Computing for Data Analysis

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7/10 stars
based on  40 reviews
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FREE

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  • TBA

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Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4710 reviews

Course Description

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, discuss 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, creating informative data graphics, accessing R packages, creating R packages with documentation, writing R functions, debugging, and organizing and commenting R code. Topics in statistical data analysis and optimization will provide working examples.
Reviews 7/10 stars
40 Reviews for Computing for Data Analysis

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Steve H profile image
Steve H profile image
4/10 starsDropped
  • 3 reviews
  • 2 completed
4 years, 11 months ago
I have a little background in SQL, a database language. I finished 'the data scientists toolbox' and was looking forward to this course (as its a suggested pre-req) for this one. However it was much too hard for an introduction and the projects were way beyond the scope of the lectures. If you're looking to learn R in a self-paced format try Datacamp.
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Laurie Blome profile image
Laurie Blome profile image
1/10 starsCompleted
  • 3 reviews
  • 3 completed
5 years, 1 month ago
I found the lectures poorly presented, the material unorganized and in general not providing enough detailed description of all the required steps in solving a problem.  Although the title of the course indicates "data analysis" is the topic, there is very little thought given to how professionals in the real world define and approach problems from a data analysis standpoint.  This is a course for those very interested in, and with prior experience in programming. I struggled through the course, and considered re-taking it, but as there are so many other, much better courses available on the topic, I would steer any potential student away from this course.  There is a huge disconnect between the material presented in the videos and the quizzes and assignments, which means a substantial amount of time being spent searching the user group discussion boards for clues on how to complete the work being assigned.  If I wanted to teach myse... I found the lectures poorly presented, the material unorganized and in general not providing enough detailed description of all the required steps in solving a problem.  Although the title of the course indicates "data analysis" is the topic, there is very little thought given to how professionals in the real world define and approach problems from a data analysis standpoint.  This is a course for those very interested in, and with prior experience in programming. I struggled through the course, and considered re-taking it, but as there are so many other, much better courses available on the topic, I would steer any potential student away from this course.  There is a huge disconnect between the material presented in the videos and the quizzes and assignments, which means a substantial amount of time being spent searching the user group discussion boards for clues on how to complete the work being assigned.  If I wanted to teach myself, I would not have enrolled in a course, yet this is primarily how it ended up.  Very dissapointing.
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Marcelo Soares profile image
Marcelo Soares profile image
8/10 starsCompleted
  • 16 reviews
  • 13 completed
5 years, 2 months ago
Took it twice, finished it once. Good course, made me begin to plan on dropping Excel altogether. Since I took it from the first installment, it's nice to see how much Peng developed as an online instructor. His early videos were nearly shy. Now, on "R Programming", he seems as comfortable as if he was on a classroom.
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Hamideh Iraj profile image
Hamideh Iraj profile image
8/10 starsCompleted
  • 70 reviews
  • 60 completed
5 years, 3 months ago
It is a 4 week course for introducing R. It is a controversial course and it has a lot of both opponents and proponents. Just look at the coursera forum for this course. video contents are really nice elevating your knowledge but assignments are hard and far away from the taught material. it is what people often complain about. I recommend it when you have a little knowledge and skill about R and you can improve your knowledge and skill with this course otherwise it would be difficult and you may get disappointed.
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Nathan M profile image
Nathan M profile image
10/10 starsCompleted
  • 6 reviews
  • 6 completed
5 years, 3 months ago
I'd already taken a few statistics courses, including one that used R. I've also been programming for several years, and had tinkered a bit with R programming, though nothing serious. The course was short, but covered most of the built-in functions (especially the apply family) and some other packages, like ggplot2 and knitr. The material was well organized, lectures were interesting, and homework was challenging enough to stretch my R programming skills. I'd definitely recommend this course (although I think it's been superseded by the new sequence of "Data Science" Specialization courses.), especially if you want to take the Data Analysis course with Jeff Leek. It might be a bit out of reach if you don't have a good foundation in programming and statistics.
