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Statistics with Python Using NumPy, Pandas, and SciPy

Statistics with Python Using NumPy, Pandas, and SciPy

本课程是 Data-Oriented Python Programming and Debugging 专项课程的一部分

位教师：Elle O'Brien

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。

中级等级

推荐体验

2 周完成

在 10 小时一周

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。

中级等级

推荐体验

2 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Use vector operations in NumPy for applied mathematics.
Visualize and analyze data distributions using NumPy and SciPy.
Use statistics to describe patterns in data distributions.
Conduct statistical inference using hypothesis testing with computational methods.

您将获得的技能

您将学习的工具

Python Programming

要了解的详细信息

可分享的证书

添加到您的领英档案

作业

1 项作业

授课语言：英语（English）

91%

of learners achieved a positive career outcome

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积累特定领域的专业知识

本课程是 Data-Oriented Python Programming and Debugging 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。

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获得对主题或工具的基础理解
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获得可共享的职业证书

该课程共有4个模块

“Statistics with Python Using NumPy, Pandas, and SciPy” explores how to apply statistical and mathematical techniques to data science problems.

Throughout the first half of the course, you’ll work on reviewing vector dot products, interpreting text as vectors, and matrix multiplication. You’ll also explore the basics of probability, laying the groundwork for statistical analysis. In the second half, you’ll cover how to interpret data distributions, reason about probability, explore the special properties of normal distributions, understand linear relationships in data, and the connection between probability and uncertainty. This is the third course in the four-course series “Data-Oriented Python Programming and Debugging,” where you’ll work to strengthen your programming capabilities and enhance your problem-solving skills.