---
title: "Qdrant Academy"
short_description: "Qdrant Academy: free, structured courses on vector search, hybrid retrieval, multivectors, and production-grade AI search applications."
description: Master vector search and AI-powered applications with Qdrant Academy. Free, self-paced courses guide you from beginner to expert with hands-on projects, code notebooks, and certification.
weight: 50
---

# Welcome to Qdrant Academy

## Learn to Build, Scale, and Master AI-Native Search

Qdrant Academy is your step-by-step learning hub for mastering vector search, hybrid retrieval, and real-world AI applications with structured, free, online courses.

Whether you’re new to Qdrant or building production-grade systems, our guided courses help you go from beginner to expert, one module at a time.

## Available Now

{{< course-card
 title="Qdrant Essentials Course"
 image="/icons/outline/rocket-white-light.svg"
 link="/course/essentials/"
>}}
**What you’ll gain:**
- Vector Search Fundamentals
- Indexing and Performance Basics
- Hybrid Search Overview
- Optimization and Scaling
- Advanced API Introducion
- Ecosystem Integrations (Bonus)
<br><br>
Time to Complete: 9-12 hours<br>
Includes: videos, code notebooks, projects, certification
{{< /course-card >}}

{{< course-card
 title="Multi-Vector Search Course"
 image="/icons/outline/similarity-blue.svg"
 link="/course/multi-vector-search/"
>}}
**What you’ll gain:**
- Late Interaction Models and MaxSim Scoring
- ColBERT for Text Search
- ColPali for Visual Document Search
- Multi-Stage Retrieval Pipelines
- Quantization and Pooling Techniques
- MUVERA Indexing for Large-Scale Search
<br><br>
Time to Complete: 4-6 hours<br>
Includes: videos, code notebooks, projects, certification
{{< /course-card >}}

## Upcoming Courses

### Beginner Level
Beginner courses require no previous experience with Qdrant and are useful for building a strong foundation in vector search.

{{< accordion >}}
- title: "Qdrant Fundamentals"
  content: |
    - Vector Search Concepts
    - Setting Up Qdrant
    - Creating and Managing Collections
    - Ingesting Vector Embeddings
    - Running Your First Query
    <br>
    <br>
    Time to Complete: 2 hours (TBD)<br>
    Includes: videos, code notebooks
    <br>
    <br>
    <p style="margin-left: 0px;"><a href="https://forms.gle/jiBmDcXr8j9tAb5UA" target="_blank">→ Register Interest</a></p>

{{< /accordion >}}

### Intermediate Level
Intermediate courses are recommended for those that have completed the Beginner Level Modules first, and extend knowledge into more practical usage of Qdrant in the real-world.


{{< accordion >}}
- title: "Optimizing Performance"
  content: |
    - Fine-tuning HNSW parameters
    - Using quantizations for memory efficiency
    - Batch insertion and parallel indexing
    - Disk indexing and cost reduction
    - Advanced filtering
    <br>
    <br>
    Time to Complete: 2-3 hours (TBD)<br>
    Includes: videos, walkthroughs, projects
    <br>
    <br>
    <p style="margin-left: 0px;"><a href="https://forms.gle/aDinAbwAARB7JArg8" target="_blank">→ Register Interest</a></p>

- title: "Scaling and DevOps"
  content: |
    - Cluster setup and replication
    - Backup, restore, and upgrade strategies
    - Deploying in Docker, K8s, or Cloud Run
    - Security and authentication
    - Observability and monitoring
    <br><br>
    Time to Complete: 4-5 hours (TBD)<br>
    Includes: videos, walkthroughs, projects
    <br>
    <br>
    <p style="margin-left: 0px;"><a href="https://forms.gle/vj1keRBjUC3Gijeo6" target="_blank">→ Register Interest</a></p>

{{< /accordion >}}


### Advanced Level
Advanced courses are recommended for those that have completed the Beginner and Intermediate Level Modules first, and provide guidance for the ultimate level of mastery with Qdrant. In these modules, you'll learn of common anti-patterns and pitfalls, nuances and best practices, and ultimately be certified as an Elite Qdrant Developer.

{{< accordion >}}
- title: "AI Engineer"
  content: |
    **What you’ll gain:**
    - Developing AI applications
    - Agentic vector search architectures
    - GPU indexing and optimizations
    - Real-time ingestion and streaming pipelines
    - Accuracy-cost-performance tradoffs
    <br><br>
    Time to Complete: ~5 hours (TBD)<br>
    Includes: videos, walkthroughs, projects
    <br>
    <br>
    <p style="margin-left: 0px;">
      <a href="https://forms.gle/eeWbeB6tUhBKFCVJ6" target="_blank">→ Register Interest</a>
    </p>

- title: "Search Engineer"
  content: |
    **What you’ll gain:**
    - Contextual reranking and semantic filtering
    - Multivector and late interaction models
    - Advanced hybrid search
    - Multimodal embedding models
    - Accuracy-cost-performance tradoffs
    <br><br>
    Time to Complete: 5-6 hours (TBD)<br>
    Includes: videos, walkthroughs, projects
    <br>
    <br>
    <p style="margin-left: 0px;">
      <a href="https://forms.gle/VEZ6xLAqvBtZQRCa7" target="_blank">→ Register Interest</a>
    </p>
{{< /accordion >}}

**Want something not mentioned above? Email [devrel@qdrant.com](emailto:devrel@qdrant.com) and let us know!**