In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
von
Johns Hopkins UniversityÜber diesen Kurs
360.834 kürzliche Aufrufe
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.
Stufe „Mittel“
Familiarity with regression is recommended.
Ca. 57 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Chinesisch (vereinfacht), Italienisch, Portugiesisch (Brasilien), Vietnamesisch, Koreanisch, Deutsch, Russisch, Englisch, Spanisch, Japanisch
Was Sie lernen werden
Understand critical programming language concepts
Configure statistical programming software
Make use of R loop functions and debugging tools
Collect detailed information using R profiler
Kompetenzen, die Sie erwerben
- Data Analysis
- Debugging
- R Programming
- Rstudio
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.
Stufe „Mittel“
Familiarity with regression is recommended.
Ca. 57 Stunden zum Abschließen
Englisch
Untertitel: Arabischer Raum, Französisch, Portugiesisch (europäisch), Chinesisch (vereinfacht), Italienisch, Portugiesisch (Brasilien), Vietnamesisch, Koreanisch, Deutsch, Russisch, Englisch, Spanisch, Japanisch
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
25 Stunden zum Abschließen
Week 1: Background, Getting Started, and Nuts & Bolts
This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story.
25 Stunden zum Abschließen
28 Videos (Gesamt 129 min), 9 Lektüren, 8 Quiz
12 Stunden zum Abschließen
Week 2: Programming with R
Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.
12 Stunden zum Abschließen
13 Videos (Gesamt 91 min), 3 Lektüren, 5 Quiz
9 Stunden zum Abschließen
Week 3: Loop Functions and Debugging
We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice.
9 Stunden zum Abschließen
8 Videos (Gesamt 61 min), 2 Lektüren, 4 Quiz
11 Stunden zum Abschließen
Week 4: Simulation & Profiling
This week covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs. Finally, we cover the str function, which I personally believe is the most useful function in R.
11 Stunden zum Abschließen
6 Videos (Gesamt 42 min), 4 Lektüren, 5 Quiz
Bewertungen
- 5 stars68,15 %
- 4 stars22,19 %
- 3 stars5,81 %
- 2 stars2,05 %
- 1 star1,77 %
Top-Bewertungen von R-PROGRAMMIERUNG
von CH30. Apr. 2020
I would have preferred the 'robot voice' concept from the toolbox course, since it could be updated to more recent R upgrades, but the assignments really made me think and that was my favorite part.
von AK26. Mai 2017
This was very engaging, however, the level of expectation and effort needed is much greater than course 1 - ToolBox. This is perhaps the best course on R Programming designed for a small duration.
von RR20. Feb. 2017
I am pleasantly surprised with the quality of this course. For a beginner, the Swirl exercises are incredibly helpful and I was able to build confidence in working with R because of them. Thank you!
von SS29. März 2021
Nice course but it would be better if more links to this course and exercises were added for students to be able to have more practices not only with swirl ( ) but also with trustable third parties.
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