Roger D. Peng, PhD
Writing good code for data science is only part of the job. In order to maximizing the usefulness and reusability of data science software, code must be organized and distributed in a manner that adheres to community–based standards and provides a good user experience. This course covers the primary means by which R software is organized and distributed to others. We cover R package development, writing good documentation and vignettes, writing robust software, cross–platform development, continuous integration tools, and distributing packages via CRAN and GitHub. Learners will produce R packages that satisfy the criteria for submission to CRAN. 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.
Instructor Details
Courses : 4
Specification: Building R Packages
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48 reviews for Building R Packages
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 13 hours |
| Year | 2016 |
| Level | Intermediate |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
Jose V D –
Just reading. There are not videos. You are not allowed to submit the quiz if you do not pay.
Zdenek K –
I liked the course a lot since it is actually covering most of the things related to the package development. Nevertheless, I still feel (the same as with the previous classes) that authors could have spent more time building the course materials as many chapters are very brief and if I hadn’t had the past experience with some of the topics, I wouldn’t have any idea what the course is telling me (e.g. merge conflicts in git).
Moises E –
Very good course for intermediate/advanced R users. Sad that you are elegible to do assignments only if you pay.
William G –
This was a great challenging course! Love it.
Christopher B –
This is a critical skill and it’s barely covered anywhere else. Thanks for making this course!
Josef T –
Course material is a bit light, missing useful pieces of information. The example code is functional but not of sufficient standard to pass the documentation exercise. The solutions to the exercise are not covered in the course material. It takes a lot of outside work to get a good mark. Course is good, but the material needs a bit of work.
Carlos C –
Easy at first, very challenging at the end. Some of the course materials really need to be updated and expanded. Mentoring should be improved (include mentors on this course).
Jose E L –
Very interesting and usefull.
KEVIN E A C –
It was a very challenging course at least for me but i think it is not necessary.
Gustavo B –
It’s one of better course for building packages!!!
Arthur G –
Informative and gives lots of information
Kevin D –
You will learn how to develop, publish and maintain a R package, and it’s quite an interesting skill that will change the way you manage your code (you’ll probably always store your code in documented packages you’ll host on gitHub then). Though it’s a pertty hard MOOC for many reasons : quite inactive community, information you’ll get in lessons isn’t enough to complete assignments, course material is just book you’ll have to read (no video, no interaction), you’ll probably have the feeling you’re going through something that’s not really finished. Don’t follow this MOOC if you want to avoid being frustrated because most of the time you’ll be.
Mai A D –
The materials is not logical and not enough. It makes a lot of difficulties for the learners, especially through self learning and online learning.
Rebecca G –
This course was not great. Almost all of the information is a screen scrape from a book and peer evaluation, so you may be better off just getting the book and going through it. The mentors very occasionally participated, the authors never. The assignments are poorly written and missing too much detail.
Francesco D Z –
very useful, especially the final practical exam
Jay B –
The difficulty of the c ourse will depend on your background. If you have software development experience plus git, the course details the steps of releasing an R package to the community. If you have never worked with git or released software, this is a good way to tie those skills to your R skills.
Gregorio A A P –
Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.
savvas s –
just links to a webpage… no support from the mentors no support form coursera… you can use your money more wisely..
Conner M –
Good course, but very specialized programming knowledge in this particular course, which was not the case with other courses in the specialization. Would only recommend this course for those with the necessity to build R packages.
Cardy M I –
Overall, this was a good course to learn the intricacies of building R packages.
Maurizio C –
Great gap between teaching and what is required to pass the course. Unnecessarily difficult. Not recommended.
JEEWESH K J –
Great course
Jason S –
R packages are essential learning. This class covers packages including documentation, vignettes, testing, building, and checking for compatibility with CRAN. It also gets you into git and travis (for continuous integration), with an entire side of open source philosophy and legal. If you can pass this, you *will* be able to create and maintain an R package.