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Manik Hindwan profile image
Manik Hindwan profile image
3/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 6 months ago
I am a final year engineering student but my programming experience is not much. I found this course very tough since there is a huge gap between the lecture content and the programming assignments. Most of the functions that need to be used in the assignments have not been discussed in the lectures and to complete the assignment one has to refer other sources which eats up significant amount of time. The workload due to the assignments, esp. after week 1 increases tremendously ( approx 10+ hours/week). This course is not recommended for beginners. PROS: Shorter duration, good for experienced programmers CONS: Heavy workload(10+ hours/week), lack of clarity
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Greg Hamel profile image
Greg Hamel profile image
6/10 starsCompleted
  • 116 reviews
  • 107 completed
5 years, 5 months ago
Computing for Data Analysis is an introduction to the R programming language for people who already know how to program. The course description makes it seem like the class is intended for everyone, even those who do not know how to program at all; this course is not designed for people with zero programming knowledge. The lectures move through material at a rate and level of sophistication that assumes prior programming experience. You might be able to get through this course without prior programming knowledge with a lot of extra work, but doing so would be an inefficient use of your time. If you have no prior experience, a true introductory class would be a better idea. The course provides a decent overview of R, but the format is not ideal. The lectures are generally 10-25 minutes with no interactive programming exercises to do as you go along. It’s a good idea to follow along and do the commands he talks about on your own so tha... Computing for Data Analysis is an introduction to the R programming language for people who already know how to program. The course description makes it seem like the class is intended for everyone, even those who do not know how to program at all; this course is not designed for people with zero programming knowledge. The lectures move through material at a rate and level of sophistication that assumes prior programming experience. You might be able to get through this course without prior programming knowledge with a lot of extra work, but doing so would be an inefficient use of your time. If you have no prior experience, a true introductory class would be a better idea. The course provides a decent overview of R, but the format is not ideal. The lectures are generally 10-25 minutes with no interactive programming exercises to do as you go along. It’s a good idea to follow along and do the commands he talks about on your own so that you at least get some practice. There’s some good material in the lectures, but they leave a lot out as well. You’ll probably end up spending a substantial amount of time Googling about basic R functions to complete the programming assignments.
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Guillermo Reales profile image
Guillermo Reales profile image
8/10 starsCompleted
  • 3 reviews
  • 3 completed
5 years, 5 months ago
The course was reasonably difficult for people -like me- with little to no knowledge on programming in general and R language in particular. The lectures covered many interesting topics in a fair depth given the short time of the course, though there was a difference in level from lectures to assignments, which included skills not necessarily provided within the lectures, and a lot of extra work searching for the appropriate functions you need to use is required if you never used R before. My suggestion is to join one of the many study groups that are formed every time, which in my experience turned out to be quite helpful.
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Marcello profile image
Marcello profile image
6/10 starsCompleted
  • 3 reviews
  • 3 completed
5 years, 5 months ago
It's quite hard for me to review this course: on one hand, I really enjoyed it and I learned a lot; on the other hand, I think it has some serious design flaws. First: this is NOT a beginner's course. Although the starting videos are simple enough, difficulty ramps up too quickly. You will find the videos difficult to follow if you have no programming background and/or previous experience with R. The programming assignments (which I reccomend) require a lot of indipendent research on forums and tutorials, and are much more difficult than you would expect. The instructor is clearly very proficient with R, but has difficulties getting into the head of a beginner. He shares quite a lot of tips very useful for an intermediate user, but gets beginners confused. I enjoyed the course because I'm not new to R, but if I were I think I would find it frustrating. Even so, I think the course is not well designed for intermediate users, either: t... It's quite hard for me to review this course: on one hand, I really enjoyed it and I learned a lot; on the other hand, I think it has some serious design flaws. First: this is NOT a beginner's course. Although the starting videos are simple enough, difficulty ramps up too quickly. You will find the videos difficult to follow if you have no programming background and/or previous experience with R. The programming assignments (which I reccomend) require a lot of indipendent research on forums and tutorials, and are much more difficult than you would expect. The instructor is clearly very proficient with R, but has difficulties getting into the head of a beginner. He shares quite a lot of tips very useful for an intermediate user, but gets beginners confused. I enjoyed the course because I'm not new to R, but if I were I think I would find it frustrating. Even so, I think the course is not well designed for intermediate users, either: the pacing is inconsistent (the last week is actually easier than week 2) and the course program doesn't seem to follow a clear logic. The istructor actually knows a lot about the topic, so this course has the potential to be great. It would just need a couple more weeks to introduce concepts gradually, more practic exercises with gradual difficulties, and some more tips for beginners. I hope the next sessions will improve the materials. For now, I will use the videos as useful reference material whenever I need to use R.
