subject
Intro

Coursera: Computing for Data Analysis

 with  Roger D. Peng
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.

Syllabus

A student who has completed this course is able to:

  • Read formatted data into R
  • Subset, remove missing values from, and clean tabular data
  • Write custom functions in R to implement new functionality and making use of control structures such as loops and conditionals
  • Use the R code debugger to identify problems in R functions
  • Make a scatterplot/boxplot/histogram/image plot and modify a plot with custom annotations
  • Define a new data class in R and write methods for that class
27 Student
reviews
Cost Free Online Course (Audit)
Pace Finished
Subject Data Analysis
Provider Coursera
Language English
Certificates Certificate Available
Hours 3-5 hours a week
Calendar 4 weeks long
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Roger Peng
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What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
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To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

27 reviews for Coursera's Computing for Data Analysis

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4 out of 4 people found the following review useful
3 years ago
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Life is Study dropped this course.
Computing for Data Analysis is an introduction to the R programming language, but not an introduction to programming. This course is designed 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, which Read More
Computing for Data Analysis is an introduction to the R programming language, but not an introduction to programming. This course is designed 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, which caused a lot of pain in the class forums. The class description estimates the effort required to complete the class at 3-5 hours per week. Although this range is probably accurate for weeks 1 and 4, week 2 and especially week 3 are likely to take significantly longer than that. I wouldn't say the course is impossible for someone who hasn't programmed before, but I imagine it would take dozens of hours to understand what's going on, because the lectures move through material at a rate and level of sophistication that assumes prior programming experience. For example, in week two the lectures cover control flow, loops, defining functions, various built in functions, scoping, higher order functions and debugging. That is a ton of ground to cover in one week of an introductory class that claims 3-5 hours of effort per week. Thus if you have no prior experience I'd avoid this course in favor of a true introduction to computer science course like Udacity 101, Rice's intro to CS on Courera, MIT 6.00, or Harvard CS50. All of these are great courses that either have sessions starting up soon or let you learn at your own pace at any time.
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3 out of 4 people found the following review useful
3 years ago
Brian Borchers completed this course.
The lectures in this course were presented as online videos of up to about 1/2 hour length. The videos consisted of prepared slides with the lecturers voice in the soundtrack. To keep the videos from becoming too boring, there were multiple choice questions interspersed throughout the videos. There were also some ac Read More
The lectures in this course were presented as online videos of up to about 1/2 hour length. The videos consisted of prepared slides with the lecturers voice in the soundtrack. To keep the videos from becoming too boring, there were multiple choice questions interspersed throughout the videos. There were also some activities for the viewer to try at the R command line. The production values were comparable to what I regularly see in lecture capture videos from conventional courses- these were not highly polished videos

I was disappointed by the lack of depth in the lecture material. This was a course in R programming rather than statistics, so any in-depth discussion of statistical issues would have been inappropriate, but I was surprised by how little discussion there was of the structure and semantics of the R programming language. For example, R uses a fairly unusual scheme of lexical scoping that can be particularly useful in statistical work. This was mentioned briefly in one lecture but not fully explained.

Although I think this course could have been much better, I certainly did learn some things about R programming that I wanted to pick up, and overall I'm glad that I took the time to participate in the course.
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1 out of 1 people found the following review useful
5 years ago
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Anonymous completed this course.
A nice 4 week mini-course that thought me how to write R scripts. The video lectures are sometimes academic in the bad sense of the word (showing great learning, but not really that relevant). The weekly quiz questions were very functional. The real meat of this course were both practical assignments. I learned a lot f Read More
A nice 4 week mini-course that thought me how to write R scripts. The video lectures are sometimes academic in the bad sense of the word (showing great learning, but not really that relevant). The weekly quiz questions were very functional. The real meat of this course were both practical assignments. I learned a lot from doing these (WARNING: you are given a real data set and real task to perform using these sets, but I had to use Google to find ways to do the task - very few hints and examples were given in the lectures -) After finishing the assignments I had acquired the skill to write R scripts. For me the course worked well, but I would not recommend it to those who are looking for an easy intro to R.
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1 out of 1 people found the following review useful
5 years ago
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Anonymous completed this course.
The course is an introduction to programming in R, and as that it is quite good. It doesn't deal with many particularly difficult statistical concepts, but when he does he sticks to the name of the course and teaches only how to program it (e.g. on the lecture on simulation). I thought the pace was quite good, but some Read More
The course is an introduction to programming in R, and as that it is quite good. It doesn't deal with many particularly difficult statistical concepts, but when he does he sticks to the name of the course and teaches only how to program it (e.g. on the lecture on simulation). I thought the pace was quite good, but some people in the forums complained it was too fast for them, so be warned (and as someone mentioned, be prepared to google some, but you should do that always: google is the bread-and-butter of any programer).
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1 out of 1 people found the following review useful
3 years ago
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Santosh Goteti completed this course, spending 1 hours a week on it and found the course difficulty to be easy.
This course is mainly about R programming. If you are not from programming background, this course might be significantly tougher.
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2 years ago
Oliver Tacke completed this course, spending 3 hours a week on it and found the course difficulty to be easy.
This course had severe flaws, I don't know if anything changed meanwhile. You shouldn't make onboarding unneccessarily hard for people who are interested in data analysis by starting with describing data strucures. That may or may not make sense in a computer science course, but not if people want to analyze data. So, Read More
This course had severe flaws, I don't know if anything changed meanwhile. You shouldn't make onboarding unneccessarily hard for people who are interested in data analysis by starting with describing data strucures. That may or may not make sense in a computer science course, but not if people want to analyze data. So, those who are familiar with programming don't need such an introduction. On the other hand, those who are not familar with programming will probably be overburdened -- that's what actually happened as you could read in the discussion forum.

