关于此 专项课程
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100% 在线课程

立即开始,按照自己的计划学习。

灵活的计划

设置并保持灵活的截止日期。

初级

High school-level algebra

完成时间大约为2 个月

建议 9 小时/周

英语(English)

字幕:英语(English), 韩语

您将学到的内容有

  • Check

    Create and interpret data visualizations using the Python programming language and associated packages & libraries

  • Check

    Apply and interpret inferential procedures when analyzing real data

  • Check

    Apply statistical modeling techniques to data (ie. linear and logistic regression, linear models, multilevel models, Bayesian inference techniques)

  • Check

    Understand importance of connecting research questions to data analysis methods.

您将获得的技能

Python ProgrammingData Visualization (DataViz)Statistical ModelStatistical inference methods

100% 在线课程

立即开始,按照自己的计划学习。

灵活的计划

设置并保持灵活的截止日期。

初级

High school-level algebra

完成时间大约为2 个月

建议 9 小时/周

英语(English)

字幕:英语(English), 韩语

专项课程的运作方式

加入课程

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实践项目

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获得证书

在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

how it works

此专项课程包含 3 门课程

课程1

Understanding and Visualizing Data with Python

4.6
227 个评分
51 个审阅
课程2

Inferential Statistical Analysis with Python

4.2
98 个评分
25 个审阅
课程3

Fitting Statistical Models to Data with Python

4.3
61 个评分
14 个审阅

讲师

Avatar

Brenda Gunderson

Lecturer IV and Research Fellow
Department of Statistics
Avatar

Brady T. West

Research Associate Professor
Institute for Social Research
Avatar

Kerby Shedden

Professor
Department of Statistics

关于 密歇根大学

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

常见问题

  • 可以!点击您感兴趣的课程卡开始注册即可。注册并完成课程后,您可以获得可共享的证书,或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分,系统会自动为您订阅完整的专项课程。访问您的学生面板,跟踪您的进度。

  • 此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

  • This specialization is made up of three courses, each with four weeks/modules. Each week in a course requires a commitment of roughly 3-6 hours, which will vary by learner.

  • High school-level algebra is the only background knowledge mandatory for the first course in the series. A basic Python and/or coding background is recommended.

  • It is definitely recommended to take this specialization in order.

  • You will not earn University credit for completing this specialization.

  • Upon completion of all courses in this specialization, you will have a solid grasp of statistical analysis and will be able to conduct analyses using the Python programming language. You'll be able to create data visualizations in Python, as well as interpret and explain them. You will be able to utilize data for estimation and assessing theories, interpretation of inferential results, and you will be able to apply more advanced statistical modeling procedures.

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