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Duncan Murray profile image
Duncan Murray profile image
8/10 starsCompleted
  • 25 reviews
  • 24 completed
5 years, 6 months ago
I have a programming background so found this course really enjoyable - the 4 week burst of learning R was spot on in my opinion. If you are new to programming you may find it a bit rushed, but still should be able to complete it.
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vaggelas profile image
vaggelas profile image
9/10 starsCompleted
  • 28 reviews
  • 26 completed
5 years, 8 months ago
This i think was my first course on Coursera.I Completed it twice. It is an introductory course in R language,a progragmming language designed for statistics. It wasn't that hard for me but i already knew 2-3 languages before this course and i have taken many CS courses before. For guys with no prior knowledge in programming it was kind of hard cause the pace was a little bit fast. Ducarion : 4 Weeks Assignments : Quizzes each week and auto graded programming assignments every other week Pros : Small duration of course, Forums were very active , Programms used were free and available in all systems , It maybe is the only Mooc in R with so many feautures of R in the course Cons : It is not easy for guys with no programming knowledge , It needed a few more video lectures with examples , Some video were a bit long,it would be nicer all videos to be at most 5 mins for easy reviewing , It would be nicer not to be voice over all the time,b... This i think was my first course on Coursera.I Completed it twice. It is an introductory course in R language,a progragmming language designed for statistics. It wasn't that hard for me but i already knew 2-3 languages before this course and i have taken many CS courses before. For guys with no prior knowledge in programming it was kind of hard cause the pace was a little bit fast. Ducarion : 4 Weeks Assignments : Quizzes each week and auto graded programming assignments every other week Pros : Small duration of course, Forums were very active , Programms used were free and available in all systems , It maybe is the only Mooc in R with so many feautures of R in the course Cons : It is not easy for guys with no programming knowledge , It needed a few more video lectures with examples , Some video were a bit long,it would be nicer all videos to be at most 5 mins for easy reviewing , It would be nicer not to be voice over all the time,but to have professor on screen with graphics
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Dean Wang profile image
Dean Wang profile image
10/10 starsCompleted
  • 6 reviews
  • 5 completed
5 years, 9 months ago
This is a very short class with high concentration on programming. I spent a lot of time trying to figure out how to do R and learn a lot during the 4-week period. This is short but hard class. I highly recommend it!
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Jose Luis Dengra profile image
Jose Luis Dengra profile image
7/10 starsCompleted
  • 5 reviews
  • 5 completed
5 years, 9 months ago
This course is a mere introduction to R fundamentals. I have completed it, but I don't feel comfortable working with R. I have learned some concepts and techniques, but to achieve the programming assignments I have needed to search many times in R documentation and internet, as well as to perform many test- and-error attempts to get any of the results. Some of the video lectures were longer than 30 minutes and difficult to be followed.
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Ramiro Aznar profile image
Ramiro Aznar profile image
6/10 starsCompleted
  • 27 reviews
  • 26 completed
4 years ago
Although I had some experience programing with R, I found this course quite difficult to follow up. Although this can be viewed as challenging, the content was larger than usual and the speed of the tutor in each lessons was quite fast. In fact, most of the time I had to search outside the coursera community for help. Besides the difficulty of the course I had learnt more about R. So if you want to take this course I highly recommend you to try some tutorials in order to have a minimum knowledge of R skills.
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daveice profile image
daveice profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 9 months ago
Generally speaking, this is a great course of learning R. I like it very much! However, learning R from scratch in 4 weeks is not enough for most of people, so the schedule is a bit tight. If you don't have enough programming skills, you'd better read some elementary R books before join the session, then you can catch the video content better. I have a solid programming background, and I read some material about R along with the course to get better understanding..
