Hybrid Search

Module Overview

Where We Left Off

The Two Families of Search

Hybrid Search: Dense and Sparse

Setting Up Hybrid Search in Qdrant

Fusion Strategies

Filtering: Works with Any Retrieval Method

Knowledge Check

References and Further Reading

Module 4: Designing a Vector Search System

Module Overview

Where Design Decisions Live

Decide Before You Ingest

What Changes as the Collection Grows

Growing Past One Machine

From Results to an Answer

Design Your Own System

References and Further Reading

Module 5: Multimodal Supplier Risk Intelligence

Module Overview

Project Overview

System Architecture

Signal Sources and Embedding Models

Ingestion Pipeline

Clustering Risk Signals

Analyst Queries

Knowledge Check

References and Further Reading

Module 6: Beyond Similarity (Bonus)

Module Overview

Find Your Problem

Ranking: Score Boosting and Reranking

Diversity: Maximal Marginal Relevance

Grouping: One Slot per Document

Searching From Examples and Feedback

Inspecting a Collection

Knowledge Check

Qdrant Beginner Certification

Qdrant Academy
Qdrant Beginner Course
Module 0: Setting Up Dependencies
Module Overview

Module 0

Setting Up Dependencies

Get started with Qdrant by setting up your environment and building your first vector search application.

Today’s Path

Qdrant Setup
Implementing a Basic Vector Search

Continue to Next Step

On this page:

Setting Up Dependencies
- Today’s Path

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