更新于2021.10.17
系统性课程-偏基础
R for Health Data Science
This book will take an individual with little or no experience in data science all the way through to the execution of sophisticated analyses. We emphasise the importance of truly understanding the underlying data with liberal use of plotting, rather than relying on opaque and possibly poorly understood statistical tests. There are numerous examples included that can be adapted for your own data, together with our own R packages with easy-to-use functions.
推荐度：★★★★
这是一本在线图书，通过bookdown构建，是专门针对R在医学数据领域写的，有一些基础语法讲解，整体比较浅显。
课程特征：
- 开源：
TRUE - 文字教程：
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FALSE - 难度：
LOW
发布者：
Surgical Informatics (github.com)
Surgery, Science and Computers. Surgical Informatics at the University of Edinburgh
Ready for R
This course is meant to be a gentle introduction to data wrangling and visualization using the tidyverse in R. This course focuses on practical data science skills in R (loading data, data wrangling, visualization, automation, machine learning, and running statistical models) that you’ll use almost everyday in your work. It is meant for both beginners and students wanting to brush up on their R skills.
推荐度：★★★★★
这是一个比较系统学习R的网站，作者非常认真并且专业，通过视频、ppt及作业等，系统完整的阐述了R的数据分析生态。
课程特征：
- 开源：
TRUE - 文字教程：
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MID
发布者：
Ted Laderas laderast/ready_for_r_site: Ready for R Site (github.com)
曾就职于Oregon Health & Science University(OHSU)，在和他邮件的交流中，得知他去年离职，现据说就职于DNANexus。
STAT 545
Data wrangling, exploration, and analysis with R
These materials originated in the STAT 545 course at the University of British Columbia.
This site is about everything that comes up during data analysis except for statistical modelling and inference.
推荐度：★★★★
University of British Columbia大学的课程，完整的课程可以访问STAT 545 @ UBC
课程特征：
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MID
发布者：
The main author, Jenny Bryan (jennybryan.org), developed this version of STAT 545 as a professor at UBC. She has since joined RStudio as a Software Engineer, on the tidyverse and r-lib teams and is an adjunct professor at UBC.
BASV - biostat2 (uni.lu)
Introduction
- Give students an introduction to the programming language R
- Bridge previously obtained theoretical knowledge in the field of Statistics with practical applications to biological data
- Provide strong practical skills in the analysis of large-scale datasets with RStudio
推荐度：★★★
基本上只有ppt，是用R Markdown生成的，并且不好获取源码。一直没有持续更新。
课程特征：
- 开源：
FALSE - 文字教程：
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FALSE - 难度：
LOW
发布者：
R Basics | Have you ever wanted to know how to use R?
This course is designed to cover the very basics of using and working with R. It will be taught with the following sections:
- Getting Started in R and RStudio
- Data in R
- The Tidyverse
- Graphing Data in R
- Modeling Data in R
- Communicating and Publishing Data in R
推荐度：★★★
比较简单的课程，完全按照R生态来开展的数据分析流程。Stats Education教程的一个分支。
课程特征：
- 开源：
FALSE - 文字教程：
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FALSE - 难度：
MID
发布者：
Adam J Sullivan
Assistant Professor of Biostatistics, Brown University
He is currently director of the Masters program in biostatistics at Brown University and the faculty statistician at the Hassenfeld Child Health Innovation Institute.
DARTISTICS:Digital Analysts: R and staTISTICS!
This site is intended to be a resource for digital analysts who are interested in learning or expanding their knowledge of R and statistics.
推荐度：★★★★
这个教程更佳系统全面，可以说覆盖到了R的整个生态，R Markdown和Shiny都有所涉及。
课程特征：
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FALSE - 难度：
HIGH
发布者：
This site is developed and maintained by Mark Edmondson and Tim Wilson, with semi-intentional assists from Donal Phipps, Dr. Michael Levin and others.
RBootcamp · A free online course about the basics of the tidyverse
The R-Bootcamp is a gentle and gradual introduction to manipulating and visualizing data in R using the tidyverse suite of packages.
推荐度：★★★★★
tidyverse 交互式课程，让你快速上手R语言的王者包tidyverse。
课程特征：
- 开源：
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LOW
发布者：
Ted Laderas and Jessica Minnier.
Predictive analytics and machine learning
Data Science and Predictive Analytics (UMich HS650)
The Data Science and Predictive Analytics (DSPA) course (offered as a massive open online course, MOOC, as well as a traditional University of Michigan class) aims to build computational abilities, inferential thinking, and practical skills for tackling core data scientific challenges. It explores foundational concepts in data management, processing, statistical computing, and dynamic visualization using modern programming tools and agile web-services. Concepts, ideas, and protocols are illustrated through examples of real observational, simulated and research-derived datasets. Some prior quantitative experience in programming, calculus, statistics, mathematical models, or linear algebra will be necessary.
推荐度：★★★★★
来自University of Michigan，针对生物医学领域最全面最系统的分析课程。如果你想系统学习，这个课程不可错过
课程特征：
- 开源：
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FALSE - 难度：
HIGH
发布者：
University of Michigan
Supervised machine learning case studies in R! · A free interactive course
In this course, you will work through four case studies using data from the real world; you will gain experience in exploratory data analysis, preparing data so it is ready for predictive modeling, training supervised machine learning models using tidymodels, and evaluating those models.
推荐度：★★★★★
监督机器学习的案例，交互式学习，轻松上手。我个人非常喜欢她的课程。
课程特征：
- 开源：
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MID
发布者：
Julia Silge
A data scientist and software engineer at RStudio where I build modeling tools. I am both an international keynote speaker and a real-world practitioner focused on data analysis and machine learning practice. I love making beautiful charts and communicating about technical topics with diverse audiences.
其他资源
learnR4free
You can find all sorts of resources (books, videos, interactive websites, papers) to learn R. Some of the resources are beginner-friendly and start with the installation process.
汇聚了一些R学习资源
Posts | Craig Hutton, PhD
Dr. Craig P. Hutton个人网站
I am a scientist working within the domains of machine learning and mental health. My diverse background in behavioural neuroscience, applied statistics, and epidemiology leads me to apply a multidisciplinary and creative approach to doing research. I deeply enjoy solving complex problems and exploring new ideas.
他写的Posts | A Scientist's Guide to R，非常不错。
Big Book of R
R开源图书的资源王者
bookmark every R-related programming book
Happy Git and GitHub for the useR
Happy Git provides opinionated instructions on how to:
- Install Git and get it working smoothly with GitHub, in the shell and in the RStudio IDE.
- Develop a few key workflows that cover your most common tasks.
- Integrate Git and GitHub into your daily work with R and R Markdown.
STAT 545 附属课程，教你如何在R中使用Git
Data Carpentry
Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Our mission is to provide researchers high-quality, domain-specific training covering the full lifecycle of data-driven research.
各种数据分析的workshop，基本都是基于R的。
**粗体** _斜体_ [链接](http://example.com) `代码` - 列表 > 引用。你还可以使用@来通知其他用户。