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Student profile image
Student profile image

Student

9/10 starsCompleted
5 years, 9 months ago
I had some prior knowledge of R, but only pretty basic stuff, and no other experience in programming. Dr. Peng is incredibly knowledgeable, but also quite good at presenting that knowledge in a way that is easily digestible. The lectures, I thought, were great. The thing that surprised me about this course is that the lectures don't cover everything you need to know for the assignments. So I had to do a lot of independent searching to find the solutions to some of the problems. At times this was very frustrating, but I feel I've come away with some really useful skills in using R. The assignments are well-designed in that they demand you use some useful bits of code that are really good to know, but they aren't so challenging that a beginner can't complete them -- provided you have the time to put in! The first and last week of the course were easily manageable, maybe 3-4 hours of work. The middle two weeks I probably spent about 10-... I had some prior knowledge of R, but only pretty basic stuff, and no other experience in programming. Dr. Peng is incredibly knowledgeable, but also quite good at presenting that knowledge in a way that is easily digestible. The lectures, I thought, were great. The thing that surprised me about this course is that the lectures don't cover everything you need to know for the assignments. So I had to do a lot of independent searching to find the solutions to some of the problems. At times this was very frustrating, but I feel I've come away with some really useful skills in using R. The assignments are well-designed in that they demand you use some useful bits of code that are really good to know, but they aren't so challenging that a beginner can't complete them -- provided you have the time to put in! The first and last week of the course were easily manageable, maybe 3-4 hours of work. The middle two weeks I probably spent about 10-12 hours watching lectures and completing the assignments. I would recommend this course to anyone wanting to learn how to use R to collect and do basic data analysis, and start making some plots of the data.
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Dwight Tinker profile image
Dwight Tinker profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 9 months ago
I have used R in development as well as other programming languages. This is a class where a beginner will spend a large amount of time trying to keep up, but it is well worth it. The class focuses on iterating through, capturing and modifying statistical data with a secondary focus on the fundamentals of plotting. To be honest, on the hardest week I spent over 16 hours working on the coursework and lectures, on the easiest week it was around 5. That included some extra time polishing the functions. Listening to the lectures was a good experience, but as with many programming languages it can get technical and just because you learn the overall technique doesn't mean applying it to specific cases is easy to do without trial and error. The programming assignments support each other with each assignment building on the next and there are some ungraded steps in some assignments that are intended to help get you ready for the scored assi... I have used R in development as well as other programming languages. This is a class where a beginner will spend a large amount of time trying to keep up, but it is well worth it. The class focuses on iterating through, capturing and modifying statistical data with a secondary focus on the fundamentals of plotting. To be honest, on the hardest week I spent over 16 hours working on the coursework and lectures, on the easiest week it was around 5. That included some extra time polishing the functions. Listening to the lectures was a good experience, but as with many programming languages it can get technical and just because you learn the overall technique doesn't mean applying it to specific cases is easy to do without trial and error. The programming assignments support each other with each assignment building on the next and there are some ungraded steps in some assignments that are intended to help get you ready for the scored assignments for the week. I highly recommend this course and think it will be an asset for future data analysis courses. Others in the course stated they thought this course complimented the Data Analysis course they were offering at the same time. A word of warning, This is one of the most difficult undergraduate courses you'll take if you're not trained in programming methodology. This is not an R tutorial! it is centered around getting data for analysis so if you're not interested in a career using data analysis this may not be for you. Many of the people in the course dropped out. If you are interested in data analysis, take this course!
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Oliver Tacke profile image
Oliver Tacke profile image
1/10 starsCompleted
  • 2 reviews
  • 2 completed
6 years, 2 months ago
In my humble opinion, the course was designed awfully. For instance, if the course is targeted at a general audience without experience in programming who wants to learn about ANALYZING data, is it really wise to begin the slide show video lectures (yuks) with explaining data types? I guess, most participants didn't want to become programmers and were totally confused. Wouldn't it be better to start with ostensive examples and then showing how to solve them with R?
