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Avis et commentaires pour d'étudiants pour Building R Packages par Université Johns-Hopkins

4.1
étoiles
200 évaluations
52 avis

À propos du cours

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....

Meilleurs avis

KM
3 juin 2019

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...

ME
15 janv. 2017

Very good course for intermediate/advanced R users. Sad that you are elegible to do assignments only if you pay.

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1 - 25 sur 51 Avis pour Building R Packages

par Shawn M

15 févr. 2019

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 However, some of the material is now out of date (e.g. functions moved from one package to another), there are no longer any mentors around, and the discussions boards are empty apart from people trying to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.

par Matthew M

14 janv. 2019

good but needs a little updating - several commands this teaches you to use are now depracated.

par Edmund J L O

20 janv. 2018

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

par Rebecca G

23 juil. 2017

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.

par Jonathan D

3 avr. 2018

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.

par Jason S

27 nov. 2017

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.

par Jay B

5 août 2017

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.

par Youdinghuan C

25 déc. 2017

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.

par Konstantin M

4 juin 2019

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...

par Moisés E A

16 janv. 2017

Very good course for intermediate/advanced R users. Sad that you are elegible to do assignments only if you pay.

par Gregorio A A P

26 août 2017

Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.

par Yi X

2 févr. 2019

There are not so mang classmates for peer reviewing. Please set other alternative ways for grading

par Christopher B

30 mars 2017

This is a critical skill and it's barely covered anywhere else. Thanks for making this course!

par Cardy M I

7 oct. 2017

Overall, this was a good course to learn the intricacies of building R packages.

par James M

7 févr. 2018

Good slow walk through of the process for creating and checking a package

par Abhinav S

14 juil. 2018

Amazing course! Will explain every detail regarding R package creation.

par Nour E Q

2 nov. 2019

very good, an interesting way of learning.

high-level examination

par Anthony S

16 nov. 2018

I finally started building R packages!!! Lots of useful bits

par Gustavo B

7 juil. 2017

It's one of better course for building packages!!!

par Francesco D Z

1 août 2017

very useful, especially the final practical exam

par William G

1 mars 2017

This was a great challenging course! Love it.

par Mridul M

12 juin 2020

A great course from a great specialization

par José E L

29 mai 2017

Very interesting and usefull.

par Jorge L R Z

22 sept. 2018

Great course!

par JEEWESH K J

1 nov. 2017

Great course