Introduction to R (The Course)
Introduction to R
This Course is part of the following Course Sets:
Data science is one of the most exciting and fastest growing careers in the world. The goal of this series is to help people with no background and limited resources transition into data science. It would be helpful to have already taken our Introduction, Organizing Data Science Projects, and Version Control courses. We guide you through the rest!
After taking this course you will be able to:
- Describe what the R programming language is
- Log in to RStudio Cloud and use the R programming language
- Load and use R packages
- Perform the basic commands you will need to start using R
Things you need to do this course
This course is designed for people with no background with Chromebooks or with R. It would be helpful if you had already taken our Introduction, Organizing Data Science Projects, and Version Control courses. But we don't assume prior programming experience. This should be a great introduction to Rfor high-school students or people looking for a career change into the tech industry. The only requirements are:
- A computer with a web browser and an internet connection
- The ability to type and follow instructions.
- The appropriate accounts set up in our earlier courses.
How you will be graded
The course has a series of short quizzes, one for each chapter. You will get two attempts at each quiz and your best score for each quiz will count toward your final score. If you receive more than 70% of the points across all quizzes you will pass. If you receive more than 90% of the points across all quizzes you will pass with honors. You get two attempts at the class with each class purchase.
How to report an error
If you find a bug, typo, or issue in the material, feel free to contact us using this form.
- What is R?
- RStudio Cloud Tour
- R Packages
- Objects in R
- Basic Commands in R
- Working with Logicals
- Lists and Data Frames
- Writing Functions in R
- R Markdown
- Getting Help in R
- Pushing Code from R to GitHub
- Creating Websites with R
Jeff is a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. His group develops statistical methods, software, data resources, and data analyses that help people make sense of massive-scale genomic and biomedical data. As the co-director of the Johns Hopkins Data Science Lab he has helped to develop massive online open programs that have enrolled more than 8 million individuals and partnered with community-based non-profits to use data science education for economic and public health development. He is a Fellow of the American Statistical Association and Mortimer Spiegelman Award recipient.
Leslie obtained her PhD in biostatistics from the Johns Hopkins Bloomberg School of Public Health and is currently an Assistant Professor in the Department of Mathematics, Statistics, and Computer Science at Macalester College.
Sarah is Human Genetics PhD student in the Institute of Genetic Medicine at Johns Hopkins. She studies the role of regulatory variation in neurodegenerative and neuropsychiatric diseases, like Parkinson disease and schizophrenia.
Leonardo Collado-Torres is a Research Scientist at the Lieber Institute for Brain Development. He has been learning and using R & Bioconductor since 2008 and works analyzing genomic data. Leonardo occasionally writes blog posts, is a co-founder of the LIBD rstats club and the Community of Bioinformatics Software Developers (CDSB in Spanish), and is a member of the Bioconductor Community Advisory Board.
This course has a private forum for learners who are taking this course.
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