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ジョンズ・ホプキンズ大学(Johns Hopkins University) による Rプログラミング の受講者のレビューおよびフィードバック

4.6
stars
15,783件の評価
3,233件のレビュー

コースについて

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....

人気のレビュー

WH

Feb 03, 2016

"R Programming" forces you to dive in deep.\n\nThese skills serve as a strong basis for the rest of the data science specialization.\n\nMaterial is in depth, but presented clearly. Highly recommended!

JM

Aug 12, 2019

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.

フィルター:

Rプログラミング: 26 - 50 / 3,125 レビュー

by Guilherme O B

Feb 03, 2016

Excelente opportunity to learn a lot. The course is very well prepared introduce you to R programing. Dont feel bad if you dont get it at te first moment. It will be a process of leaning worth trying

by Walter H

Feb 03, 2016

"R Programming" forces you to dive in deep.

These skills serve as a strong basis for the rest of the data science specialization.

Material is in depth, but presented clearly. Highly recommended!

by Jacob T

Apr 03, 2019

This is an excellent course but be warned, the programming assignments are difficult. If you do not have any coding experience, the assignments may be a bit challenging for you. But with the help of the internet and Github, you can complete them with no problems. The course content is great. All the videos and information are for beginners and are very helpful. The best part of the course was the swirl exercises it had you complete in R. Swirl exercises acquitted you with the programming needed for success in R. Overall it is a great course. Just understand that the programming assignments can be challenging for new timers.

by Kerryn A M

Oct 08, 2018

I learnt a lot, but most assignments required me to look a lot of stuff up outside of the course. They say they have done this deliberately to encourage "hacker mentality". I agree that we need to learn how to cope on our own, but it ends up taking up hours of your time and seems like a pointless lesson. One reason for doing a course like this is so that you can have access to consolidated and trusted learning materials, which was not really provided. Having said that, the assignments are a good way to push yourself to learn R. But most of what you need to do the assignments will not be provided within the course.

by Matthew W

Oct 05, 2018

The assignments were way beyond the scope of what was taught in the lectures.

by Nouran G

Feb 14, 2019

Assignments are hard compared to the content

by Sotirios T

Oct 14, 2018

Programming assignments are very hard (and in some cases irrelevant) based on the material presented and topics discussed

by Rushi P

Apr 01, 2019

Gave to little instruction and expected the assignments to be completed based on very little instruction

by Jeremy T

Sep 30, 2018

If I wanted to learn from outside source and "hack" my way through understanding, I would not be paying money for this course. I am paying money as I expect a smooth introduction and summary to the topic which it is not. I have taken classes in SQL and python on courser. Those were of better quality. I think this R class is one of the worst.

by Brian W

Feb 20, 2017

Damn near worthless. The course material has significant gaps of information. The programming assignments require knowledge that isn't presented in the course. I had to Google my way through this entire course. I would not recommend it.

by Shreya S

Feb 27, 2019

Brilliant content!! Practice exercises really help you evaluate yourself. A little knowledge of R programming before this course is helpful as that might help understand the slides better. Though it is not mandatory but one can still utilize free resources available online to build the basic knowledge. Also, if you have prior experience with any programming language, that'll be very helpful. Would highly recommend this course.

by Justin M

Aug 12, 2019

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 WHAT

Apr 16, 2019

Nice!!

by Gaby R

Oct 24, 2018

The only feedback I have is that they should try to incorporate more examples (simple real world ones would be great) when explaining concepts in R, because otherwise it is quite dry. The things you learn in the individual lectures give you a very basic idea of the functionality without much insight on *why* its important or *how* it can be applied...I found most of my solutions/answers by googling and using swirl a bunch of times. However it is rewarding if you power through it and have A LOT of patience, especially if you are a beginner with no background in programming (like myself).

by Ong W J

Oct 06, 2018

This course is tough if you have zero background in programming. I struggled alots especially in the last assignment.

by SEEUN H

Feb 04, 2019

Nice, but limited explanation for beginners.

by Yaw O

Feb 02, 2019

Some concepts weren't clearly discussed

by Suwei W

Jan 02, 2019

I learned something, of course, in this course. But without previous experience in data science, I found it OK to understand the lectures, but always got lost in the coding assignments. I tried to finish it on my own, but it turns out I have to search everything online. I felt that there's a big gap between lectures and assignments.

by El M

Apr 09, 2019

very good course but you need much more time then announced to finish the assignments

by Jueyi S

Jan 07, 2019

Tutorials are indispensible for students to complete the assignments.

by Sherif A

Jan 01, 2019

Needs to be more interactive

by Tareq R

Sep 17, 2018

I think for a MOOC, this course could have used the power of video a lot more, listening to the videos that are basically voice over a slide , wasn't helpful at all, and if it wasn't for the book, I wouldn't learn anything.... if the videos were more illustrative and visual to explain certain concepts , that would have been much better

by Javier P

Dec 08, 2019

Very poor material. Very theoric, no interaction, interesting applications or examples, and very boring lectures.

The material is very trivial, without real applications.

The assessments were useful but in some cases they were not related with the topic.

by Kristofer R

Oct 31, 2018

R Programming assignments were much more complex than what the tutorials taught. There was a very drastic jump between the two and was very difficult/frustrating to complete, especially for someone with no coding experience.

by Tural D

Dec 14, 2019

My overall evaluation for that course is 1 stas due to main two reasons:

First of all course has too much information without the applying during the weeks. However once a learner opens the assignment it is inevitable to face with very hard tasks

I spent more time on youtube and other sources to learn how to use the functions and solve the assignments in comparison with the course itself. That is the reason I am not satisfied with the course.

Given theory is okay but the applying of them during the week is very less. THat is the reason learner face big issues during quizzes.

I found SWIRL assignments very useful that I can say they were the only things that I learned the practical part of R programming.

My advice is to increase the number of SWIRL assignments and increase the difficulty level of them each time.

It is also better to decrease the difficulty level of assignments and quizzes. Because course is more theoretical than being practical in teaching. but the assignment requirements are more practical.