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Captain profile image
Captain profile image
2/10 starsDropped
  • 2 reviews
  • 1 completed
6 years, 3 months ago
Having no previous programming experience, this course was too hard. The lectures did not go through most of what was required in the programming assignments, which leaves you to go look it up on your own. Not useful and very frustrating. It gave me a minimal knowledge of R that I needed to move on and take the Data Analysis class, in which I Iearned much more about R
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Thomas Sarlandie profile image
Thomas Sarlandie profile image
7/10 starsCompleted
  • 4 reviews
  • 4 completed
6 years, 1 month ago
Good introduction to the R programming language although a bit too "formal" by times. The exercises got me quickly up to speed too. I am a professional developer with background in several languages and it felt very easy. It was not boring though because the lectures are quite short and get to the point quickly. I had never played with R and I think it was really useful to prepare for the Data Analytics course. Suggestions: * More exercises to entertain and challenge the viewers (maybe some more optional challenges would have been fun) * Give more examples that relate to data analysis - This is what I was looking for and I had to wait for "data analysis" to start really crunching data.
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Denis Shepetovsky profile image
Denis Shepetovsky profile image
2/10 starsDropped
  • 1 review
  • 0 completed
6 years, 6 months ago
This is NOT an introductory R course for beginners. The main problem of the course is that the lectures are too distant from the quizes and assignments. The smallest examples in the lectures were definitely not enough to complete the home tasks. The lecturer's attention is too much on some not so elementary R features which most beginners simply do not need (like optimization and to a less extent coercion) while really basic topics that appear the most challenging to beginner (and which are the most required to do ANYTHING AT ALL, like subsetting ) are not receiving enough time and EXAMPLES. The on- screen presentations are terrible in that they do not contain enough info to help you, e.g., when you are struggling with an assignment. Most of the time they look like just fragments of R code with NO COMMENTS WHATSOEVER. This course could be much improved if the presentation slides contain more info from what the lecturer actually talks... This is NOT an introductory R course for beginners. The main problem of the course is that the lectures are too distant from the quizes and assignments. The smallest examples in the lectures were definitely not enough to complete the home tasks. The lecturer's attention is too much on some not so elementary R features which most beginners simply do not need (like optimization and to a less extent coercion) while really basic topics that appear the most challenging to beginner (and which are the most required to do ANYTHING AT ALL, like subsetting ) are not receiving enough time and EXAMPLES. The on- screen presentations are terrible in that they do not contain enough info to help you, e.g., when you are struggling with an assignment. Most of the time they look like just fragments of R code with NO COMMENTS WHATSOEVER. This course could be much improved if the presentation slides contain more info from what the lecturer actually talks ( in form of comments or as a superscripted handwriting, like I saw it in other courses). This course definitely needs more examples. The good examples should be based not on some rnorm() output, but on a single array of meaningful data, which should be analyzed throughout the course by means of different functions. It will help understanding and remembering different ways of data treatment. Previously I took Coursera's Interactive Programming in Python from Rice Uni, and that was really what a beginner's course should look like. I tried Coursera's Statistics One from Princeton, and while it has a demanding learning curve and underestimates time consumption on its page, Statistics One is free from most of the problems of CfDA and I will definitely retake it when available. I took this course in preparation for Coursera's Data Analysis from the same JHU, now I think of dropping them both.
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jac profile image
jac profile image
4/10 starsCompleted
  • 5 reviews
  • 4 completed
6 years, 4 months ago
Takes far longer than the 3-5 hours suggested, even though I have a strong programming background (even just watching the lectures was two-three hours a week, if I was trying to pay attention and take notes). I would not take this again unless I had at least 10 hours a week to commit. I simply didn't have the time available to complete the course properly, which was very frustrating. It basically consisted of recorded lectures, graded online quizzes with a right/wrong mark given but no other feedback on the answers, and assignments that required a lot of self-directed research outside the provided material and took up the bulk of the time each week.
