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

4.5
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20,731 Bewertungen
4,451 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

EJ
11. Juli 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!

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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101 - 125 von 4,340 Bewertungen für R-Programmierung

von Juergen K

21. Mai 2020

Not very well organized overall. The assignments were fun, but I had to do extensive research online to find out how to answer the questions being asked, which made me wonder why I had sat through the videos. Sometimes I didn't even use what I learned in the videos to complete that week's assignments. The videos are far too theoretical, they probably would have been useful for someone familiar with R or S, but for a new user they required a lot of rewinding and without practical examples it was hard to actually remember what was being taught. In the rare instance practical examples were given the material stuck much better!

von Gabriela Á L

7. Nov. 2020

The assignments are not gradual, I mean the content of the classes is not enough for the completion of the assignments. I think I would have appreciated more content in the classes, more explained exercises so that the making of the assignments wouldn't have been so miserable! It's a very hard course.

But I've learned a lot on my own, thanks!

von Diego V

24. Aug. 2020

Huge disconnect between the canned lectures (almost all not by Peng) and the exercises. Moreover, other than generating random number distributions, there are no examples of the lecture material worth anything. Given the subjects covered, the course could be great

von Javier C

29. Jan. 2021

The contents of the lectures are quite hard to follow, and exercises do not have much relationship with them. Difficult to follow the course, even with other programming languages skills.

von Biel G P

8. Jan. 2021

The assignments are too difficult compared with the knowlegde taught in the videos and swirl

von Li C W

31. Okt. 2020

I am extremely disappointed with the quality of this course. I am a professional analyst and have some years of programming, I intended to "formalize" my knowledge in R and data science by taking this course. This course is organized in a very poor manner, lectures and assignments are completely disconnected, the instruction in the assignment is also extremely poor, it is very hard to understand what the learner is expected to do, it is very frustrating and I cannot imagine this course is intended for "beginner". I managed to finish that just because it is sponsored by my company. 0 out of 5 stars

von Tom W

30. Aug. 2020

The worse Coursera course I've ever taken. The videos feel like someone reading the technical documentation to you, the "interactive" tutorials are like an 1980s text-only game, and the assignments require massive leaps in ability over what you learned in the lessons. I would call this course "Advanced-level assignments sure to both bore and frustrate people new to R"

von Madhubalini V

3. Okt. 2020

the instructor is like this is ABCD.., and the assignment is like write a report on a topic. the course is too hard for a beginner, then the instructions are confusing.

von wang z

19. Nov. 2017

实在是大大低于我的期望,教学内容和作业完全脱节,使得学生花费了大量时间自己没有头绪的学习,课程本省较为枯燥乏味,缺少实际操作性的演示,大部分是概念性和理解性的知识点,实际操作价值不大。

von Ramalakshmanan S P

23. Feb. 2016

Thanks to Coursera and Prof. Roger D. Peng for offering such a wonderful course on R Programming.

Before the start of this session, my knowledge of R Programming is NIL. After attending the session, I'm confident that I could program in R and level of my knowledge is more than that of fresher. Thanks for the well designed course on R.

The Quizzes and Assignments are good and helped me test my understanding. These helped me improve my confidence level as well. I appreciate Professors special video session before difficult assignment. Just following these sessions closely, I could complete the assignment to my satisfaction and have confidence to attempt and complete.

I completed this course in the old format. Do I need to repeat it in the new format ?

The Discussion Forums are amazingly helpful in sharing subject knowledge and making the learning Fun. Getting help from some corner of the world and getting thanks from some other corner of the world makes this learning truly Universal and great Fun.

Thanks again to Coursera and Prof. Roger D. Peng.

Wishing Coursera and my Professors all the best and Success always.

Best Wishes,

S. Ramalakshmanan

von 张万八Colin

10. Mai 2020

1.The assignment is sophisticated but worth it. I agree with most people that the coding assignments are difficult and I usually spend at least one hour on each function. However, I think this is what makes the course worth it. The videos and swirl sessions are so basic that it only serves as a basic introduction and is barely useful for actual data processing and analysis. The assignments will force you to think about the steps need for building a function to serve your specific purposes.

2. Subsetting is the key and needs to be reviewed over and over again. Personally, I find subsetting in R powerful and a little bit confusing at the beginning. It is really the key to any manipulation of the data sets. Practive makes perfect. I think I will still spend time on reviewing them after the course.

von Emre Y

25. März 2020

This is an outstanding course. As an undergraduate student in the final year of my degree program, where not a lot of programming was covered, this course has really boosted my confidence in using R studio and has genuinely made me believe that I can programme anything I put my mind to. This course has also shown me that with a bit of practice each day, significant progress can be made to a level beyond what one may have imagined. This course has also enhanced my critical thinking skills, as programming needs careful logical thinking. At times, it can be so frustrating when a code is near functional but not quite working the way one intends, and so by persevering and sticking at it you will get there! I am now feeling ready to delve into the scientific world feeling that anything is achievable.

