# Beginners Course **Learn the fundamentals of vector search** Understand why traditional keyword search fails and how semantic (vector) search solves it. Learn about embeddings, distance metrics, and hybrid search systems.

Multiple modules

Focused lessons building from fundamentals to practical applications

Shareable certificate

Earn a digital certificate upon completion

Flexible schedule

Learn at your own pace

Beginner level

No prior experience required

## What you'll learn

Skills you'll gain:

Why keyword search breaks and how semantic search solves it
How embeddings convert text to vectors that capture meaning
Distance metrics: cosine similarity, dot product, and Euclidean
Hybrid search: combining dense and sparse retrieval
Building your first Qdrant collection and queries

### The Path **Module 0**: Setup. Configure your environment and get started with the basics. **Module 1**: Let's Understand Search. Understand why keyword search fails and how semantic search solves it. **Module 2**: First Principles of Vector Search. Learn what vectors are, how dimensions represent meaning, similarity metrics, and build your first Qdrant collection. ## How the course works

Clear lessons

Focused modules by the Qdrant team

Hands-on learning

Practical examples and exercises

Progressive learning

Build from fundamentals to advanced concepts

Self-paced

Learn at your own speed

## Syllabus

Module 0: Setting Up Dependencies

Qdrant Cloud Setup
Implementing a Basic Vector Search
Project: Building Your First Vector Search System

→ Start Module 0

Module 1: Let's Understand Search

The Problem: Why Keyword Search Breaks
How Traditional Search Improved
Enter Semantic Search
How It Works: Embeddings
Comparing Meaning: Distance Metrics
Why Similarity Alone Is Not Enough
Modern Search = Hybrid Systems
References & Further Reading

→ Coming soon

Module 2: First Principles of Vector Search

What is a Vector?
How Dimensions Represent Meaning
Similarity Under the Hood
Your First Qdrant Collection
Points, Payloads, and Queries

→ Coming soon

Module 3: Sparse vs Dense vs Hybrid Search

The Two Families of Search
Hybrid Search: Dense + Sparse + Filters
Setting Up Hybrid Search in Qdrant
Fusion Strategies
Beyond Text: Multimodal Search
Real-World Use Cases

→ Coming soon

## Who it's for Anyone new to vector search who wants to understand the fundamentals. No prior experience with Qdrant or vector databases required. ## Time commitment - Duration: Multiple modules - Self-paced learning - Flexible schedule

Ready to start your vector search journey?

What you’ll get

Understand the fundamentals of vector search
Learn why semantic search outperforms keyword search
Build your first Qdrant collection
Foundation for advanced courses

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