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Avis et commentaires pour d'étudiants pour La programmation en R par Université Johns-Hopkins

4.5
étoiles
17,929 évaluations
3,772 avis

À propos du cours

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....

Meilleurs avis

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!

EJ

Jul 12, 2016

Excellent course! I already knew a lot about R - but this class helped me solidify what I already knew, taught me lots of new tricks, and now I have a certificate that says I know `something' about R!

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226 - 250 sur 3,665 Avis pour La programmation en R

par Sanjay K S

Jun 22, 2016

tutorial contents suit the first timer very well, ofcourse i used the R-programming book for further reading but the contents in this course suited my speed and awareness.. was able to learn R very effectively, specially the swirl was very good experience.

par John M

Jan 15, 2017

Great course to get your feet wet. As a complete beginner to R with a very small amount of prior programming experience, the programming assignments took me around 4-8 hours each. The swirl() exercises were very helpful in reinforcing lecture information.

par Brittney B

Apr 25, 2020

This course was well-structured and very useful! I have only been programming in R for a few months and I found this very informative and a great way to learn! I would 100% recommend this course and will be continuing on with other courses in the series.

par Jonathan D W

Dec 26, 2019

Really enjoyed this course and found it both challenging and informative. After having taken it, another user's advice seems appropriate: Watch the lectures, but reserve your time for the assignments. They can be tough, but that's really where you learn.

par Dmytro I

Apr 08, 2017

Great course! It is the second course of the Data Science Specialisation I have finished so far, and I really enjoy how it goes. However, in my option, some assignments lack clear instructions, what still does not prevent students to complete the course.

par Kyle S

Jun 16, 2017

Great introduction to R programming. Much more rigorous than other primer courses. The quizzes and project really make you think, and you feel like you accomplished something at the end. I would highly recommend this course to anyone wanting to learn R.

par Akshay C

Apr 13, 2017

The course structure is very well crafted. The pace and learning curve goes smoothly although starting third week, you would need external resources for help. You do get to learn a lot about R as a computational language with great hands-on experience.

par Daniel O

Aug 05, 2016

Excellent and challenging introduction to programming in R. Plenty of materials to help you along the way and the course is delivered at a reasonable pace in a friendly and clear manner. Would highly recommend if you want to get into programming in R.

par Mayur N

Aug 19, 2019

Great course as an introduction to R programming. The course provides a base on which I could build upon. I enjoyed the programming assignments which exercised my ability to troubleshoot problems and search for answers on google and stack overflow.

par Prabhjyot S

Jul 23, 2019

I find the course very interactive. I want to say thank you to the team members of John Hopkins University for their hard work. I always feel pleasure in learning new things and Coursera has given me this opportunity by creating this MOOC platform.

par MUNSHI K

Dec 06, 2019

Best course I have completed on R. As a new bee in R language, assignments was really a tough challenge for me. Now I have gained basic understanding of R language and I hope to do an advance course on R as well in future from Coursera. Thank You!

par Hyungjin K

Mar 19, 2018

Such a nice introduction to R Programming! I urge you to take this course if you need essential guides to enhance your coding skills and programmer's mind. Assignments are challenging but rewarding enough to bring you feelings of accomplishments.

par Srinivasan R

Oct 19, 2017

The last exercise was excellent (Week 4). Each question exposed the chinks in our code. This challenged the learner to refine the code to plug all holes. However, what I am not sure is how effective is my coide against failures and against speed.

par Subhankar J

Aug 16, 2017

the assignments might be a little bit difficult for beginners to start with but that is what which will trigger a hacker in you and in turn will compel you find the answers and explore new and innovative ways of solving highly convoluted problems

par YUTING W

Apr 03, 2016

You can learn basic functions of R and do practical assignments on your own. However, the assignments are a little bit challenging, and students need to take some time to figure it out, especially for people who are not familiar with programming.

par badal s

May 23, 2020

Undoubtedly the best course on Coursera! This course is great fun, challenging, and loads of learning! I highly recommend this course to all the learners! Thanks to the instructors and the Johns Hopkins University for such a magneficient course!

par Luca B

Jun 05, 2020

Very useful course for beginners and intermediate users of R. It gives some very important insights about the infinite potential of this programming language. Definitely recommended for people who use R for professional and/or academic reasons.

par Hugo S

Mar 27, 2020

Great introductory course in R. Swirl is a very good introductory method for learning R by 'doing it'. The set of exercises were great (allow us to explore R in a more deep level), with very detailed and easy to follow instructions. Recommend!

par Yatin M

Oct 20, 2016

Excellent introduction to R Programming...whether you are taking it stand-alone, as part of the data scientist specialization or want to ease into the machine learning side of things . The swirl() exercises are a helpful add. Kudos to the team.

par James H

Feb 09, 2016

This course provides a great overiew to introductory R programming. Since taking the course, I have successfully used the precepts learned here for a number of analysis projects. Coupled with ggplot2 graphics, the results became self-evident.

par Marely T R A

Apr 24, 2019

Great course, I loved the SWIRL module. It was awesome. The videos were great and the examples really well though. The instructor has a great voice, he should consider a side job as a narrator, he could do it great.

Honestly, I just loved it.

par Akshay W

Jun 27, 2020

I like this course so much.just because when I was doing this course I have learnt so many thing that will help me in future and thankyou so much sorry for giving me this opportunity.i will surely do more course and learn new thing from you.

par Gerson G

Apr 27, 2020

This course will provide you with fundamental knowledge about R. It does not only teach you how to do things, but why to do them and it also covers how R works behind the scenes. This is valuable knowledge for anyone wanting to work with it.

par John M M

Dec 07, 2017

It was a nice programming course to start with although did not have prior skills in programming. I believe that I will use the knowledge to improve my programming skills and hopefully become a data scientist and an expert on R programming

par Rick B

Feb 07, 2016

This course was set out in such a way that it was very easy for me to follow. I hope that all the courses in this Specialization will be as well planned and structured as this one. It was very easy to learn the very basics of R programming.