von Alexander W

3. März 2021

Challenging course that forces you to show what you got at the intermediate level in mathematics, statistics and computer science. Even that the SWIRL exercises were optional, it provided the underlying knowledge while the assignments (especially assignment 2 and 4) force you to organize your R-functions to solve the problems. The videos with Prof. Peng at JHU to install R studio, download and configurate the computer software were the easiest part meanwhile reading .CSV-files into R and writing the R-functions were the challenging part. Recommending the course to students who have studied computer science for a while and are bored on lectures with the regular stuff about IF-statements, looping and WHILE-statements. Regards from Sweden

von Oka M S

25. Nov. 2020

I underestimate the lecture and it hit me back right in the face! The lesson is really good, and the assignment is really challenging. Not only we need to learn about R programming, but also some familiarity with git and github as version control method. The mentor respond is swift, additional lecture note from github is also really helpful. But it seems that sometime it will be really helpful if Coursera can facilitate to handle limited live session during lesson period so students can ask and get direct respond from lecturer, and might save hours of searching and experimenting if we can get a good directions at the time in need. Overall, excited to continue learning, thanks Coursera and ITB :D

von Edmund J L O

11. Mai 2016

This is course was pretty hard for someone like me without any background in computer programming. I had to take it twice to pass it. Luckily, there are many wonderful people in Coursera and in R who are always willing to lend a hand. Even if you pass all the basic requirements of the course i encourage you to do an exploration on your own. There are so many things to learn to make your job easy and to give inspiration to improve your performance in whatever field your in. It might feel like you're not learning at times or it's too difficult to continue, but once you get there, you'll realize how this wonderful new tool can help you with data analysis and presentation.

von Zoey

30. Apr. 2018

If there's one thing about this course that beats all the other regular ways to learn basic R (e.g. datacamp, swirl, reading a textbook, udemy, etc.) it is the MCQ exercises and peer-graded assignments. I can't begin to describe how satisfying it is to have to figure out on your own just 5 cleverly written MCQs for hours and then have the answer in the console finally match one of the choices.

Yes, there are other ways of learning R, but I find this one just sticks in my mind and gamifies the whole learning process. This could just be the strength of Coursera's system, I don't know, I haven't done enough courses to tell. But tell you what, I love this course.

von Wei D

11. Aug. 2019

Great class. Lecture was very to the point. I was a bit hesitant on taking this class given my limited programming experience and other reviewer's comments that the homework was significantly harder than the homework. Now that i have completed the class, I mind that as long as I listened to the lectures and did the practice questions, I had no issues completing the homework assignments (granted, occasional google & stackoverflow consult was needed just like any other programming class). I find the course material easy to understand and perfect for a data newb or someone who wants an introduction to data science and processing. Highly recommend this class.

von Tomohiko J M

29. Nov. 2016

This was a challenging course. I have some experience in stats, but no experience with programming so I spent an extraordinary amount of time fumbling through the assignments. However, the effort was worth it. I am far from fluent in R, but I do feel like I know how to talk in R, pose questions about code, and begin to build functions with my knowledge. Have plenty more to learn, but fumbling through this course has definitely given me a good foundation. Tips for anyone thinking of taking the course: read the discussion forums, learn to look for answers online, and be patient if you're unfamiliar with programming languages.

von Garrett F

23. Apr. 2020

I am a programming beginner and this class took me many many hours to work through seemingly simple assignments. When I did arrive at the right answer, I was happy and proud and recognized my growth. I guess that's the nature of programming. I found that the swirl practice assignments were helpful, if not simply enjoyable. In the forums there were a select few mentors that were quite helpful. I did almost prefer the robotic voice of the Data Science Toolbox over the videos that were presented here. I would have not been able to do the final assignment without dplyr knowledge from Getting and Cleaning Data. Continuing on!

von Jonathan B

17. Dez. 2015

I rate this course as the beta-testing (not that I had completed this course prior the beta started).

1) the course is still very good with a lot of explanations and examples

2) I liked the part about debugging because we don't see often this topic when learning a new language.

3) I liked (but it's only a cosmetic thing) that all the slides have the same template/organization ; it's easier later when we looked back at the lessons to find what we search.

4) one (very) minor comment : I watched the videos with subtitles (english) and sometimes it also writes when the instructor thinks "loud", or repeat a word several times

von Paul L

4. Juli 2018

5+ years ago as a graduate student I took a bio-statistics class focused on analysis of NGS data where we used R to do the statistics required in the homework assignments. In that class we mainly used the built-in functions at the console to calculate things like correlation coefficients, but didn't do much real programming or function writing. I took this course because I wanted a refresher in R and because I was interested in learning more about its programming capabilities. From that standpoint I'm really satisfied with the things I learned, especially given the fact that the course is quite short.

von George G

9. Juni 2018

I loved the well-thought-out, tricky programming assignments. At the end, I wish there was an 'answer key' or 'hall of fame' for good examples of solutions to the programming assignments. I understand why they can't do this (oversharing/cheating/watering down the challenge for the next class), but it would be awesome to find out if there was a simpler, more elegant or readable solution. R is full of different ways to solve a problem, so it would help us to 'think in r' if we could see worked examples after we're done. That said, the challenge of the blank page is really where I learned the most.

von Alvin C Y H

30. Juni 2020

Although there are significant disconnection between the level of difficulty of assignments and what is taught in the lecture videos, the assignment proves to be very challenging and would make your R programming skills improve leaps and bounds. Whenever stuck at assignments, I often search Stackoverflow for specific functions and would be able to find answers from there.

Overall, I think this course is suitable for learners who have some background in programming, and I would be continuing to take the specialization courses to find out more about the statistical packages of R like ggplot2.

von huasah23

26. Nov. 2018

This course provides me an overview understanding of R Programming. The professor not only teaches the important programming concepts but also teaches how to learn R programming well (e.g. how to ask good questions in the forum, how to solve problem via different functions). I think the grading of homework is creative and helpful. When I have to evaluate other people's programming work, I had to understand what's going on in the assignment. The swirl packages and each of the homework are time-consuming but really helps a lot for me to better understand and use the R programming.

von VADALI S G

21. Nov. 2016

It was very informative and understandable. This course seems difficult in the beginning as we need to remember various syntactic notations. When you are in such a situation, don't forget to start using swirl. Even if you are a quick learner of syntax, swirl takes your journey like a cake walk as it just plants all the course content into your brain. It is such an interactive,student friendly environment being provided in the course that it makes you fall in love with swirl, course and instructor's methodologies.I am really thankful to John Hopkins university for such a course.