10最好的MLOps教程推荐

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特写 iPhone，显示 Udemy 应用程序和带笔记本的笔记本电脑有数以千计的在线课程和课程可以帮助您提高 MLOps 技能并获得 MLOps 证书。

在这篇博客文章中，我们的专家汇总了 10 个精选列表 最好的 MLOps 课程, 现在在线提供的教程、培训计划、课程和认证。

我们只包括那些符合我们高质量标准的课程。我们花了很多时间和精力来为您收集这些。这些课程适合所有级别的初学者、中级学习者和专家。

以下是这些课程以及它们为您提供的内容！

10最好的MLOps教程推荐

课程名 在校生（人数） 评论（计数）
1. Docker Masterclass for Machine Learning and Data Science 我们的最佳选择 33455+ 690+
2. Deployment of Machine Learning Models 25380+ 4022+
3. Testing and Monitoring Machine Learning Model Deployments 4750+ 363+
4. MLOps Fundamentals: CI/CD/CT Pipelines of ML with Azure Demo 4518+ 894+
5. Katonic MLOps Certification Course 570+ 65+
6. Learn & Deploy Data Science Web Apps with Streamlit 233+ 21+
7. Machine Learning Deployment For Professionals 153+ 11+
8. YOLO: Custom Object Detection in Python 101+ 15+
9. Complete MLOps Bootcamp | From Zero to Hero in Python 2022 40+ 6+
10. “MLOps, Machine Learning Operations for beginners” 1+ 0+

1. Docker Masterclass for Machine Learning and Data Science 经过 “Jordan Sauchuk, Ligency I Team, Ligency Team” Udemy课程 我们的最佳选择

Learn how to containerize and deploy your ML projects with Docker

截至目前，超过 33455+ 人们已经注册了这门课程，而且已经结束了 690+ 评论.

课程内容
Welcome
Introduction
Working With Docker – Basics
DockerHub
Challenge
Automated Builds
File Challenge
Docker Compose
Docker Swarm
AWS
Security
Maintenance & Monitoring
Final
Course Vault
Bonus Lectures

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2. Deployment of Machine Learning Models 经过 “Soledad Galli, Christopher Samiullah” Udemy课程

Learn how to integrate robust and reliable Machine Learning Pipelines in Production

截至目前，超过 25380+ 人们已经注册了这门课程，而且已经结束了 4022+ 评论.

课程内容
Introduction
Overview of Model Deployment
Machine Learning System Architecture
Research Environment – Developing a Machine Learning Model
Packaging The Model for Production
Serving and Deploying the model via REST API
Continuous Integration and Deployment Pipelines
Deploying The ML API With Containers
Differential Testing
Deploying to IaaS (AWS ECS)
A Deep Learning Model with Big Data
Common Issues found during deployment
Appendix: Former Section: Serving the model via REST API
Final Section

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3. Testing and Monitoring Machine Learning Model Deployments 经过 “Christopher Samiullah, Soledad Galli” Udemy课程

“ML testing strategies, shadow deployments, production model monitoring and more”

截至目前，超过 4750+ 人们已经注册了这门课程，而且已经结束了 363+ 评论.

课程内容
Introduction
Setting the Scene & ML System Lifecycle
Testing Concepts for ML Systems
Unit Testing a Production ML Model
Docker & Docker Compose
Integration Testing the ML API
Differential Testing
Shadow Mode Deployments
Monitoring – Metrics with Prometheus
Monitoring – Logs with Kibana
Conclusion
Final Section

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4. MLOps Fundamentals: CI/CD/CT Pipelines of ML with Azure Demo 经过 J Garg – Real Time Learning Udemy课程

MLOps fundamentals of Continuous Integration & Continuous Delivery (CI/CD) using Azure DevOps & Azure Machine Learning

截至目前，超过 4518+ 人们已经注册了这门课程，而且已经结束了 894+ 评论.

