Volver a Programación R

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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....

MR

11 de may. de 2020

Really interesting course. The interactive coding sessions with swirl are especially useful. Would be great, if you provided sample solutions for the programming assignments, in particular for week 4.

WH

2 de feb. de 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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por Tareq R

•16 de sep. de 2018

I think for a MOOC, this course could have used the power of video a lot more, listening to the videos that are basically voice over a slide , wasn't helpful at all, and if it wasn't for the book, I wouldn't learn anything.... if the videos were more illustrative and visual to explain certain concepts , that would have been much better

por Javier P

•8 de dic. de 2019

Very poor material. Very theoric, no interaction, interesting applications or examples, and very boring lectures.

The material is very trivial, without real applications.

The assessments were useful but in some cases they were not related with the topic.

por Kristofer R

•31 de oct. de 2018

R Programming assignments were much more complex than what the tutorials taught. There was a very drastic jump between the two and was very difficult/frustrating to complete, especially for someone with no coding experience.

por Rushabh K

•28 de abr. de 2020

Should have been better taught and the stuff in assignment is way tough than taught in the lecture

por Brian K

•20 de mar. de 2016

I am really unhappy with this course. Coming to R with some background in statistics and SQL, but lacking programming experience, I assumed this would be an introduction. The material in the lectures is straightforward enough, and the swirl exercises are easy to get through and informative, but the assignments are, without exception, based on writing functions in R with basically zero experience. Having no background or frame of reference for best practices in syntax, logic, etc, and very little information in the lectures or supplementary material to help, I found these to be almost impossible to complete.

Furthermore, there's no mechanism or provision in the course to review the assignments after they're submitted. So not only did I not feel like I was doing the work correctly, I can't get feedback, and the lecturer doesn't break down the rationale behind the assignment, and how he would have done it or why. In addition, the assignments bear only a tangential relationship to the lecture material. So I would be feeling good coming out of a lecture and going through swirl exercises, only to be plunged into a programming assignment that was far too advanced for the small steps I felt I had taken in my overall competence with the language and material.

I don't doubt that someone with better knowledge of programming can get through this stuff, but this class should be reserved for advanced learners only, or maybe be broken up into two courses. I feel like I wasted $49.

por Kenneth N

•14 de abr. de 2020

This course is extremely poorly constructed and now quite dated providing instruction in only base R.

The philosophy underlying the modular system in Coursera is clearly that the subject matter covered in the module relates to the set work for that module. I was only able to complete work for week x after doing the reading for week x+1. It took me some time to discover this strategy, a lot of which was wasted wondering what I was missing, what I had done wrong &c. I'm sure the course fee doesn't mean much to most but it is a significant amount to me and I felt let down. Very little time or thought has gone into the structure of this course. It is clear that something is wrong with the week 3 assignment when there are git hub entries on the background knowledge required to complete it. Without these I would not have managed. Going by the age of some of these entries, this problem is now years old with no attempt made to rectify it.

My only reason for persisting with the course is that my boss asked me get the certificate. I imagine his assumption was that the quality must be high given the institution sponsoring it. It seems to me this course is risks causing a significant amount of reputational damage to Hopkins by association. I won't be continuing with this series of courses, I have switched to a related course series offered by Duke. The quality is incomparable.

por Tural D

•14 de dic. de 2019

My overall evaluation for that course is 1 stas due to main two reasons:

First of all course has too much information without the applying during the weeks. However once a learner opens the assignment it is inevitable to face with very hard tasks

I spent more time on youtube and other sources to learn how to use the functions and solve the assignments in comparison with the course itself. That is the reason I am not satisfied with the course.

Given theory is okay but the applying of them during the week is very less. THat is the reason learner face big issues during quizzes.

I found SWIRL assignments very useful that I can say they were the only things that I learned the practical part of R programming.

My advice is to increase the number of SWIRL assignments and increase the difficulty level of them each time.

It is also better to decrease the difficulty level of assignments and quizzes. Because course is more theoretical than being practical in teaching. but the assignment requirements are more practical.

por Boban D

•12 de ago. de 2017

One of the most worthless courses I have ever taken! There are so many gaps in the course material that you will sepnd the majority of your time banging your head against the table wondering what and why something in the code is happening. The Material on Loops and Functions is a joke! You are supposed to learn loops from that? Maybe if you already know a programing language, you can, but is suposed to be a beginners course, as it was announced whe I started it. Also dont expect much exercises. Swirl is nice to play around, and there is a quiz, but that does not come even close to having a comprehensive set of Exercises. The Instructors advice when there are gaps: Google it! I dont need to enroll in a paid course (for beginners) to do that. Pathetic!

por Benjamin L

•5 de dic. de 2018

Don't expect so much... Lexical scoping will probably not be used by the majority of data scientists but the course expects you to research it yourself entirely and spend hours on hours on it, when the focus could have been placed on somewhere else!

