11 de ago. de 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.
11 de jul. de 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!
por Kira B•
2 de jun. de 2016
This is not a course for a beginner in programming. If you are interested in learning R, I would recommend going to DataCamp and starting there. The lecture videos were not engaging, and the jump from the lecture and quizzes to the programming assignments was quite significant (as others have pointed out). The lecturer for this course does have a pre-programming assignment on his GitHub repository to aid in the first programming assignment, but this was not easy to locate nor advertised well (had to scroll through discussion forums before I saw someone mention it). The swirl assignments were the only saving grace for a class that was otherwise not engaging or structured well. The class could stand to be restructured: for example, it would have been nice for the lectures to cover the str() function before our first programming assignment. Overall, this class does seem to be a good choice for a "refresher" course if you already have some experience coding in R, but be wary if you have little to no programming experience.
por Ellen M•
5 de dic. de 2017
I would only recommend this course if someone were to audit it, and not pay for the certificate and access to the assignments. This course states that it's for beginners, but I would disagree. While the lecture material was helpful for me, someone with little background in programming, the assignments seemed poorly fit to the course. There was a very large gap in what is learned in lectures and what is meant to be applied in the assignments in order to pass. I understand the instructors want to cultivate the so-called 'hacker's mentality' within the students, but I felt I did not get what I paid for. I wasn't anticipating to pay a fee for this course only to have to go and spend a lot of time on google filling in gaps that the instructors did not cover in order to pass, and still not understanding the assignments fully. I think this isn't conducive to great learning for beginners (as this course stated it's geared towards), and for this reason I wouldn't recommend this course.
por xuedi w•
21 de mar. de 2017
This course is very bad. I would like to say this course sucks compared with my sql course no matter how it is structured or how the instructor conducted the course. The instructor is very boring and does not explain very clearly. Even when I start, he does not clearly clarify how to start to use R. He was just talking about what the powerpoint shows. I will absolutely not recommend this course if you are beginners. (0 STAR)
I will give a little credit to swirl, a practical tool provided by this course to learn R by yourself thought the instruction of the R program itself. But for the later part of swirl, it's confusing sometimes. However, I learnt much more from swirl rather than from the instructor. I can't understand what he is talking about but you have to make it clear thru using swirl. He said the swirl is an optional part but he does not realized what he shows is much worse than swirl. (2 STARS)
Overall, I don't recommend this anyone, especially if you are beginners.
por Gianluca M•
9 de jun. de 2016
Poor quality. A disappointing experience.
The lectures are very basic, thought for people that have no experience in programming. This might be ok, but the difficulty of assignments should follow; instead, they can be relatively hard; newbie programmers will probably have an extremely hard time solving them, considering that many of the problems they will encounter are not treated at all in the course.
The course does not focus enough on what differentiates R from other languages: just a few videos on data types, *apply functions, and a tiny little bit of scoping (very unclear). All these areas should have been expanded, and the course should have had more arguments as well.
Finally, the assignments are not enough and their grading system is quite poor: instead of submitting your code and testing it automatically, you should calculate some quantities by hand and select the results out of a few possibilities.
All in all, I was disappointed with the course.
por Jaymes P•
12 de oct. de 2020
Althought there is a lot to learn here and the instructor knows their stuff, I am disappointed in this course. First, I recommend going ahead and having the computer give most of the lecture, except for maybe the introductions to each week to keep it personalized. The instructor repeats "um", "uh", and "so" far too much (2-4 times per sentence) and it's very hard to focus on the lecture.
Second, the assignments do not match the material taught, and there is no scaffolding. I have a Ph.D. in quantitative sociology and eight years of statistical coding experience (not in R) and I think that is the only thing that got me through the assignments. I'm sure I would have been completely lost if I had no programming experience. It makes no sense to me why the instructor doesn't slowly build the assignments in difficulty, but rather throwing students in the deep end analyzing data from 322 different datasets.
Please improve this course for future students.
por deidre h•
2 de feb. de 2016
This is a challenging course because there is a marked gap between the video lectures and the weekly assignments. This course will be far more demanding of your time and willingness to fail that the Data Scientist's Toolbox. If you have the time and resilience to search out support materials and frequently peruse the Discussion threads, you will be able to find what you need. My peers with programming experience confirmed that there is too wide a gap between the content delivered in the video lectures and the demands of the coding assignments. If you decide to take this course, be sure to do the swirl exercises so you get a feel of how the R functions work. When you grade your peers' work, you might notice that more than a few decided to plagiarize code from others.
The videos need to be redone. Effective instructors know that students learn by seeing examples, not by listening to broad descriptions of what a function can do.
por Ping Z•
26 de sep. de 2016
From my past experience, I know it’s not easy for people to take suggestions. But I still want to have a try this time.
I had high hopes for this course, but I am quite disappointed. I think Dr. Peng needs to improve his teaching skills.
