About this Course
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Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 17 hours to complete

Suggested: 6 hours/week...

English

Subtitles: English, Korean

What you will learn

  • 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

Skills you will gain

Python ProgrammingData VirtualizationData Visualization (DataViz)Matplotlib

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 17 hours to complete

Suggested: 6 hours/week...

English

Subtitles: English, Korean

Syllabus - What you will learn from this course

Week
1
5 hours to complete

Module 1: Principles of Information Visualization

7 videos (Total 37 min), 6 readings, 2 quizzes
7 videos
About the Professor: Christopher Brooks1m
Tools for Thinking about Design (Alberto Cairo)8m
Graphical heuristics: Data-ink ratio (Edward Tufte)4m
Graphical heuristics: Chart junk (Edward Tufte)5m
Graphical heuristics: Lie Factor and Spark Lines (Edward Tufte)3m
The Truthful Art (Alberto Cairo)8m
6 readings
Syllabus10m
Help us learn more about you!10m
Notice for Coursera Learners: Assignment Submission10m
Dark Horse Analytics (Optional)10m
Useful Junk?: The Effects of Visual Embellishment on Comprehension and Memorability of Charts30m
Graphics Lies, Misleading Visuals10m
Week
2
7 hours to complete

Module 2: Basic Charting

7 videos (Total 42 min), 2 readings, 1 quiz
7 videos
Matplotlib Architecture6m
Basic Plotting with Matplotlib7m
Scatterplots8m
Line Plots8m
Bar Charts4m
Dejunkifying a Plot3m
2 readings
Matplotlib30m
Ten Simple Rules for Better Figures30m
Week
3
8 hours to complete

Module 3: Charting Fundamentals

6 videos (Total 39 min), 2 readings, 2 quizzes
6 videos
Histograms9m
Box Plots7m
Heatmaps3m
Animation5m
Interactivity5m
2 readings
Selecting the Number of Bins in a Histogram: A Decision Theoretic Approach (Optional)10m
Assignment Reading10m
Week
4
5 hours to complete

Module 4: Applied Visualizations

3 videos (Total 18 min), 2 readings, 1 quiz
3 videos
Seaborn8m
Becoming an Independent Data Scientist1m
2 readings
Spurious Correlations10m
Post-course Survey10m
4.5
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Top reviews from Applied Plotting, Charting & Data Representation in Python

By 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.

By 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.

About University of Michigan

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....

About the Applied Data Science with Python Specialization

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....
Applied Data Science with Python

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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