"Mentors" are quick to respond to dissatisfaction at the course with comebacks but when students ask for help regarding assignments they are nowhere to be seen.

Watch all the lectures, enrol for 7 day trial, submit assignment 2 and 4, and ignore the rest. Don't let them trick your money!!! (PS I was like you at the beginning, I thought of paying for the course, doing a good job and getting a certificate, but trust me, this course is not worth it.)

por Troy M

•5 de dic. de 2019

As many others have stated before, the gap between the lectures/swirl practices and the actual assignments is way too big. I am a novice at R but did come with practice of the basics before starting this course. I also took notes and completed every swirl practice. Even with that I felt incredibly unprepared for the assignments. I understand that searching the internet for help is part of the process but the extent to which the student must search is unforgivable for this to be considered a proper way of teaching. I would also caution that the estimated hours of completion are understated if you plan on trying to actually complete these assignments by yourself.

por Todd D

•24 de abr. de 2020

This course is frustratingly bad. The lecture topics are very scattered and provide almost no practical information. The slides are static with simultaneously too much and too little to understand how to apply them "in the real world." The disparity between the lecture material and assignments is truly laughable and -- if you are a beginner -- more or less impossible to complete without lots of Google/stackoverflow searching and head scratching. I would not recommend this to anyone.

por Olivier P

•13 de mar. de 2016

This is probably the most pedagogically inept course I have ever enrolled on. Although the content is what you would hope to find in such a course, the delivery of it is outrageously bad. When to complete your assignment, Google becomes your best friend rather than your lecture notes, you know that something is wrong. The idea that a baby thrown in the water may just learn to swim rather than drown is pedagogically retarded. Unfortunately, this seems to be the approach here...

por Ethan T

•8 de jun. de 2019

The gap between tutorials and assignments is huge. They teach you algebra I and then expect calculus. I got by because of google searching. It took a long time, and it was very frustrating. This course could have been better if there were intermediate assignments to help close that gap. I'm not sure why they've done this already. Based on the discussion sections, I can tell that a large percentage of people quit the data science specialization after taking this course.

por arif v

•26 de ene. de 2019

the content of the course is rather irrelevant of the assignments, at least in terms of the hardness... also the presenter is substantially fast.

por reco g

•4 de may. de 2020

the lectures are very shallow and lack good code examples. The programming assignments are too hard. The worst course I have ever seen.

por Akram A

•31 de ene. de 2019

it's not good to explain only without practice or giving examples

por Abhishek J

•27 de sep. de 2016

I will break down the review into the contents and comment on them. Before doing that and saving the trouble for people who do not like to read a lot - This course is an awesome kick-starter for R-programming.

Video Lectures : The speed and content are just perfect. The concepts covered in each lecture and the manner in which it was taught just made them stick well in my mind.

2. Quiz - They were simple so I infer that they are meant to test how well we have learnt the concepts.

3. Swirl Practice Programming Assignments - A very innovative way to teach us in the R console itself. I really enjoyed playing with it.

4. Programming Assignment - It was a sheer pleasure to do the last assignment. The level was really good. I found it a bit daunting at first but then caught up by reviewing some concepts.

5. Discussion Forums - I couldn't be very active in terms of replying but I never missed to hear what mentors had to say. I owe thanks to mentors for their awesome posts that gave deeper insights especially Al Warren.