课程内容
Introduction
Challenges in existing ML projects
MLOps – A solution
Maturity levels in MLOps
MLOps Tools/Platforms Stack
Demo – Project Requirements
Azure Machine Learning Studio – Crash course
Demo – Data scientist’s experiment
Demo – Orchestrated ML codes in Azure
Demo – CI/CD MLOps Pipeline in Azure
BONUS

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5. Katonic MLOps Certification Course 经过 Katonic MLOps Platform Udemy课程

“Understand the concepts of MLOps, Kubernetes, Docker & learn how to build an E2E use case on Katonic MLOps Platform”

截至目前，超过 570+ 人们已经注册了这门课程，而且已经结束了 65+ 评论.

课程内容
Introduction to MLOps
Introduction to Kubernetes & Docker
MLOps Platform Introduction
End-to-End Use Case Demo

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6. Learn & Deploy Data Science Web Apps with Streamlit 经过 “Gusksra R, Data Science Anywhere” Udemy课程

“Learn, Develop and Deploy Streamlit web app for Data Science application using just Python”

截至目前，超过 233+ 人们已经注册了这门课程，而且已经结束了 21+ 评论.

课程内容
Introduction
Getting Started with Streamlit
Streamlit APIs
Streamlit Input Widgets
Practice test – 1
Visualizations with Streamlit
Interactive Visualizations in Streamlit
Project – 1: Develop & Deploy Automatic Data Profiling App
Bonus

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7. Machine Learning Deployment For Professionals 经过 Eduonix Learning Solutions Udemy课程

Learn to deploy and scale your machine learning solutions

截至目前，超过 153+ 人们已经注册了这门课程，而且已经结束了 11+ 评论.

课程内容
Course Introduction
Introduction to machine learning in production
ML and Data lifecycle
ML Pipeline
Deploying ML Solutions

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8. YOLO: Custom Object Detection in Python 经过 “Gusksra R, Data Science Anywhere” Udemy课程

YOLO: Custom Data Object Detection Model in Python

截至目前，超过 101+ 人们已经注册了这门课程，而且已经结束了 15+ 评论.

课程内容
Introduction
Data Preparation
Training YOLO Model
Prediction from YOLO Model
BONUS

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9. Complete MLOps Bootcamp | From Zero to Hero in Python 2022 经过 Data Bootcamp Udemy课程

“Advanced hands-on bootcamp of MLOps with MLFlow, Scikit-learn, CI/CD, Azure, FastAPI, Gradio, SHAP, Docker, DVC, Flask..”

截至目前，超过 40+ 人们已经注册了这门课程，而且已经结束了 6+ 评论.

课程内容
Challenges and evolution of Machine Learning
Fundamentos de MLOps
Etapas del MLOps
Instalación de herramientas y librerías
MLOps Phase 1: Solution Design
MLOps Phase 2: Automating the ML Model Cycle
MLOps phase 2: Registration and versioning of the model
Model interpretability
Putting models into production
MLOps Phase 3: Model serving with Web Applications
Flask for application development
Docker and containers for Machine Learning
Deploy Flask app to Cloud with Azure Container
Despliegue de modelos en Azure

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10. “MLOps, Machine Learning Operations for beginners” 经过 Dat Art Udemy课程

Machine Learning models from experimentation to production

截至目前，超过 1+ 人们已经注册了这门课程，而且已经结束了 0+ 评论.

课程内容
Introduction
MLOps Concepts
MLOps actors
MLOps tools

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下面是一些关于学习的常见问题MLOps

学习MLOps需要多长时间？

“学习MLOps需要多长时间”这个问题的答案是。 . .这取决于。每个人都有不同的需求，每个人都在不同的场景下工作，所以一个人的答案可能与另一个人的答案完全不同。

考虑这些问题：你想学习 MLOps 是为了什么？你的出发点在哪里？您是初学者还是有使用 MLOps 的经验？你能练习多少？每天1小时？每周40小时？ 查看本课程关于 MLOps.

MLOps 学起来容易还是难？

不，学习 MLOps 对大多数人来说并不难。检查这个 关于如何学习的课程 MLOps 立刻！

如何快速学习MLOps？

学习 MLOps 最快的方法是先得到这个 MLOps 课程, 然后尽可能练习你学到的任何东西。即使每天只有 15 分钟的练习。一致性是关键.

在哪里学习 MLOps？

如果您想探索和学习 MLOps，那么 Udemy 为您提供了学习 MLOps 的最佳平台。查看此 关于如何学习的课程 MLOps 立刻！