Отзывы учащихся о курсе Introduction to Data Science in Python от партнера Мичиганский университет

This is not an organized course by any means. The lectures do not cover much and assignments are incredibly tough to the point that each requires more than a week by themselves.

For context, I have completed the Python Specialization by Dr.Chuck (Which was incredible!) and have an Fulltime-Masters in Engineering. One of my main motivation for taking this course is to learn all the topics in well structured manner but I don't understand what Dr. Brooks trying to do with his bizarre way of 'teaching'. Unfortunately, Dr. Brooks just points to StackOverFlow for everything rather than explaining the concepts by himself.

Currently, I am just learning through various Pandas Lectures in youtube and attempting the assignment (which is harder than most assignments I have completed in my college!!). Unless you have great motivation to learn by yourself, this course would be very hard to complete.

While the material is undoubtedly useful, te structure of the assessments is not very helpful. For example, in week 3 we are asked to create data frames from input files: these are presented in descending order of complexity for cleanup. Furthermore, the points for most of the questions are 6.66, despite what are very different demands fore each part. In the final week, the dictionary of state names is counterproductive in answering part one (some state names are region names) and one can either get 100% or one fails the course (as one question is worth 50% of the grade.)

Some of the autograder feedback is so terse as to be downright infuriating. Add to that frequent issues with the notebook crashing and much of this coursework was an exercise in unnecessary frustration rather than increasing enlightenment.

Primary instructor is very good and very clear. Although I feel that in the MOOC format he could have spent more time going through the mechanisms going on underneath (even if you don’t need it to complete the problem sets). However the lectures from the assistant are poor - he seems to speak without explaining anything.

Major issue is the problem sets themselves. Some of the questions are really poorly written (and I think in some cases wrong). For example in week 4 I spent longer trying to debug a question (that I got right) than I spent on the whole week put together; the answer being something that wasn’t explicitly asked for in the question.

If you’ take the course read the forums... there are dozens of posts from students (and teaching assistants) complaingin about the questions.

Unfortunately, the course delivery style was not right for me. The profesor background is good, but the teaching style is too much talking (difficult to remember), and that doesn't helps to understand Pandas or Numpy concepts. There were very few visual aids. The course uses Jupyter notebooks with code examples, it would really help to add some written explanation to them, because the explanation in the video goes too fast. It would be great to have more practice to construct gradually the knowledge at least at the beginning. Most of the learning was on my own reading books, python docs which does not focus on conceptual explanation, and using stackoverflow as it was recommended during the course. This course is for somebody that does not expect much guidance or explanation.

il manque beaucoup de théorie, je me suis retrouvée à perdre énormément de temps à chercher sur internet pour pouvoir répondre aux Assignement. Au point, on l'on se demande à quoi sert le cours (version video) à la base, car si on nous avait donné les Assignement seuls sans le cours ça aurait été pareil !

c'est à dire que : durant le cours je n'ai absolument rien appris ! De plus, le fait que le cours soit fait dans dans l'open space et qu'on voit les gens travailler, boire de l'eau .... ça déconcentre énormément.

Néanmoins, comme que suite aux recherches que j'ai fait j'ai appris beaucoup de chose et ça été grâce aux assignements qui même les questions étaient assez vagues (exemple total ou top ?? ça prêtait à confusion )

C'est pour ça que je donne une note de 2/5.

merci

Completed the first course but probably won't continue.

U of M auto-grader uses an old version of Python (3.6) and an ancient version of Pandas (0.20.2), so after you code everything up in 3.7.7, you have to go back and try to get it to work in 3.6 and old Pandas. This just comes down to how you want to spend your time in life: learning and solving problems or messing around with an old auto-grader.

This is a total waste of time and effort. There is no reason to spend time doing this just to appease the auto-grader.

I was considering the Data Science Masters program, too, but I want to learn, not fight old versions of Python and Pandas. Good to know now, I guess! What a shame. This series could have been great!

