R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing and scaling useful data science results and products. This Specialization will give you rigorous training in the R language, including the skills for handling complex data, building R packages, and developing custom data visualizations. You’ll be introduced to indispensable R libraries for data manipulation, like tidyverse, and data visualization and graphics, like ggplot2. You’ll learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers. This Specialization is designed to serve both data analysts, who may want to gain more familiarity with hands-on, fundamental software skills for their everyday work, as well as data mining experts and data scientists, who may want to use R to scale their developing and programming skills, and further their careers as data science experts.
A very good course to read and get the valuable content of R language. This is for the students who want to learn and practice the basic and some intermediate concepts of data manipulation.
The last problem is unnecessarily difficult with little related teaching and learning material provided. Otherwise, the course is certainly well worth taking.
Very good course for intermediate/advanced R users. Sad that you are elegible to do assignments only if you pay.
very useful, especially the final practical exam.not 5 score because I think more time should have been spent in more modern interactive charts
This programming assignment got me to practice essential coding skills for writing and deploying a package in R, which is super helpful.
First three weeks materials are amazing, and I like to interactive with swirl(). If there are some more videos rather than reading materials, it would be interesting.
Brilliant course. Loved Week 4 for OOP. This was really new for me and would love to have been able to see its application in real world examples to better cement the concepts.
Useful programming exercises to guide learning the basic elements of R packages. Also glad that I got my assignments graded within a week following submission (thought it would take much longer).
It is a very good course, but feels a bit more hands-off than the other 3 preceding courses in the Mastering Software Development in R certificate.
This course is excellent! I truly learned a lot about software development with R. The only problem is that it is open a few times a year, due to the small number of participants.
Excellent class. I had already done a lot of the swirls and would have liked that to be in my record somewhere, although it really wasn't hard--and was probably good--to repeat them.
Great course but would prefer more video lectures versus text based lectures. Otherwise, a great course to help build out the foundations of R programming.
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This course should be removed for two reasons:
1. The only videos are the introduction videos. Everything else is a text-based assignment. This is just lazy. If I wanted to google how commands worked, I can do that without paying for Coursera. There is no instructional material contained in this course.
2. The student is required to submit assignments through a third-party interface that doesn't work. Completed assignments are not given credit. There are many people in the discussion forums saying the same thing.
This course uses a software package developed by the instructors for a portion of the required tests. There are serious bugs in this package that make it impossible for students to complete the tasks assigned. Going through the discussion boards, these flaws have been present for at least 2 years -- clearly Johns Hopkins in general, and the instructors in particular, hold the students' time and learning experience in such low regard it borders on contempt.
The content is good, but many students (including me) are NOT able to submit assignments with the course "token". I've commented in the course discussion forum about this, and I have opened a support ticket with Coursera, but no one is taking serious initiative to correct the malfunction.
Great gap between teaching and what is required to pass the course. Unnecessarily difficult.
The didactic material is not compelling.
Not recommended.
Not possible to submit programming assignments, this course seems to have a lot of technical issues. Signing out during the first week and un-enrolling the specialization. I'll check again later to see if those technical problems are solved.
This course, and the Specialization as a whole, is poorly structured and a rather cursory overview that is unlikely to satisfy serious learners. If the material is completely new to you then it will likely leave you confused as it does not adequately explain the concepts. If you are already somewhat familiar and are looking for deeper dive into R and programming you will be disappointed as the courses just don't have the depth of material needed to gain mastery over the subject.
Your money and time would probably be better spent on a couple of books by Wickham.
The course dumps a ginormous amount of content onto learners while being extremely poorly structured. The course materials are littered with spelling and formatting errors. There are assignment segments in the course that require R functions that were not covered in the syllabus. Multiple datasets required for stepping through the course materials as well as required assignments were at best not provided by mistake or neglect (datasets.zip file only contains the "Team Standings" data), or at worst provided only with the purchase of the textbook + dataset on top of the Coursera subscription fee. Some of these issues could potentially have been solved by having more responsive instructors in the forum, but they were nowhere to be seen, and there are questions with datasets or swirl token that date back years without replies. Overall, I highly recommend spending your money somewhere else. Perhaps downloading swirl alone with all its free materials without going through this course is a good start.
