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.
Offert par
Université Johns-HopkinsÀ propos de ce cours
359 643 consultations récentes
Dates limites flexibles
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Certificat partageable
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100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau intermédiaire
Familiarity with regression is recommended.
Approx. 57 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Chinois (simplifié), Italien, Portugais (brésilien), Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol, Japonais
Ce que vous allez apprendre
Understand critical programming language concepts
Configure statistical programming software
Make use of R loop functions and debugging tools
Collect detailed information using R profiler
Compétences que vous acquerrez
- Data Analysis
- Debugging
- R Programming
- Rstudio
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Niveau intermédiaire
Familiarity with regression is recommended.
Approx. 57 heures pour terminer
Anglais
Sous-titres : Arabe, Français, Portugais (européen), Chinois (simplifié), Italien, Portugais (brésilien), Vietnamien, Coréen, Allemand, Russe, Anglais, Espagnol, Japonais
Offert par
Université Johns-Hopkins
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.
Programme de cours : ce que vous apprendrez dans ce cours
25 heures pour terminer
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 heures pour terminer
28 vidéos (Total 129 min), 9 lectures, 8 quiz
12 heures pour terminer
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 heures pour terminer
13 vidéos (Total 91 min), 3 lectures, 5 quiz
9 heures pour terminer
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 heures pour terminer
8 vidéos (Total 61 min), 2 lectures, 4 quiz
11 heures pour terminer
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 heures pour terminer
6 vidéos (Total 42 min), 4 lectures, 5 quiz
Avis
- 5 stars68,15 %
- 4 stars22,20 %
- 3 stars5,81 %
- 2 stars2,05 %
- 1 star1,77 %
Meilleurs avis pour LA PROGRAMMATION EN R
par DV2 févr. 2016
The content is superbly designer for a beginner. The Swirl assignments need to make compulsory. Infact they contributed more to the learning process. More Swirl contents will make the course richer.
par GP6 mai 2017
Helpful in learning the basics and then some. However, the course assumes you know certain things about the R language and a lot of catching up had to be done (learning from outside sources etc.).
par YZ16 juil. 2020
This is course is probably my favorite out of the Data Science: Foundations using R specialization. There was plenty of opportunity to practice and further develop by burgeoning R programming skill.
par JM11 août 2019
Very challenging, but good course. I've been programming in R for over a year, but there were still some things for me to pick up in this class. Assignments were a challenge, but satisfying to tackle.
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