CourseraData ScienceFree courseCertificate

R Programming

4.7

422 reviews

Created by: Roger D. Peng

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Overall Score : 94 / 100

Course Description

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.

Time: 20h

Instructor Details

Roger D. Peng

4.7 Rating
422 Reviews

Roger D. Peng is a Professor of statistics at the Johns Hopkins Bloomberg School of Public Health and a Co-Editor of the Simply Statistics blog. He received his Ph.D. in Statistics from the University of California, Los Angeles and is a prominent researcher in the areas of air pollution and health risk assessment and statistical methods for environmental data. He is the recipient of the 2016 Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to health statistics. He created the course Statistical Programming at Johns Hopkins as a way to introduce students to the computational tools for data analysis. Dr. Peng is also a national leader in the area of methods and standards for reproducible research and is the Reproducible Research editor for the journal statistics. His research is highly interdisciplinary and his work has been published in major substantive and statistical journals, including the Journal of the American Medical Association and the Journal of the Royal Statistical Society. Dr. Peng is the author of more than a dozen software packages implementing statistical methods for environmental studies, methods for reproducible research, and data distribution tools. He has also given workshops, tutorials, and short courses in statistical computing and data analysis.

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Reviews

4.7

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By DJM on 12-Aug-19

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.

By Parker O on 19-May-19

Great course, however I think it is particularly hard for those who never had programmed in R before. Moreover I think the Programming Assignments were quite hard regarding the topics being discussed during the weeks.

By LiyaM on 15-May-19

Course content was good, but assignments were too hard and not well linked to the rest of the content. I spent hours online trying to work out the assessments which then leads to the question of why the course

By Maria N on 14-May-19

I have programmed in SAS before (15 years ago), so I thought that experience would be sufficient for me to take this class. I have to say it is not. This class is definitely not for beginners - you must have programming experience, R experience and/or both. The programming exercises do not follow the lectures and it does not build upon concepts. You will be required to seek help elsewhere (i.e., Stack Overflow) and answers to your questions will take days, if not longer. So, the fact that the classes are organized by week means that you will not conclude in the time you believe you will. I feel that this class is more self-taught than anything else. I have decided to quit this class as it has become extremely frustrating.

By Daniiar B on 22-Apr-19

I learned a lot of the R basics, but I was completely lost for the week 2 + 4 'write a function' assignments - they strike at a level too high for a complete beginner for me (and that's after religiously taking notes and completing all swirl exercises.)

By Pooia L on 20-Apr-19

The assignments are too hard. Wish there were more similar example walk-throughs provided.

By Prasenjit P on 17-Apr-19

I would be cautious to recommend this course to a complete beginner. I had been using R for about 6 months before starting this course and found the content challenging. For instance, topics like lexical scoping covered in this course are usually tackled in a more Advanced R course. For a complete beginner into R, I would recommend a book like "R in Action" by Robert Kabacoff or the course on Udemy by Jose Portilla.However, if you have had some exposure to R and would like it to take it to the next level, this is an excellent course. It will force you to learn things on your own. Read the documentation of R functions, peruse through stack overflow and really step up your game.

By Austin C on 16-Apr-19

Nice!!

By Yash G on 15-Apr-19

The course can be little more better for folks who are non programmers to begin with. This is an advanced course for a beginner/non programmer, hence would recommend to have a beginner course for non programmers/ R and then this course should be offered.

By Meichen L on 14-Apr-19