Swirl doesn't allow some codes even if its correct. '=' is not allowed for example.
When a number of students ran into an identical problem with an assignment, there were no support or help, for weeks. By the end, we never got any support. A work-around the glitch was found by a student. For a paid course that is not optimal.
Completely disappointing. Much of the practice is performed in R using a package named swirl(), ehich produces an incredible amount of errors in a lot of silly aspects such as only checking if the code you wrote is exactly the same that it has stored as solution, rather than checking if the solution is the same.
The assignments are also awful, the test questions are poprly written, the R dataframes have errors in the name of the variables, the forum is outdated (since the last comments observed correspod to 2016)
Im canceling my subscription to this course right now.
If I wanted to read a book, I would have bought the book.
There are also many "right" ways to code, and the swirl tutorial, while helpful for learning specific syntax, should not grade correct answers as wrong simply because they use a different syntax. It is overly rigid.
this course basically just has you run through the widely available SWIRL packages and then gives you a quiz it has poorly prepared you for and charges you for the privilege.
Not at all engaging. Its like a university lecturers notes without any personal interaction or videos.
There was no mentor to help.
I really enjoyed this course. I thought it was a really good introduction to R. I thought Swirl was a really good tool as well. The Week 02 Swirl assignment was more time consuming than the others and the Week 04 quiz which required hands on problem solving was very good and an excellent review of the materials. I would emphasize to future students to review the online textbook and to be prepared for Google Searching in order to answer some of the questions especially from Week 02 - 04. In other words, not everything one needs to pass this course is solely contained within the weekly chapters nor the suggested textbook. I assume however; that this is by design to stretch the student and to force them to put time into learning and understanding the materials and searching the Internet for additional help. Bravo!
Loved this course! Beware that the material is at an intermediate level, and not really appropriate for beginner R programmers. The final quiz was extremely challenging, as it should be, and very useful.
I give this course six stars and take one away for the automated upload of answers from R (the swirl package). This package /process is really buggy and causes needless grief especially in Lesson 2.
The content of this course is A+++
This is a really great introductory course to R as a programming language. By the end of it, you do become proficient in reading data from different formats into R and in performing basic data manipulation routines using cutting edge packages. Fantastic if you are a beginner. If you are already fairly experienced in R, only the last week of the course may hold some interest to you.
Amazing course, I would say addictive. However the swirl lesson #12 on Data Manipulation and quiz of week #4 on Reading and Summarizing Data offer a huge difficulty spike in comparison with the rest of the assignments. I would say almost too high compared to the rest, I would rather increase the difficulty gradually.
This course basically consists of reading the book, Mastering Software Development in R, that is available via LeanPub as well as at https://bookdown.org/rdpeng/RProgDA/. (Starting with the fourth course in the specialization, the authors didn't even bother to enter the content into the course and instead you read a paragraph or two and then click the link to finish reading what's at bookdown.org!) Though the bookdown.org link has a December 2020 date, the course feels dated. I'm glad to have completed this course, but the second one has left me waiting for several weeks for a peer review. I'd recommend you complete this and later courses as an audit, at least in your mind, since it's highly likely that it will take weeks or months for you to get the peer reviewers needed to finish the course. I'm disappointed in Coursera continuing to offer this course and specialization; it's a trap!
The content of the courses in the specialization are fine. it's just that the whole specialization has been abandoned.
Excellent tour of basic R programming with many examples and well thought out assignments . The final project uses a real life data set and it was fun to use dplyr piping to find the correct answers. The Swirl program, which is downloaded inside of R as a package and is used for grading, was a little cumbersome at first, but once you get the hang of it, then it's not bad. Hang in there and don't give up.