Opiniones y comentarios de aprendices correspondientes a The Data Scientist’s Toolbox por parte de Universidad Johns Hopkins

Extremely Git centric

Too easy, very basic

Too short and easy.

Not really useful.

Sound is too quiet

Barely any depth

Not very useful

Way too basic.

Too simple.

Very basic

Too basic!

Very basic

Useless

ok

B

The first week has one assignment: a five question quiz that reviews the syllabus, course/program design and purpose. As someone with multiple degrees and a PhD significant other - both of us work, and are successful, in data analysis and research. My career is centered around Business Intelligence. I was hoping to engage a program that would help me develop R programming skills and build my skill set. After watching all the videos twice, taking notes, completing almost five hours of online research into the topics that I encountered during my first attempt at the quiz, having my significant other review the topics & questions with me, I still failed to pass the quiz after ten attempts. Hence, a syllabus quiz is my roadblock to moving forward in the program. This is not pride, I am not imagining myself to be a genius who is insulted by this failure. Frankly, no one is stupid enough to have not been able to comprehend a syllabus and course desi

The Amazon Polly robot voice has to go. It may make it easier to update the course on the instructors' end, but it degrades the quality of the course from the students' perspective to a degree that is not even close to acceptable. I'm surprised they are trying to get away with it despite the primitive state this technology is still in.

As for the course content; this is certainly not for a beginner. Not because the content is difficult, but because the way they teach it is terrible for someone who isn't familiar with R already. They just shoot a million concepts and definitions at you with short descriptions and little examples. I tried to take this course years ago as a beginner and it was so discouraging. Now that I have a few years experience, it is a good refresher and nice to pick up a couple new tips. That's all it's good for though, a refresher.

most part of this course is a duplicate of the "R programming" course.

microphone/sound of the teacher quality is very bad.

not original, boring, dividing this in "4 weeks" is too ridiculously long, this should be done in 1 week to enable users to take more time for the "R programming".

this course should be free. don't lose too much time on it, it's doable in a day or a weekend and move on to "R programming".

asking for so much money to see how to install R and github is a shame.

feels like this course has been added just to have a round number for the specialization.

even the survey in the end asking for feedback starts with a question not adapted to moment it's been asked "did you get a certificate?" of course i did not as i've just finish the course and now wait for my peers to review my final submission.

Very unimpressed with the justification of leaning on automated voice instruction for updated content, when the content is still outdated. For anyone who prefers human interaction, intonation, a sense of engagement with visual queues, will be disappointed. This misses the mark as having any merit beyond a reading manual. In fact, a book is outlined more effectively, because the instruction is approached with reading in mind, which is not the case in the written form provided. Truly disappointed and will not continue with future Johns Hopkins course offerings.

I am sorry but the robot-based voiceover, extremely slow pace, and lack of interactivity made this specialization unbearable. Additionally, choosing R over Python seems illogical for many reasons, such as Python being the #1 language for data science, ML, AI (if you'd ever consider specializing in these areas).

Poor experience - gave up after the 3rd week and started the one from Michigan (applied data science w/ python).

Git should be introduced more slowly, over multiple courses. I cannot possibly absorb all the command line instructions that were mentioned in the class. There are just too many.

Please PLEASE *PLEASE* spread out the course content on Git over 3 or 4 courses, so we can practice it as we submit assignments. I forsee numerous wasted hours fiddling with Git Bash trying to make it work, not knowing what mistake I'm making.

$38 is a lot to pay for tutorials about how to install software. This course takes only 20 minutes to complete. It is also obsessed with command line interfaces. There's a reason that they were left behind in the 80s. It does cover GUI software like Rstudio, which is ignored for the rest of the course. How about something on the desktop Github version? https://desktop.github.com/ So much easier to use.

Quizzes were based off of extremely high level overview videos not covering anything specifically or deep diving into anything. When applying the git commands covered, numerous errors arose. Overwhelmingly academic course with very little hands on. This is not for anyone actually looking to work in this field, but for someone looking to be able to talk about this field.

No value as a stand alone course, as completing it provided no more knowledge, skills, or attitudes than, say a 15 minute Ted Talk would. May help prepare me for other courses in the Data Scientist Specialization, but it's difficult to say until I complete those courses. I may come back and change this review after completing other courses in the specialization.

While it's amazing to save costs and resources by creating automated voice-overs, it would be helpful if commands on the screen match what is being said. It was quite challenging going back and forth between lecture videos and lecture notes to copy and paste commands. I find it time-consuming, and I hope this problem can be rectified for future classes.