RafaB G –
The amount of uncovered yet crucial issues is too damn high. For week 4 assignment I did most of my research on stackoverflow.
Rafal G –
The amount of uncovered yet crucial issues is too damn high. For week 4 assignment I did most of my research on stackoverflow.
David C –
This course provides useful knowledge in building R packages, as well as opportunities to implement our knowledge. However, as the previous courses in the series, the last module (week) is extremely challenging compared to the previous ones.
Edmund J L O –
This course really boosted my confidence in writing codes, functions and i look forward to someday writing my own package. The course left me on such a high note that I made a couple of presentations using the plots in my vignette. I wanted to somehow show my appreciation to the authors of the course. The choice of a real life dataset made it really very interesting for me. Here’s the link to the presentations i made. I’m not sure if it should be shared with your students, so i’ll leave that up to you. Thanks again for making learning so much fun. BTW, it was a bit of a cliffhanger for me. I only got my package to pas travis at the last minute. Here are the links: http://rpubs.com/DocOfi/350304 and http://rpubs.com/DocOfi/350099
Igor P –
Basic course no more then that
James M –
Good slow walk through of the process for creating and checking a package
Tim S –
Iam actually waiting for over one week to get graded. I dont want to pay for waiting!
Johans A A –
I learned a lot in this course, was difficult at the begininng but enjoyable at the end!
Jonathan D –
Poor course material made it difficult to complete the final assignment. The course has little to do with R and more to do with Software development methodologies.
Eduardo B G –
The content was good but I have missed the videos. I can read a book, the experience with video demonstrations is better than this aproach.
Ganapathi N K –
Nice
Damian S –
Among the worst courses I have found on Coursera. Once again, just a bunch of text, cut and pasted (sloppily) from their book and other resources. Examples are poor and insufficient, and much of what they ask you to do in the project is not covered well, or at all in the course forcing you to learn on your own. I don’t object to self education, but then, why bother taking this course? Can’t believe they are charging money for this.
Abhinav S –
Amazing course! Will explain every detail regarding R package creation.
Zsolt P –
The material is not bad, however, this is just a refurbished version of a corresponding book written by the authors. Literally, all the readings are just excerpts from this book with typos all over the place. Save some money and just read that, I think this is a minimal extra work cash grab and you feel that all throughout. The final project is fine but not too fun (and the reading material is insufficient for it), it isn’t worth the money either.
Jorge L R Z –
Great course!
Anthony S –
I finally started building R packages!!! Lots of useful bits
Matthew M –
good but needs a little updating several commands this teaches you to use are now depracated.
Yi X –
There are not so mang classmates for peer reviewing. Please set other alternative ways for grading
Shawn M –
There is much I like about this course and also many areas for improvement. First, the online book that comes with the course presents an excellent overview of the steps required to build an R package. It will eventually get you where you need to go. However, some of the material is now out of date (e.g. functions moved from one package to another), there are no longer any mentors around, and the discussions boards are empty apart from people trying to get their assignments peer graded. Also, the content in the book, while good, is incomplete in many cases. I would highly suggest buying the “R Packages” book by Hadley Wickham as an additional reference since it fills many of the gaps and goes into much greater detail.
konstantin m –
Fantastic course… Unfortunately, not too many people registered, it’s tough to get your assignments graded. The program is the great continuation to the 10 course R data science specialization…
George L –
Lots of outdated material and no mentors remain to assist. Documentation is incomplete and left to the user’s imagination. There have got to be better courses than this.
Nour E Q –
very good, an interesting way of learning. high level examination
Jean–Philippe M –
Whish we would have a video going through all the steps (real case example) to show how to build, test and use travis on a package.
Jean Philippe M –
Whish we would have a video going through all the steps (real case example) to show how to build, test and use travis on a package.
Christopher M P –
Final assignment may not be reviewed for weeks. If you go on to capstone, issue could extent into months. Expect to use many external resources.