---
title: "bootcamp"
type: "tool"
slug: "milvus-io-bootcamp"
canonical_url: "https://www.graphcanon.com/tools/milvus-io-bootcamp"
github_url: "https://github.com/milvus-io/bootcamp"
homepage_url: "https://milvus.io"
stars: 2437
forks: 688
primary_language: "Jupyter Notebook"
license: "Apache-2.0"
categories: ["vector-databases", "data-retrieval"]
tags: ["embeddings", "deep-learning", "llm", "image-recognition", "image-classification", "milvus", "audio-search", "image-search"]
updated_at: "2026-07-07T18:44:34.392958+00:00"
---

# bootcamp

> Interactive tutorials and examples for mastering Milvus with unstructured data applications.

Provides a suite of interactive Jupyter Notebook tutorials, covering a wide range of use cases including image search, question answering systems, and more. Focuses on enhancing project integration with seamless optimization tools and evaluation methods.

## Facts

- Repository: https://github.com/milvus-io/bootcamp
- Homepage: https://milvus.io
- Stars: 2,437 · Forks: 688 · Open issues: 1 · Watchers: 37
- Primary language: Jupyter Notebook
- License: Apache-2.0
- Last pushed: 2026-04-20T03:06:07+00:00

## Categories

- [Vector Databases](/categories/vector-databases.md)
- [Data & Retrieval](/categories/data-retrieval.md)

## Tags

embeddings, deep-learning, llm, image-recognition, image-classification, milvus, audio-search, image-search

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## README (excerpt)

```text
<img src="pics/logo.png" alt="milvus bootcamp banner">

<div class="column" align="middle">
  <a href="https://github.com/milvus-io/bootcamp/blob/master/LICENSE"><img height="20" src="https://img.shields.io/github/license/milvus-io/bootcamp" alt="license"/></a>
  <a href="https://milvus.io"><img src="https://img.shields.io/badge/milvus-blue" alt="milvus"/></a>
  <a href="https://cloud.zilliz.com/signup?utm_source=partner&utm_medium=referral&utm_campaign=2024-11-04_web_github-readme_global"><img src="https://img.shields.io/badge/zilliz-green" alt="fully-managed-milvus"/></a>
  <a href="https://milvus.io/slack"><img src="https://img.shields.io/badge/Slack-%234A154B.svg?style=flat&logo=slack&logoColor=white" alt="slack"/></a>
  <a href="https://discord.gg/mKc3R95yE5"><img height="20" src="https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white" alt="discord"/></a>
  <a href="https://x.com/milvusio"><img src="https://img.shields.io/twitter/follow/milvusio" alt="twitter"/></a>
</div>

## :bird: What You Can Do

Begin an interactive journey to master [Milvus](https://milvus.io), enhancing your projects with seamless integration and optimization tools.

- **Explore Tutorials:** Dive into notebooks that walk you through diverse Milvus use cases.

- **Deploy Demos:** Build your own demo to see Milvus in action.

- **Discover Use Cases:** Learn how Milvus integrates with other tools and frameworks through practical examples.

- **Expand Your Skills:** Apply evaluation methods to test and optimize your applications.

## :pencil: Examples

You can explore a comprehensive [Tutorials Overview](https://milvus.io/docs/tutorials-overview.md) covering topics such as Retrieval-Augmented Generation (RAG), Semantic Search, Hybrid Search, Question Answering, Recommendation Systems, and various quick-start guides. These resources are designed to help you get started quickly and efficiently.

<table>
  <tr>
    <td width="30%">
      <a href="https://milvus.io/milvus-demos">
        <img src="https://assets.zilliz.com/image_search_59a64e4f22.gif" />
      </a>
    </td>
    <td width="30%">
<a href="https://milvus.io/milvus-demos">
<img src="https://assets.zilliz.com/qa_df5ee7bd83.gif" />
</a>
    </td>
    <td width="30%">
<a href="https://milvus.io/milvus-demos">
<img src="https://assets.zilliz.com/mole_search_76f8340572.gif" />
</a>
    </td>
  </tr>
  <tr>
    <th>
      <a href="https://milvus.io/milvus-demos">Image Search</a>
    </th>
    <th>
      <a href="https://milvus.io/milvus-demos">RAG</a>
    </th>
    <th>
      <a href="https://milvus.io/milvus-demos">Drug Discovery</a>
    </th>
  </tr>
</table>


Here is a selection of demos and tutorials to show how to build various types of AI applications made with Milvus:

| Tutorial | Use Case | Related Milvus Features |
| ----------- | -------- | -------- |
| [Build RAG with Milvus](https://milvus.io/docs/build-rag-with-milvus.md) |  RAG | vector search |
| [Advanced RAG Optimizations](https://milvus.io/docs/how_to_enhance_your_rag.md) | RAG | vector search, full text search |
| [Full Text Search with Milvus](https://milvus.io/docs/full_text_search_with_milvus.md) | Text Search | full text search |
| [Hybrid Search with Milvus](https://milvus.io/docs/hybrid_search_with_milvus.md) | Hybrid Search | hybrid search, multi vector, dense embedding, sparse embedding |
| [Image Search with Milvus](https://milvus.io/docs/image_similarity_search.md) | Semantic Search | vector search, dynamic field |
| [Multimodal Search using Multi Vectors](https://milvus.io/docs/multimodal_rag_with_milvus.md) | Semantic Search | multi vector, hybrid search |
| [Movie Recommendation with Milvus](https://milvus.io/docs/movie_recommendation_with_milvus.md) | Recommendation System | vector search |
| [Graph RAG with Milvus](https://milvus.io/docs/graph_rag_with_milvus.md) | RAG | graph search |
| [Use Milvus as a LangChain Vector Store](https://milvus.io/docs/basic_usage_langch
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/milvus-io-bootcamp`](/api/graphcanon/tools/milvus-io-bootcamp)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_