Data visualization is a critical skill for anyone that routinely using quantitative data in his or her work - which is to say that data visualization is a tool that almost every worker needs today. One of the critical tools for data visualization today is the R statistical programming language. Especially in conjunction with the tidyverse software packages, R has become an extremely powerful and flexible platform for making figures, tables, and reproducible reports. However, R can be intimidating for first time users, and there are so many resources online that it can be difficult to sort through without guidance.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Data Visualization & Dashboarding with R
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Spezialisierung Data Visualization & Dashboarding with RJohns Hopkins UniversityÜber diesen Kurs
14.424 kürzliche Aufrufe
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Zertifikat zur Vorlage
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Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 2 von 5 in
Stufe „Mittel“
Ca. 13 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 2 von 5 in
Stufe „Mittel“
Ca. 13 Stunden zum Abschließen
Englisch
Untertitel: Englisch
von
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Lehrplan - Was Sie in diesem Kurs lernen werden
4 Stunden zum Abschließen
Introduction to the Grammar of Graphics
In this module, we will get started using ggplot2. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.
4 Stunden zum Abschließen
4 Videos (Gesamt 26 min), 11 Lektüren, 3 Quiz
3 Stunden zum Abschließen
More Visualizations with ggplot
In this module, we will continue working with ggplot, learning additional types of visualization techniques. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up.
3 Stunden zum Abschließen
7 Videos (Gesamt 39 min), 4 Lektüren, 3 Quiz
5 Stunden zum Abschließen
ggplot Graphical Elements
In this module, we will cover how to refine plots created in ggplot2. You should begin by watching the introductory videos in each lesson. Then, carefully review the readings and reference materials provided. Once you have done that, I recommend watching the videos again to check your understanding. You will take a few quizzes as you progress through the material to make sure you are keeping up. Then, at the end of the module, you will submit an assignment for peer review that covers all of the material in this course.
5 Stunden zum Abschließen
6 Videos (Gesamt 38 min), 8 Lektüren, 4 Quiz
Bewertungen
Top-Bewertungen von DATA VISUALIZATION IN R WITH GGPLOT2
von DP28. Juli 2021
The best course that I took on Coursera. Thanks Prof. Collin Paschall very much for the entire course set up.
von AT14. Apr. 2021
The course is very interesting. It helped me improve my skills with different graphs and charts
von MZ12. Mai 2021
My best thanks to Coursera and Johns Hopkins University for holding this valuable course.
von AA18. Apr. 2021
Excellent course, learned a lot; looking forward to the next one in the series.
Über den Spezialisierung Data Visualization & Dashboarding with R
This Specialization is intended for learners seeking to develop the ability to visualize data using R. Through five courses, you will use R to create static and interactive data visualizations and publish them on the web, which will you prepare you to provide insight to many types of audiences.
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