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Advanced Python: Data Science, Testing, and Distribution

Advanced Python: Data Science, Testing, and Distribution

本课程是 Advanced Programming Techniques with Python 专项课程的一部分

位教师：Bill Rosenthal

包含在中

了解更多

4个模块

深入了解一个主题并学习基础知识。

8 小时完成

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

8 小时完成

灵活的计划

自行安排学习进度

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Advanced Programming Techniques with Python 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有4个模块

To round out your advanced implementation of Python, in this course, you'll clean and visualize data, and apply basic machine learning principles. You'll also handle exceptions and write and execute unit tests, as well as create and distribute Python packages.

单元详情

Python® is one of the most popular programming languages in the field of data science. This includes everything from data cleaning, to data analysis, to data visualization, and much more—all of which Python excels at. In this lesson, you will program Python for data science applications.

涵盖的内容

1篇阅读材料5个插件

Before your applications will be ready for people to use, you must ensure that they run error free and can handle any user, system, or data issues you can anticipate. In this lesson, you will handle exceptions and write and execute unit tests.

涵盖的内容

4个插件

Once you've created an application, you may want to think about sharing it with the world. The default Python® installation includes utilities to help you bundle all of the files required for your application into one place for easy distribution.