JM
Aug 11, 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.
MR
May 11, 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.
By Rachade H
•Sep 28, 2016
not the easier way to learn R
By Ron M
•Jan 28, 2018
good but very time consuming
By 后峻
•Jun 8, 2017
in course purchase make th
By Jaivardhan D
•Jul 25, 2020
Quite hard for beginners
By Vivekanand R
•Oct 2, 2016
Needs clear instructions
By JOSÉ A T M
•Aug 6, 2020
No esta todo en español
By Nicholas E
•Jun 9, 2020
course is really fast
By Vraj P
•Jul 1, 2019
a little fast paced.
By Jiahui X
•Apr 29, 2016
straight and narrow.
By Mansour H
•Jan 20, 2023
tank you Coursera.
By Samuel Y
•Aug 9, 2021
not for beginners
By Shreya S
•Feb 17, 2017
nice to learn:))
By Diana S
•May 9, 2022
Hard and boring
By Vikramaditya M
•Apr 7, 2020
homeoworks are
By Sushmit R
•Aug 20, 2017
Very helpful.
By Sumit K S
•Jun 22, 2020
Need Update
By 柏一
•Mar 22, 2016
作业和教学有点脱节。
By Brian L
•Feb 27, 2019
too fast
By Andreas H
•Jul 22, 2018
Too hard
By Benjamin S
•Sep 25, 2017
Very cha
By Ajit K
•Jun 22, 2020
Swirl.
By kishore
•Feb 8, 2016
good
By Rahul
•Jul 15, 2019
NA
By Rahul M
•Nov 11, 2017
.
By Jacob P H B
•Aug 5, 2021
I want to begin this review by thanking Johns Hopkins and Coursera for putting this course together. In the age of "work/learn from home" and "upskilling" it is courses such as these that allow the layman who is unfamiliar with data science to learn basic programming. For that I am grateful. On the other hand, even as this course cost $50.00 (which is reasonable), I still cannot recommend it to other students. As a graduate student, I have had some exposure to R. My statistics class utilized R for HW assignments and basic regression models. Our TA taught us some intermediate coding methods via ggplot2 and dplyr. I primarily took this Coursera course as a refresher. It should be noted that the course description encourages - nay, states - that beginners should do just fine taking the class. Nothing could be further from the truth. The course instructor is clearly a brilliant man who is a leader in the field of data analytics. I'm sure he is also a very well-respected lecturer at JHU. However, I felt like this whole course he was speeding through the content. I had to use 0.75 speed during the lectures so I could hear everything that he was saying. On top of that, he used a lot of R jargon that made the content seem more exclusive to students who already have a background in data science. Finally, there were limited opportunities for students to apply the skills that we learned in each lecture in the actual R environment. He took screenshots of code, explained it in an opaque fashion, and then moved on to the next lesson. That may be fine for some students, but I personally like to 'drive' when I'm learning how to use a car. The one bright spot in this course was the interactive swirl sessions which did allow you to put some concepts to good use. It should be noted that these are optional. In my opinion, if you didn't do the swirl assignments then I can't see how you took anything away from the course at all. Still, the swirl module could be clunky at times and could use updating. In addition, some of the answers in swirl simply required you to copy and paste what you were previously shown, which isn't very challenging. My final qualm with this course is the "programming assignments." While the swirl assignments were probably too easy for the layman user, the programming assignments were insurmountable tasks. There is a HUGE gap between what we learned in the modules and what we were expected to perform in the assignments. I don't understand the logic of teaching concepts, implementing what we learned in simplistic interactive swirl sessions, and then taking on advanced assignments. How does that help the beginner student at all? The teacher encourages a "hacker mentality" but in my opinion, struggling and googling your way to get the right answers isn't learning, it's insufficient teaching. It would be one thing if this course was advertised to advanced users. If that was the case, fine, the student should probably be able to write some of this code. But that was not the case and from the comments, it seemed that many other students also struggled with the program assignments. The teacher also dove into statistical theories in week 4 without explaining them. No offense, but I don't understand how we can possibly grasp linear models and Poisson regressions in a sub ten minute video. In summary, don't take this course if you are beginner or looking for a refresher. The content is outdated, the pace is too fast, and the programming assignments are disconnected from what you learn in the videos. One would be better off watching YouTube videos or taking a Udemy course for free.