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Kursteilnehmer-Bewertung und -Feedback für R-Programmierung von Johns Hopkins University

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19,925 Bewertungen
4,266 Bewertungen

Über den Kurs

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....

Top-Bewertungen

JM
11. Aug. 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.

WH
2. Feb. 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!

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251 - 275 von 4,154 Bewertungen für R-Programmierung

von Danie R

19. Okt. 2016

Assumes no prior knowledge, definitely helps if you do, but the course teaches you from scratch, at a quick pace. The videos do have links where you can find more reading material, when needed, although highly recommended. Best money I could have invested.

von Sanjay K S

22. Juni 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.

von John M

15. Jan. 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.

von Brittney B

24. Apr. 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.

von Jonathan D W

25. Dez. 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.

von Dmytro I

8. Apr. 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.

von Kyle S

16. Juni 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.

von Akshay C

13. Apr. 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.

von Daniel O

5. Aug. 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.

von Renzzo S S

6. Nov. 2020

Excellent course, it is my first time in R programming, and with this swirl package I learned a lot, then complete the training with the thinking to complete the assignments that are challenging and are excellent choices since real live is not easy!

von Mayur N

19. Aug. 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.

von Prabhjyot S

23. Juli 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.

von MUNSHI K

6. Dez. 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!

von Taif A

2. Nov. 2020

I didn't know anything about R programming before enrolling in this course. The interactive teaching style (swirl exercises) and the relevant assignments contributed so much to my learning. It was a good decision to invest my time on this course.

von Michael M J

27. Sep. 2020

Very well-taught and well-structured course, with great instruction by Dr. Peng. The programming assignments really helped with the practical aspect of R. Overall, this course is an excellent foundation for the programming aspect of data science!

von Hyungjin K

19. März 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.

von Srinivasan R

19. Okt. 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.

von Subhankar J

16. Aug. 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

von YUTING W

3. Apr. 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.

von badal s

23. Mai 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!

von Luca B

5. Juni 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.

von Hugo S

26. März 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!

von Yatin M

20. Okt. 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.

von James H

8. Feb. 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.

von Juan M E R d A N R

9. Juli 2020

Great course. But please consider including a reading version of the video lecture, (not the same as the transcript) just like in the previous course (The Data Scientist Tool Box). I found those reading versions of the lectures really useful!