Introduction to Milvus (Vector Database) Using Python

Introduction to Milvus (Vector Database) Using Python, available at $74.99, has an average rating of 4.49, with 33 lectures, 16 quizzes, based on 268 reviews, and has 1760 subscribers.

You will learn about Basics of Vector databases Introduction to Milvus and Installing Milvus Collections, Partitions and Indexes in Milvus PyMilvus – Python SDK for Milvus A Real world Example using Milvus Role Based Access Control in Milvus Attu – UI based tool for managing Milvus This course is ideal for individuals who are Data Scientists or AI Engineers or Machine learning Engineers or MLOps Engineers or Data Engineers or Anyone who is motivated to learn and work with a Vector database It is particularly useful for Data Scientists or AI Engineers or Machine learning Engineers or MLOps Engineers or Data Engineers or Anyone who is motivated to learn and work with a Vector database.

Enroll now: Introduction to Milvus (Vector Database) Using Python

Summary

Title: Introduction to Milvus (Vector Database) Using Python

Price: $74.99

Average Rating: 4.49

Number of Lectures: 33

Number of Quizzes: 16

Number of Published Lectures: 33

Number of Published Quizzes: 16

Number of Curriculum Items: 49

Number of Published Curriculum Objects: 49

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

Basics of Vector databases
Introduction to Milvus and Installing Milvus
Collections, Partitions and Indexes in Milvus
PyMilvus – Python SDK for Milvus
A Real world Example using Milvus
Role Based Access Control in Milvus
Attu – UI based tool for managing Milvus

Who Should Attend

Data Scientists
AI Engineers
Machine learning Engineers
MLOps Engineers
Data Engineers
Anyone who is motivated to learn and work with a Vector database

Target Audiences

Data Scientists
AI Engineers
Machine learning Engineers
MLOps Engineers
Data Engineers
Anyone who is motivated to learn and work with a Vector database

Milvus isthe world’s first open-source vector database system that canstore, index, and search across Billions of vectors! Vector databases are one of the emerging technologies of the decade supporting modern AI tools and learning Milvus to build highly scalable and real-time AI applications can help you progress faster in your career.

This course will provide you with solid practical Skills in Milvus using its Python SDK (PyMilvus). Before you begin, you are required to have basic knowledge on

Python Programming
Linux Commands
Docker and Docker Compose

Some of the highlights of this course are

All lectures have been designed from the ground up to make the complex topics easy to understand
Ample working examples demonstrated in the video lectures
Downloadable Python notebooks with the examples that were used in the course
Precise and informative video lectures
Quiz at the end of important video lectures
Covers a wide range of fundamental topics in Milvus

After completing this course, you will be able to

Install and work with Milvus using Python
Manage Collections and indexes in Milvus
Perform vector search on vectors stored in Milvus
Manage users and roles in Milvus
Use Attu, a web-based UI that can be used to manage Milvus
Use Milvus to build scalable AI apps

This course will be updated periodically and enroll now to get lifelong access to this course!

Course Updates:

17-05-2024 – Updated the course for version 2.4.1. updated the video lectures on Collection, Indexes and installation. Added new lecture videos on Dynamic schema and custom partition key.
01-02-2024 – Updated the quiz section under collections and indexes
04-11-2023 – Added a new section with working examples
04-07-2023 – Added quiz on Flat, IVF, Scalar quantization, Product Quantization, and HNSW Indexes
25-06-2023 – Added a new chapter of video lectures on Milvus Indexes
11-06-2023 – Updated the quiz questions

Course Curriculum

Chapter 1: Introduction

Lecture 1: Prelude

Lecture 2: Introduction

Lecture 3: Introduction to vector Databases

Lecture 4: Components of a Vector Database

Lecture 5: Embedding vectors

Lecture 6: Vector Similarity Metrics

Lecture 7: Introduction to Milvus

Chapter 2: Milvus

Lecture 1: Milvus Architecture

Lecture 2: Milvus – Storage Concepts

Lecture 3: Installation

Lecture 4: PyMilvus

Lecture 5: Collections

Lecture 6: Partitions

Lecture 7: Data management

Lecture 8: Indexing the data

Lecture 9: Querying & Searching

Lecture 10: Dynamic Schema in Collections

Lecture 11: Partition key

Lecture 12: An Example Using Tensorflow

Lecture 13: Role Based Access Control

Lecture 14: Attu

Lecture 15: Milvus Lite

Chapter 3: Indexes in Milvus

Lecture 1: Introduction

Lecture 2: Flat Index

Lecture 3: Inverted File Index (IVF)

Lecture 4: Scalar Quantization

Lecture 5: Product Quantization

Lecture 6: HNSW Index (Hierarchical Navigable Small World graphs)

Chapter 4: Working Examples – Optional

Lecture 1: Introduction

Lecture 2: Find the similar sheeps – PyTorch

Lecture 3: Song Search – OpenAI

Lecture 4: Answering the Questions – LangChain

Chapter 5: Conclusion

Lecture 1: Conclusion

Instructors

Vijay Anand Ramakrishnan
Instructor at Golden Clover Education

Rating Distribution

1 stars: 1 votes
2 stars: 5 votes
3 stars: 28 votes
4 stars: 89 votes
5 stars: 145 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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