Course teaches Python Pandas in a very practical way and I'm sure now having learnt it I'll use the skill. But this course wasn't taught well. Weekly assignments asked questions about skills that had not been taught yet. The course coordinators didn't respond or help in the forums, The topic area deserves more in depth video lectures and discussion. All the above basically means that passing the weekly assignments takes longer than you may assume. Had the course been taught and tested more effectively then doing the weekly assignments would less frustrating and time consuming.

Basically the course is good, but it requires much more work and research because of the poor way its caught and monitored by staff.

Course content is very scarce as compared to what is asked in assignments. No explanation is give to what function does and what should be its inputs and outputs. Unlike Professor chuck's course this course is very tough and not at all an introductory course. Assignments take 4x more time than mentioned in course content. Overall a very heavy work for student to go through other online materials to understand what each function does. It feels like I have learnt alot from other websites than in this course. What is the point in taking a course if I have to go through other materials from some other website? Please change course content, make videos more elaborative, reduce the difficulty of assignments.

The instructor reads during lectures, making them hard to follow. In-lecture quizzes are inappropriate as they cannot be answered without further research outside of the material covered in the lectures. (That is appropriate for assignments and projects but not for in-lecture quizzes.) Finally, the quality of the feedback from instructors in the discussion forums is low, including incorrect/misleading answers. Another annoying feature is that the notebooks expire after a much shorter time than it takes to complete the assignments. Autosave does not always work. So it's possible to lose work. On the pro side, the material covered is relevant and I learned a lot in doing the assignments.

Positive aspects:

Readings were relevant and interesting.

I learned a lot.

I was challenged.

Negative aspects:

Programming assignments took SIGNIFICANTLY longer than suggested (I have 20+ years of programming experience and am fluent in 3 programming languages, but I'm new to Python).

Course did not provide enough support to learners. You're on your own to learn the material and you won't get timely responses (if any) from the staff. I asked clarifying questions about lecture material on the Discussion Forums and got no response (twice).

Several concepts were not taught with appropriate detail / explanation. For example, there was no instruction on how to read error messages in Python.

This course is a mess:

-Not well structured

-They don't properly guide you in the learning process : better courses from better universities, as Stanford ones, describe all you need to complete an assignment, or give you a good and deep introduction to the libraries/framework you have to use... here they just explain part, non including many info you need in the assignment, so, you have to spend a lot of time trying to find proper documentation, reading other external tutorials, checking people with same issues in stack overflow -some even with the same datasets, I am not sure if they were from the same course

A lot of stuff to improve, I recommend to you to look for another course

I have learn a lot by taking this course not from the instructor or TA but through stackoverflow. There is clearly a gap between the video and the assignments. The instructor are knowledgable but less of ability to instruct. When watching the video, I need to pause to clearly read what instructor just typed. I feel like the instructor is reading the screen without clarifying the contents. There are a lot of times I want the quit the course but I finally make it, so proud of myself. Working on the assignment with the help of stackoverflow, I learn a lot.

In sum, I really think the instructor needs to improve the way he teaches and the assignments are useful. Thanks.

One thing I dislike a lot about this Specialization is that it forces you to work through their structured weekly materials rigidly. It does not allow you from working on Week 2 and Week 3 courseworks when you have finished Week 1 materials which I think it is just a way for the course owner to make more money from you. Their excuse is that they allow 'other students' to mark your work to promote interactions between students but I think this makes no sense as not people who takes these courses have a uniformed fixed number of hours each week. The whole point of studying an online course is to be flexible with the hours you put in, which this isnt.

The aim of the course and general guidelines are fine.

BUT!!!

It s aweful how the explanation s given.

Main idea of all videos is: here s a function, here s another one, also you can use this function.

Now you 'go girl' try to glue all the puzzles together by yourself.

It feels like professor was just rushing to record videos and get back to his work which gives money.

Never-the-less i did learn A LOT from this course which i couldnt do by myself since as i said GENERALLY GUIDELINES are OK.

PS. The WEEK4 last assignment was the main problem since i had to watch about 6-8 hours of statistics to truly feel and understand VAR, STD, TTEST.