1. Good teaching is clear, concise, and right to the point. So please slow down, speak. Don’t mumble.
2. Programming is a practical skill. So the best method to learn programming is to use step-by-step demos. You can talk about a concept for 5 to 10 minutes but I still can’t get it. Use a demo and I can get it right away.
3. Don’t just try to cover the materials so you think you have done the teaching, try to understand how your students learn and make sure they really get it.
4. If you haven’t covered some concept, don’t assume your students will understand it by magic.
A good teacher can make the learning experience effortless and fun, a poor teacher makes it like a torture.
por Rob B•
26 de oct. de 2016
This course is "1-dimensional" and not of high didactic quality. I have followed several other courses ( also Python in Coursera set up) and this one really disappointed me ( I'm in wk 2 out of 4 now). It is a bit of a pitty that the instructor speaks too rapid ( it is ment to be also for non-native US speakers?). The material is hardly explained step by step. So what I do at the moment: I watch the video and than go to Yuotube to find other videos that deal with the topics in an easier and didactic better way.
Examples of good cousres in my opinion are stats and probabilty course/ and the python course
PS "all of the data toolbox" course seem to have the same flaws.
Of course my knowledge level is low concerning programming ( I am a MD, so hardly scientific educated...). Nevertheless I hope this feedback can be of any good.
por Phillip C G•
13 de may. de 2020
This course features great Swirl exercises and decent if bland lectures. Unfortunately the homework assignments are highly problematic. They (a) do not build enough upon what is taught, (b) all too often require skills that have not yet been taught, (c) are extremely advanced for what is supposed to be a beginner R programming course and (d) often require you to look up things in Google rather than in the class lectures or exercises. You can easily put 20 hours or more into this course per week and still struggle to complete or pass it. I would recommend beginning R programmers to steer clear until they improve the assignments.
If however you're a more experienced R programmer this might be a worthwhile challenge, but I would caution that the assignments are not well-tied to lectures and exercises.
por Alla C•
25 de ene. de 2016
I am very frustrated by the disconnect between the lectures and programming assignment in this course. The lectures are very basic, but that makes sense for an intro-type course. The programming assignments, however, have very little connection to the lectures. I have some experience using software with command-based interface (including R) for statistical analysis, and I am relatively good at searching and finding information independently, but this course was way too hard even for me. I might revisit programming assignments again once I have more time and more experience with the application, just for the sake of completing the course, but I kind of find it silly that I need experience with R to pass the course intended for people with little to no experience with R.
por C E•
15 de abr. de 2018
Some of the assignments in the course require coding that is quite a bit more advanced than what is taught. I felt there was insufficient direction and instruction provided in how or where to begin to complete the homework in week 4 especially. This made the homework quite frustrating for me as a true beginner in R programming, and as someone with limited programming experience. I spent a maddening amount of time wandering the stacks and wondering how to even do what was being proposed. If you are a genuine beginner in R and do not have a lot of experience programming in some other (possibly related) language I would hesitate to sign up for this course. It is my opinion that previous experience really is required for the course to be accessible.
por Janet K•
8 de may. de 2017
For my level of expertise in programming, there were huge jumps between what was explained about the R language in the lessons and what was expected from the programming exercises. So I needed to spend A LOT of time Googling and studying various examples on the web, and then, just trying again and again and again. No way could I have passed the course in a month if I hadn't been retired and been able to drop everything else to put in the time I needed. I did learn a lot, but, would have preferred to do it with less wear and tear on my stomach lining.
Also RStudio is not quite as stable or unbreakable as I'd like, nor is there any real way to get feedback on programming style when just getting the answer took 98% of my available time.
por Yun C•
25 de sep. de 2016
There are huge gaps between learning materials (videos) and assignments. Assignments are very difficult and definitely not for R beginners. Also assignments' instruction are a little difficult to understand. I wonder if the purpose of assignments is to exam our reading and understanding abilities or the skills of R!!!
I also took courses <Getting and Cleaning Data> and <Exploratory Data Analysis> at the same time and these two courses' assignments are much easier than the course <R Programming>. Writing function in R really isn't that easy especially for an R beginner who only has little knowledge of R packages and functions. I really don't think this course should arrange as the second course to take in this Data Science course series.
por Jacob D•
9 de dic. de 2017
The lectures that the professor provides are quite clear, and the practice exercises created for this course do well to reinforce the lectures. However, the assignments are impossible and have little to do with the material. It is as if one is taught introductory algebra and then given a calculus problem to solve.
The professors who designed this course need to go back and review the way they design their assignments because they ruin this course. Even submitting the assignments is difficult as they somehow expect you to know how Github works. Unless you have taken an R course before or you are an experienced programmer, I would avoid this class. It will be a waste of your time.
por Bekele D•
22 de mar. de 2020
Well, I learned the basic of R programing , I very impressed with the assignment questions; they are so challenging and I got a lot out of it. At the same time the swirl package come along with course is so helpful. Having say it, I was very dissatisfied with the way instructor present this course; it so embracing to teach programing course by reading slides. How so ?????
