R Programming
date_range Débute le 10 décembre 2018
event_note Se termine le 14 janvier 2019
list 4 séquences
assignment Niveau : Intermédiaire
chat_bubble_outline Langue : Anglais
language Sous titrage : Arabe, Français, Chinois, Vietnamien, Japonais
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3.7 /5
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619 avis

Les infos clés

credit_card Formation gratuite
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En résumé

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.

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Le programme

  • Week 1 - 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 descri...
  • Week 2 - 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.
  • Week 3 - 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 a...
  • Week 4 - 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 addresse...

Les intervenants

Roger D. Peng, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health

Jeff Leek, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health

Brian Caffo, PhD
Professor, Biostatistics
Bloomberg School of Public Health


Le concepteur

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.

La plateforme

Coursera est une entreprise numérique proposant des formations en ligne ouverte à tous fondée par les professeurs d'informatique Andrew Ng et Daphne Koller de l'université Stanford, située à Mountain View, Californie.

Ce qui la différencie le plus des autres plateformes MOOC, c'est qu'elle travaille qu'avec les meilleures universités et organisations mondiales et diffuse leurs contenus sur le web.

Avis de la communauté
3.7 /5 Moyenne
Le meilleur avis

good course, But I would like to see something approaching codding more like production, or even projects, real life projects to in.

le 5 mars 2018
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le 5 mars 2018

In this course, a tutor should explain what is rnorm and how their values are distributed and also assignments are way much harder for beginners. we cannot even have an idea how the particular function should be created.

le 5 mars 2018

good course, But I would like to see something approaching codding more like production, or even projects, real life projects to in.

le 3 mars 2018

This course will teach you a lot but it is very difficult. The programming assignments are very challenging. I would not recommend this for someone who has never used R before.

le 1 mars 2018

Its really well concieved. I didn't have to have past experience in statistics to learn R, yet since I do have some background, it was fun to mess around with it.I learned enough to get me started with R. Thank you very much.

le 27 février 2018

Though I have learned R for 5 years, I still found some very interesting contents and insight opinion, by the way, all the mentors of this course are very professional and accommodating.