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.
oferecido por
Universidade Johns HopkinsInformações sobre o curso
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Resultados de carreira do aprendiz
29%
comecei uma nova carreira após concluir estes cursos
30%
consegui um benefício significativo de carreira com este curso
11%
recebi um aumento ou promoção
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Familiarity with regression is recommended.
Aprox. 57 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Português (Brasil), Vietnamita, Alemão, Russo, Inglês, Espanhol, Japonês
O que você vai aprender
Understand critical programming language concepts
Configure statistical programming software
Make use of R loop functions and debugging tools
Collect detailed information using R profiler
Habilidades que você terá
Data AnalysisDebuggingR ProgrammingRstudio
Resultados de carreira do aprendiz
29%
comecei uma nova carreira após concluir estes cursos
30%
consegui um benefício significativo de carreira com este curso
11%
recebi um aumento ou promoção
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Familiarity with regression is recommended.
Aprox. 57 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Português (Brasil), Vietnamita, Alemão, Russo, Inglês, Espanhol, Japonês
oferecido por
Universidade 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.
Programa - O que você aprenderá com este curso
25 horas para concluir
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 horas para concluir
28 vídeos (Total 129 mín.), 9 leituras, 8 testes
12 horas para concluir
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 horas para concluir
13 vídeos (Total 91 mín.), 3 leituras, 5 testes
9 horas para concluir
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 horas para concluir
8 vídeos (Total 61 mín.), 2 leituras, 4 testes
11 horas para concluir
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 horas para concluir
6 vídeos (Total 42 mín.), 4 leituras, 5 testes
Avaliações
Principais avaliações do LINGUAGEM R
por JM11 de Ago de 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.
por EJ11 de Jul de 2016
Excellent course! I already knew a lot about R - but this class helped me solidify what I already knew, taught me lots of new tricks, and now I have a certificate that says I know `something' about R!
por WH2 de Fev de 2016
"R Programming" forces you to dive in deep. These skills serve as a strong basis for the rest of the data science specialization.\n\nMaterial is in depth, but presented clearly. Highly recommended!
por MR11 de Mai de 2020
Really interesting course. The interactive coding sessions with swirl are especially useful. Would be great, if you provided sample solutions for the programming assignments, in particular for week 4.
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