Just dull presenting and showing ugly power point slides is no fun, the quizzes were meant to replicate facts from the videos, etc.
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5 years ago
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Anonymous completed this course.
Expected much more. This is not an introductory course to R. It requires you to have previous knowledge and experience in programming. Not all necessary knowledge to complete programming assignments is covered in video lectures. It's necessary to read and study from other sources. 3-5 weekly hours is not enough, be pre Read More
Expected much more. This is not an introductory course to R. It requires you to have previous knowledge and experience in programming. Not all necessary knowledge to complete programming assignments is covered in video lectures. It's necessary to read and study from other sources. 3-5 weekly hours is not enough, be prepared to invest much more time trying to find our how to do things by yourself. 4 weeks is not enough to acquire proper knowledge of R. Basic topics are covered and some examples are shown, but you are not taught how to do things the R way. That is for you to find out.
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4 years ago
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Mark Tuttle completed this course.
Enrolled in previous offering but didn't have the time to participate. Am early on in the videos this time, and am impressed. This is a challenging subject to simplify and I think Peng is doing a great job so far. His lectures are easily more productive than using the pile of R books I have. On the one hand, Peng has a Read More
Enrolled in previous offering but didn't have the time to participate. Am early on in the videos this time, and am impressed. This is a challenging subject to simplify and I think Peng is doing a great job so far. His lectures are easily more productive than using the pile of R books I have. On the one hand, Peng has a feeling for programming language design, and on the other hand his presentation is driven by anticipated "data" needs.
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5 years ago
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Anonymous completed this course.
I wish the lectures were more informative and helpful in answering at least homework questions. I found myslf learning from google eventually. I started Data Analysis by Jeff Leek, and like it much better so far. Everything is well explained, relevant exercises, there practical examples of real life applications.

Hopefully, it will continue to be good!
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5 years ago
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Anonymous completed this course.
I took the course a couple of months ago and have been working with R a lot since. Peng did an incredible job - making a very complicated subject understandable, with excellent lectures and excellent assignments.

I highly recommend this course.
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5 years ago
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Anonymous completed this course.
I just finished the course. The whole experience was great. The programming tasks were fairly non-trivial. The knowledge you would gain is absolutely worth spending an few hours a week on the course for four weeks!

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5 years ago
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Anonymous completed this course.
Good and fast introduction into the R package.

A little bit too much ex-catetra, more small interactive exercises and some real world problems can make ths course more exciting.
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2 years ago
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Anonymous dropped this course.
This series of courses is a joke! Don't waste your time!

If you know how to use R for data analysis you don't need it - if you don't, you won't learn here!!
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4 years ago
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Anonymous completed this course.
Not the best course I took. All in all it reduces to a kind of introduction to R... "Computing for Data Analysis" is a bit of a mouthful.
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2 years ago
Michael A. Alcorn completed this course.
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2 years ago
Rajesh Kohli is taking this course right now.
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2 years ago
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Rafael Prados completed this course.
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10 months ago
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Alex Ivanov audited this course.
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11 months ago
Y. Nicodeme completed this course.
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6 months ago
Mbegera partially completed this course.
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2 years ago
Pablo Torre completed this course.
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2 years ago
Colin Khein completed this course.
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a year ago
Janet Wesner audited this course.
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2 years ago
Olga Pustovalova completed this course.
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a year ago
Mark Henry Butler completed this course.
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0 out of 3 people found the following review useful
3 years ago
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Marta completed this course.
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