I highly recommend this course. Prof. Peng - your videos are really good and far from boring. And yes, Thank you Coursera.

por Patricia R B D

•23 de may. de 2018

I have long since wanted to learn R, but other online tutorial sites which mostly involved learning through copy-pasting codes didn't help me well. I had no expectations for this specific module as I know that I have unsuccessful experience on learning R online, but this module helped me significantly. Unlike other online tutorial sites, lectures in this module helped me understand how R thinks and works. Lexical scoping was particularly difficult to understand at first, and I also had to rewatch it a few times, but it did help me a lot in actually learning the language. I also like how the programming assignments are laid out as "machine problems" wherein students are asked to create functions that also require us to search for other functions on our own. The swirl exercises were also particularly helpful for me in remembering some useful functions that I would later use for the programming assignments. In just one month, I am now confident to say that I know how to R (but I know there's a lot yet to learn hahaha).

por Michael M

•31 de jul. de 2017

This is one of the most frustrating courses I've ever taken. Please do not mistake this for criticism, it is not. This course is basically trial by fire, but at the end of it, I am surprised how much I have learned about R. One suggestion I have for students is this: do not just write the code for the functions from the assignments. Play around with the different functions by writing your own codes. Here are some ideas: write a code that takes in two numeric values and one letter that each represent the corresponding sides of a right triangle. Your code should calculate the length of the third side using the Pythagorean theorem. Also, write a code that solves a quadratic equation in standard form given three numeric values as elements in a vector (where each element = its respective leading coefficient). Finally, write a code that takes any numeric matrix with dimension [3:n] and runs each column of the matrix through the quadratic formula. Doing this really helped my understanding of the split and lapply commands.

por Carlos C

•3 de sep. de 2019

Excellent course. Really. Don't listen to those people saying it is too difficult. You just need to think, probably watch again some small lecture, and probably go to the Discussion Forums (or Stack Overflow in my case to know about how to do something specific in R), to solve the Programming Assignments. It has the right level of difficulty and the instructor, Roger Peng is amazing. He's very excited about the subject and his energy helps to motivate you throughout the course.

Maybe just a little bit of programming experience is required (just thinking in programming terms or knowing the basic functions). But really, I believe anyone with motivation, patience (you're gonna need this last one haha), and focus can pass this course without a problem.

I almost didn't take this course because of the negative comments I read before starting. But trust me,take the leap and start R Programming from Johns Hopkins University. You won't regret it! Especially if you're interested in the Data Science or Data Analysis field.

por Miguel C

•16 de mar. de 2020

I really enjoyed this course!

I was already somewhat familiar with R but I now feel much more confident in my R programming skills. I am glad this course was not exclusively helpful for people just starting with R. I learned many new things and I sometimes struggled with some of the assignments (especially week 3 programming assignment) and they pushed me to understand more complicated concepts, which I was really happy about.

I thought the swirl library was also really helpful. It solidified what we'd learned in the video lectures, and sometimes delved into things I had not seen before or things we had seen before but with more detail, such as ellipses (as arguments in functions), definition of binary operations and simulations of coin flips.

The only part I was not interested in is the history of R at the beginning of the course. I didn't really care for it, but I think I understand why it's there.

Overall, I really enjoyed it and I would definitely recommend it to other people.

por Bruno H

•15 de ene. de 2020

Foi um curso bem útil e de grande aplicabilidade, passando muito bem por todo conteúdo de funções, loops, extrações e manipulação de conjunto de dados, reforçando muito bem através de exercícios. Em conjunto com os principais métodos usuais de depuração, otimização e utilização de gráficos. Entretanto, achei este curso com uma dificuldade considerável nos projetos semanais para quem é iniciante, dediquei por um mês uma média de 4 horas/diária (inclusive aos finais de semana) e a maior parte do tempo gasto foi buscando conteúdos de apoio, metodologias adicionais em fóruns como o GitHub, Stackoverflow e lendo a biblioteca do R. O que não é algo ruim, pois no dia a dia, iremos nos deparar procurando novas informações e metodologias mais atuais para fazermos algo de uma forma mais eficiente.

por Shreya S

•27 de feb. de 2019

Brilliant content!! Practice exercises really help you evaluate yourself. A little knowledge of R programming before this course is helpful as that might help understand the slides better. Though it is not mandatory but one can still utilize free resources available online to build the basic knowledge. Also, if you have prior experience with any programming language, that'll be very helpful. Would highly recommend this course.

por Eva K

•23 de may. de 2021

With no prior experience of programming, I found this course to be very challenging especially while solving the programming assignments in which the problems were very difficult to solve at times. But the lecture material and discussions in which mentors and students actively participated really provided some background support to me. Overall, an excellent course for all who are interested to learn R.

por Elisa R

•15 de abr. de 2021

The assignments are very difficult. ALL the assignments required me to spend HOURS on them, looking for help outside what was given in the course..

BUT I learned a LOT and after finishing this course and others from the specialization I learned in 5 months what I haven't been able to learn in like a whole year.

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