This is not history or music/Art course; you have to show each and every example on IDE.
I should have give this course a lone star rating , but for all resources come with it made to be nice to add one more. otherwise 1 star would have been fair review, for there is no rating option below 1 star.
por Karl P•
21 de ene. de 2021
The assignments for this section were difficult to follow and did not necessarily align with the presentations. There was less instruction on R than I expected and it made the programming assignments more difficult. I suggest you have programming experience and it would be even better if you have exposure to R.
A few mentors on the DB did provide some advice on how to think about and write the programs, so find those before you start your assignments. You will likely need to scan the discussion board for advice provided to other students rather than wait on a response from a mentor. They don't have dedicated staff to answer questions.
por Ashly Y•
20 de mar. de 2017
Love Coursera but was disappointed in this course. Being a true beginner w/no background in programming or data science, I felt the programming assignments were way too far a stretch from the Swirl exercises (which I felt were super helpful and beginner appropriate) and lectures. I spent 8-12 hrs on each one just googling and trying to decipher the programming jargon that most responses were written in. I was able to figure out workable code for most problems but I feel like I am still lacking the basic fundamentals underlying the solutions to these assignments and would have a hard time reproducing solutions to similar problems.
por Joshua W•
28 de ago. de 2021
Unfortunately, lessons and practice exercises do not prepare students for the assignments beyond the first week. Concepts are brushed over lightly with chances for basic application, then assignments are given that seem years beyond the material taught. I'm not sure how such a disconnect was created. More thought and time should have been dedicated to building students' confidence levels. More frequent assignments building on lesson topics and engaging discussion could have helped. Discussion is more of a library of past problems, not a platform to engage students. Overall, disappointing.
por NICOLAS Y•
4 de ago. de 2016
The first 2 weeks have too many videos, which make it difficult to follow. This breaks the flow of the lectures and makes a lot of unuseful repetitions.
The slides only have words and are hard to follow, no graphs or illustrations, this means that you rely on the voice of the lecturer to guide you, which is difficult sometimes.
Furthermore, the code presented is not run 'live', and results are often lacking, which makes comparison with 'my own results' hard to do.
Summary: Not that its a bad course (SWIRL is a great tool), just look for another course that's easier to follow.
por Mark S H•
29 de mar. de 2021
The course is unfortunately very old (2012) without much revision, the gap between the content and the exams is too big and there is hardly any didactic concept.
I would accept such a course from a freshman ta at a mediocre college but this lacks depth an explaining. Its still doable but leaving the students with a mess to cleanup instead of a path of learning is poor. This especially bitter when you start with the first course and its premise to be updated and improved regularly. I urge all people involved to redo this course - 9 years is a lifetime in programming!!!
por Theresa B•
11 de ago. de 2018
This course had all the required content for learning to program in R. However, the presentations were hard to understand. There was a lot of information jumps that were more than an intermediate level. I feel these instructors were very knowledgeable, but didn't know how to teach. They need to understand that when you teach a person to read "cat" you start with the sounds "c" "a" "t" and slowly put the sounds together.... You don't just say cat says "cat".
My previous experience in R & my R "hacker mentality" are the only thing that got me through this course.
por Laura S•
29 de sep. de 2020
The lectures are not very helpful to answer the assignments, they are similar to the help files and provide little practical examples and guidance. As a result you have to learn a lot yourself when doing the assignments, and have no way of knowing if you are coding efficiently/ sensibly. I completed the Python course by Chris Brooks at the University of Michigan before this course, and that was a great example of how to integrate lectures and assignments to test learning. This course might benefit from an overhaul along those lines.
por Erika R•
12 de may. de 2017
The instructor explained functions to use in R, but did not do a good job of demonstrating how to properly use them in conjunction as the course progressed. The programming assignments had almost nothing to do with what was taught in the course. As a person with beginner experience with R, this course required more advanced knowledge for coding in R to complete the programming assignments. I was very disappointed with the instruction though I managed to get myself through the assignments with the use of google and R help prompts.
por Tirth B•
9 de may. de 2020
Huge difference between the concepts taught and the quizzes/assignments give. NOT for a beginner level coder. This course is good for those who already have apt knowledge of coding and minimum 1 year of coding experience. Would absolutely NOT recommend this course for those learning how to code. Better to first learn Python and then do this R programming course. The ONLY THING GOOD about this course is the SWIRL package, which really teaches the foundation for coding in R, hence the 2 stars, otherwise I was going to give just one.
por Fabiana G•
26 de may. de 2016
It feels like this course was abandoned by the instructors. The Programming Assignments are practically impossible to be done unless you have previous programming experience. Other than swirl, it would be very helpful if there were basic optional exercises for those who have never programmed before. I worked hard to be able to follow it, but if I knew how uninvolved the instructors were, I would have saved my money and spent it on a course with active involvement from those who developed it. Disappointing.