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The content is good, but I have some comments that would make it a lot better. On the one hand, R is a programming tool so this is by no means an exhaustive program, but rather a light introduction. However, when following along, some elipsis were made and I had to keep checking with resources to understand all that was done during the exercises and lessons since there was a lot more than just what was being explained. Providing further context on why some stuff was being added to the lines of code appearing would be useful. Also, in the spirit of lightness in this lessons, a more guided programming approach would probably be better. I'd probably prefer to have more guided exercises in R on understanding what you can do (working with different datasets as well) rather than having to fill out the 'reflections', which you could clearly see they have all been looked up in chatgpt. I have a better sense now of R, but would have preferred to have probably had a more hands-on approach in this case, using google collab or Python instead to align better with what's been most widely used nowadays too.

I wish the course was longer and there were some more lessons in the hands on programming. I'm stuck now doing my capstone having learner VERY LITTLE about programming with R, for instance, cleaning data is not merely pulling up the names of all the columns in a dataframe. That's just seeing what you're working with, but in the Coursera course that was considered cleaning. I can't do any merging of dataframes, which would have been WILDLY useful. And I realize you can't cover everything, but I feel like Google and Coursera, together, didn't cover enough. This could have been such a fun course, and I was hoping it would have been slightly closer to a boot camp, but it wasn't. Not enough covered. I loved all the other courses (granted I wish ya'll covered more in SQL, BigQuery, and Sheets too) but this one seemed a big like the tip of the iceburg and cutting corners.

The instructor speaks clearly, materials are presented clearly, the free version of the RStudio (Posit) works well and is enough to do everything the course requires. However, the course is way too easy/simple to be of any use. There are VERY few exercises. On those few exercises, it tells you what to put in, it's hardly any challenge (there is also a separate file with answers). The quizzes are also very easy. I had no prior knowledge of R going into this course but I know other programming languages and have been working in the data industry for years. I'm sure those experiences helped in making the course feel easy. However, I'm absolutely sure that with the amount of skills gained from this course, there is no way one can perform even the most basic data analysis task.

The class is informative, but the instructor rushes through some of the material without thoroughly explaining how she got from step A to step B and doesn't provide enough instruction on which files and packages need to be loaded before a video demonstration begins. In addition to this, whoever put the class together got lazy toward the end as they just dumped extremely long readings about R Markdown into the course without providing adequate instructional support via video demonstrations. Overall, the class blends in well with the rest of the program, but I would suggest learning the basics of R prior to this course and reinforcing the key concepts though additional sources afterward in order to develop a working knowledge of R.

I wish the course continued with the split screen practice when doing hands on. I also would have enjoyed it more if the course did not flip back and forth between SQL and Excel just do one at a time without the back and forth comparison. For beginners in some of the program I felt that some of the coding was a little too advanced for the little amount of teaching that was given for someone new at this to type out long and compound lines of code, and there not a step by step pace for video instructions. There were times I had to slide the video back a few times to see where they clicked to get this and that to happen. The overall beginning of what data analytics is was good.

Not finished yet. I like the pace of the course, and the many repetitions, this helps to foster the knowledge. I am happy to have participated in this course, and I think it helped me understand the very very basic principles of R. However, one large minus: the women/teacher in the video is way to seductive and speaks very artificial, it completely steals your attention and concentration. She could speak more normal and objective, rather than immersive and subjective, this is just way too much. This became very annoying, as one is mainly focused on her (seductive) face expressions and voice and not on what she says.

Great job at lying down the foundations so well thought out in terms of hierarchy . However, the breadth of material covered in 5 weeks, can be improved. Think of it this way: ANYONE can and will google EVERYTHING as it has become a habit at the current time. One could have googled all commands provided in this course in an hour or two (less than 20 commands covered in this course) and practice probably 10 hours to master them. These commands are pretty self explanatory after all and are independent of one's background. Could have been a lot shorter and more practice oriented.

It could be much better. Many times same material was repeated 3-4 times wasting our time instead give real-life examples of analysis. Also, during the entire course, the teacher was using the same example limiting the possibility to learn something new. For me, it looks like the authors didn't have idea what to teach us.

R language is really very interesting and could be very helpful. Pity that course didn't focus properly.

...and every time repeating "load packages/libraries" is insane wasting our time.

To me, this course is not for the absolute beginner, even though you took the previous Data Analysis certification courses. There are some concepts learners need to know before they start the 1st lesson of programming language, otherwise they are going to lose. Luckily I have friends and class that help me to go through this part, and bring me back to the track again. I hope this course can at least introduce those kinds of concepts at the very beginning, it will help a lot.

This course could have been far better. It was incredibly frustrating to try and follow along with the examples and several of the practice quizzes used files from previous sections/modules that weren't mentioned as being needed for future practice in the course. It is also very weird that earlier sections are set up as temporary workspaces in R Cloud, and later ones work from files that we should have saved but aren't provided.

This course had a few pitfalls. When using RStudio Cloud it would not allow the installation of the Penquins packages and also there were no instructiions on how to import an excel or csv file into the RStudio Cloud working directory. That was frustrating and made it very difficult to do the assignments. Something I think the course administators should look into. Overal great course though.

This was a great introductory course in R; however it wasn't as comprehensive as other courses that I attended before.

Another thing I didn't like is the fact that this was supposed to be the ACT phase of the data analysis process, but we did everything other than that. It was a repetition of the other phases using R.

I really enjoyed this course, and learning about Data Analysis with R Programming. However, when taking numerous exams, I received a "processing error" after writing my code chunks after I began the exam. The only thing I could do was guess, and then pray I got the answer right. This happened NUMEROUS times.

I think the information is valuable and the woman presenting it is lovely, but the explaining went too fast, and if it is a course aimed to beginners, we need to know what we're doing, not just write things and say we will explore it later. I liked R, but will need further training to understand it.

Video & Reading sections could be combined using rmd-based follow alongs. Questions are sometimes irrelevant (too much focus on names instead of actual use) or childish (the open questions "How would you use this bla bla bla". Obviously, there is zero bias caused by loving Matlab and hating R ;-)

It's a good opportunity for students to practice and apply their knowledge, which would help to reinforce their understanding of the material. I would recommend this course to anyone looking to learn the basics of R Markdown and improve their skills in creating reproducible documents."