I would recommend the coursera online training session need more improvement. Please look at this youtube video. this will give you some fair idea what do i mean.

https://www.youtube.com/watch?v=V0AWyzVMf54

During the session speaker need to be visible on top corner and they need to present with more examples during learning this will help and learn fast.

I struggled a bit following your videos going back-and-forth with the given materials.

I also struggled solving the assignment due to confusing questions. Not much clear what is required to solve the problem. it would be helpful to provide some hints for each assignment.

The content of the course is really good but the outdated version of Anaconda they are using is a real pain, because you can't use many features available and causing serious problems when trying to submit the assignment. For a course like this you should consider using at least a recent version of the tools.

Also the speed in which the instructor is talking is like a machine gun, without making almost any pause, and thus making really difficult to keep up. I don't know if they modified the speed of the videos or it is the way the instructor usually talk. I strongly suggest to review this aspect of the course.

I decided to take this course after having a great experience with "Python 3 Programming Specialization". I was expecting the same kind of experience from this course but the lectures are pretty fast. The instructor seems to rush through the lectures and keeps on recommending using StackOverflow for any questions so I finally decided to unenroll myself from this course. I recommend you to install Jupyter notebook, buy "Python for data analysis" by Wes McKinney and follow along with all the book exercises. You will have a way better experience learning data analysis than this course.

Assignements are awfuly messy written. You spend way more time on trying to figure out what the author of question had in mind than on working on your Python coding skills. The instructions are unclear and You have to dig trough the forum to understand what You have to do. What's more, even teachers that help on the forum agree, that instructions are unclear.

It's even more frustrating if You realize, that if someone from University of Michigan spent a few hours on making the instructions clearer, then thousands of students woudn't waste millions of hours inefficiently.

The professor sounds like he is reading script. He uses so many hand gestures, his phrasing, his monotone voice, his hand movements, and pace of explanation makes it hard to focus on what he's saying. The woman was even more monotone. I'm not one to make a fuss about teaching styles given that I was a math major and had professors that barely spoke english, but this course is taught terribly. On top of all of this many of the programming questions could have been better worded. Many of the questions seemed unclear. This course could have been much better designed.

Though the syllabus for this course was well designed, I found most of the concepts being taught very fast or without explaining it clearly. I had to go and refer a lot of other YouTube videos to understand the course videos much better. In fact, the YouTube channel called Corey Schafer helped me more compared to the course videos to complete the course. I would suggest to slow the pace of the videos and explain the necessary concepts even more clearly.

Here, I would also like to appreciate the Assignment questions. They were very well set and challenging.

The class was a helpful intro to pandas. But it was not as much a class as it was a series of homework assignments and the student painstakingly looking things up on stackoverflow. In the end, i am positive I got the correct answers using a horrible coding method and will never see the correct solutions. There should be a little bit more handholding in order for the student to learn the concepts. Otherwise, I might just throw a class up on coursera, give the link to docs.python.org, tell the students to read it and then they will be experts at python.

"Course" is very self-directed. There are very few exercises, and there is minimal feedback on those exercises. No attempt is made to reinforce learned knowledge over time (e.g. spaced repetition) nor is there any definitive list for what knowledge should be gleaned from this course. Emphasis is placed on the student's teaching themselves and learning through experience with no attempt to actually understand the learning process or rest the course design on a scientific basis. Standard filler course for an empty education system.

The course instructions are very limited comparing to some of the other Coursera courses I've taken. The video lectures and code examples are extremely high level and general, while the assignments are significantly more challenging than the content demonstrated in the lectures. I spent a significant amount of time reading the Discussion Forum and googling for the right codes to use, rather than actually applying any knowledge learned from the lectures. If I wanted this much self-learning, I wouldn't have taken a Coursera class.

I have to say, as a new data analyst, even though I have started my work. It is still difficult to complete the assignment. The assignment is far away from the lecture video, which makes the assignment painful and you may lose interests in the process. Even the assignments are not written in a understandable way, so you have to go to forum to clarify each question in the assignment. So please make the learning process me more enjoyable and easy for the starters. Data science is a great career and and I believe it is the future.