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Markus Weber profile image
Markus Weber profile image
1/10 starsCompleted
  • 5 reviews
  • 4 completed
6 years, 6 months ago
The worst part is that the lectures are in no way related to the assignments. So what use are they? Basically, one has to search in books and in the internet to complete the course, the lectures are a "bonus" at best. There are no practical examples throughout the lectures, the audience is simply bombarded by function references. Don't be fooled by the course description - this course requires extensive programming experience. While I have related experience through my PhD and my work, it was in no way sufficient to pass this course. Not by a long shot. The overall experience of this course is very frustrating and drop-out rates are accordingly high.
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steve profile image
steve profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 5 months ago
Great introduction to R. Some previous experience with programming would be very helpful. Roger gives great lectures, and the exercises were helpful without being unnecessarily tedious. Some reviewers have noted that the course is not a good introductory course to R--I think it is. No previous knowledge of R is assumed. It is assumed you know what variables, classes, etc. are, you're comfortable with a command-line, and you've been exposed to things like regular expressions.
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Matt Williams profile image
Matt Williams profile image
9/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 5 months ago
I thought this was a great course. The lectures covered all the material, though having examples based on something other than rnorm would be nice. The slides don't contain everything but they are there in the lecture, just take notes. It seems that some of the reviewers want the lecturer to do all the work for them. The exercises were mostly a challenge. Week 3 was especially tough for me. Week 4 was insanely easy, completing in about 20 minutes. I think the pre reqs were right for the most part. Minimal knowledge of programming required is right. I was surprised though at the higher level of statistics knowledge required. That was one of my challenges. Overall, very glad I took the course and moving on know to the Data Analysis course which started a few days ago.
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makoto_inoue profile image
makoto_inoue profile image
8/10 starsCompleted
  • 8 reviews
  • 7 completed
6 years, 5 months ago
This course is good for someone who has programming experience like me. I enjoyed the programming assignment because that's the best way to learn. I prefer this shorter length (4 weeks) rather than longer length so that I can keep the motivation. I thought about recommending to my scientist friend, but probably it's a bit too difficult as the instructor often used technical jurgons which he took granted that students know. Hence -1. If you are interested in what kind of content is taught, I created a website to search captions, so feel free to use as a reference. http://benkyoplayer.com/courses/4
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Skye Wills profile image
Skye Wills profile image
1/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 6 months ago
Class description should be altered and students shouldn't be steered to this class for an introduction to R. You MUST have either some programming knowledge or a large amount of time to devote to this. I had neither. This is my second attempt at this class. I am an R user looking to move into more sophisticated programming. I cannot keep up and will be dropping the class again. I learned some things, but I could not make the leap from the lectures and quizzes to the assignments. After my second 5 hour day this week - I am going to cut my losses and unenroll.
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Bill Buckley profile image
Bill Buckley profile image
7/10 starsTaking Now
  • 1 review
  • 0 completed
6 years, 6 months ago
If you know how to hack and have a basic familiarity with a few C functions (like sprintf), then you should be able to complete the course. There are many places where Dr. Peng can improve the accessibility for those not so capable as hackers but those are not sufficient reasons to stay away from the course.
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xasmx profile image
xasmx profile image
8/10 starsCompleted
  • 5 reviews
  • 5 completed
6 years, 5 months ago
The reviews for this course seem quite divided after after reading the reviews I can appreciate both of the view points. I found the course enjoyable and a decent introduction to R. However, it's an introduction to R for programmers, so you should feel comfortable programming in at least some other language before engaging this course. You should not consider this as your first course into programming. The lectures felt a bit dry at some points, due to delving into details of number of functions in the standard library. However, they were useful. The course also included required programmin assignments that forced you to engage and get your feet wet. Some details of the assignments required you to figure out and use functions of the R library that were not introduced in the lectures. This might have again been frustrating if you didn't have prior programming experience, but pretty much standard practice for anyone who is a programmer.
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alessio ansuini profile image
alessio ansuini profile image
9/10 starsTaking Now
  • 2 reviews
  • 1 completed
6 years, 6 months ago
I reccomend this course to everyone who want to learn basic R programming and also as a (brief) introduction to Data Analysis. I agree with who observed that the course is maybe a little too short: for an absolute beginner there is little time to absorb the material completely, but the assignments are amazing, and by far the most important part of the course.
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  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars

Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.