课程信息
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第 2 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为17 小时

建议:6 hours/week...

英语(English)

字幕:英语(English), 韩语

您将学到的内容有

  • Check

    Create a visualization using matplotlb

  • Check

    Describe what makes a good or bad visualization

  • Check

    Identify the functions that are best for particular problems

  • Check

    Understand best practices for creating basic charts

您将获得的技能

Python ProgrammingData VirtualizationData Visualization (DataViz)Matplotlib
学习Course的学生是
  • Data Scientists
  • Data Analysts
  • Risk Managers
  • Process Analysts
  • Scientists

第 2 门课程(共 5 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为17 小时

建议:6 hours/week...

英语(English)

字幕:英语(English), 韩语

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 5 小时

Module 1: Principles of Information Visualization

7 个视频 (总计 37 分钟), 6 个阅读材料, 2 个测验
7 个视频
About the Professor: Christopher Brooks1分钟
Tools for Thinking about Design (Alberto Cairo)8分钟
Graphical heuristics: Data-ink ratio (Edward Tufte)4分钟
Graphical heuristics: Chart junk (Edward Tufte)5分钟
Graphical heuristics: Lie Factor and Spark Lines (Edward Tufte)3分钟
The Truthful Art (Alberto Cairo)8分钟
6 个阅读材料
Syllabus10分钟
Help us learn more about you!10分钟
Notice for Coursera Learners: Assignment Submission10分钟
Dark Horse Analytics (Optional)10分钟
Useful Junk?: The Effects of Visual Embellishment on Comprehension and Memorability of Charts30分钟
Graphics Lies, Misleading Visuals10分钟
2
完成时间为 7 小时

Module 2: Basic Charting

7 个视频 (总计 42 分钟), 2 个阅读材料, 1 个测验
7 个视频
Matplotlib Architecture6分钟
Basic Plotting with Matplotlib7分钟
Scatterplots8分钟
Line Plots8分钟
Bar Charts4分钟
Dejunkifying a Plot3分钟
2 个阅读材料
Matplotlib30分钟
Ten Simple Rules for Better Figures30分钟
3
完成时间为 8 小时

Module 3: Charting Fundamentals

6 个视频 (总计 39 分钟), 2 个阅读材料, 2 个测验
6 个视频
Subplots7分钟
Histograms9分钟
Box Plots7分钟
Heatmaps3分钟
Animation5分钟
Interactivity5分钟
2 个阅读材料
Selecting the Number of Bins in a Histogram: A Decision Theoretic Approach (Optional)10分钟
Assignment Reading10分钟
4
完成时间为 5 小时

Module 4: Applied Visualizations

3 个视频 (总计 18 分钟), 2 个阅读材料, 1 个测验
3 个视频
Seaborn8分钟
Becoming an Independent Data Scientist1分钟
2 个阅读材料
Spurious Correlations10分钟
Post-course Survey10分钟
4.5
550 个审阅Chevron Right

33%

完成这些课程后已开始新的职业生涯

35%

通过此课程获得实实在在的工作福利

15%

加薪或升职

来自Applied Plotting, Charting & Data Representation in Python的热门评论

创建者 SBNov 3rd 2017

Loved the course! This course teaches you details about matplotlib and enables you to produce beautiful and accurate graphs.. Assignments are challanging, and helps to build a solid foundation.

创建者 AMar 6th 2018

Very helpful to understand what it takes to make a scientific and sensible visual. Recommended for someone who is interested in learning data visualization and does not have a background.

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....

关于 借助 Python 应用数据科学 专项课程

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate....
借助 Python 应用数据科学

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