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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-in-containers/
课程评论：没有评论
课程名称：Python在容器中 课程概述：本课程要求下载Anaconda（来自anaconda[.]com网站）和Docker（来自docker[.]com网站）软件。如果你是Udemy Business用户，请在下载软件前咨询你的雇主。如今，Docker和Kubernetes是Python工程师必备的技能。无论是聚焦于机器学习与数据科学，还是将Python作为通用编程语言，了解Docker和Kubernetes都是必要的。这两者构成了现代云原生应用程序的基础，采用微服务架构。 课程评价摘录： - "它涵盖了企业项目中你所期望的一切。" - Abbi1680 - "这门课程对于数据科学和机器学习的人来说绝对是宝藏，因为市面上所有的Docker和Kubernetes课程都只关注Web应用。感谢讲师从一个非常需要的不同视角处理虚拟化的概念。" - Mertkan Alacahan - "非常到位，深度很大且非常简明。" - Toby Patterson - "这是一次关于Python和Docker的深入探索。这是完整的课程，感谢你将其整合在一起，这远远超过了我所需要的。" - Pedro 课程内容： - 在Docker中开发和探索机器学习与数据科学的Jupyter Notebook - 在生产中使用Kubernetes和Docker运行机器学习模型 - 将Python代码打包到容器中 - 在镜像注册表中发布容器 - 在生产中部署容器 - 以微服务的方式构建高度模块化的基于容器的服务 - 监控和维护容器化的应用程序 通过本课程，你将精通并自信地使用Docker工具创建运行Python代码的顶级容器。你将掌握Docker运行时工具（如Compose和Swarm）。课程还将深入讲解Kubernetes作为应用平台的知识，使你在设计可以在Kubernetes上运行的应用时更加自信，并深入了解Kubernetes对象声明的编写。 课程包含实践练习，并提供超过40个包含代码示例的GitHub仓库。你可以通过两种方式使用本课程： 1. 如果你将Python用于机器学习与数据科学，可以从第7节开始，快速获得实用的Docker技能，然后使用第2至第6节深入特定的容器主题。 2. 如果你希望使用Python开发Web应用和微服务，建议线性学习课程内容。 今天就开始构建容器吧！
Important Disclaimer: This course requires you to download Anaconda software from anaconda[.]com website, as well as Docker software from docker[.]com website. If you are a Udemy Business user, please check with your employer before downloading software.Docker and Kubernetes are the Must-Have Skills for Python Enginner these days.Whether your focus is in Machine Learning & Data Science, or you use Python as General Programming Language, you must understand Docker & Kubernetes. Both form a basis of Modern Cloud Native Applications built in Microservices Architecture.Quotes from selected course reviews:"It covers pretty much everything you'd expect from enterprise project" Abbi1680"This course is absolute gold for data science and machine learning people because all Docker and Kubernetes courses out there focus on nothing but web applications. Thanks to the instructor for handling the concept of virtualization from a much needed different perspective. There are a lot of sources for learning ML and DS but skills taught in this course are what will make you stand out from the crowd." Mertkan Alacahan"Spot on. Great depth yet very concise." Toby Patterson"This is a deep deep deep dive in Docker with python. It is the complete course. Thanks for putting this together it is more than enough for what a need. I think watching the basic lectures and some selected topics I get what I needed and this became my docker reference guide if I need to solve a specific scenario. Thanks for putting this together. Highly recommend the course if you are a python developer." PedroIn this Course you learn how to:Develop and Explore Machine Learning & Data Science Jupyter Notebooks in DockerRun Machine Learning Models in Production with Kubernetes and Docker Swarmpackage your Python Code into Containerspublish your Containers in Image Registriesdeploy Containers in Productionbuild highly modular Container-based Services in Micro-Services fashionmonitor and maintain Containerized AppsYou are going to become fluent and confident in using Docker Tools to create top-class Containers running your Python Code. You master Docker Runtime Tools like Compose and Swarm to run them. The Course also gives you sound knowledge and deep understanding of Kubernetes as the Application Platform. You gain confidence in Designing your Application to run on Kubernetes, as well as get deep knowledge of writing Kubernetes Object Declarations.The Course is full of practical Exercises. There are over 40 GitHub Repositories full of Code Samples for the Course.You can use the Course in two ways:If you use Python for Machine Learning & Data Science, go Top-Down: start with Section 7 to quickly gain practical Docker skills and use Sections 2 to 6 to dig deeper into specific Container Topics.If you want to use Python for Web Apps & Microservices, try Bottom-Up: use the Course in linear manner.Start building Containers today!
