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Kursteilnehmer-Bewertung und -Feedback für Introduction to Data Science in Python von University of Michigan

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4,677 Bewertungen

Über den Kurs

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python....

Top-Bewertungen

PK

May 10, 2020

The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans

SI

Mar 16, 2018

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .

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101 - 125 von 4,609 Bewertungen für Introduction to Data Science in Python

von Gina G

Apr 07, 2020

I think all the assignments in this course are interesting and well designed. I learned more from doing the assignments than watching the videos. Yes, it took me a lot of time searching and reading stack overflow and other similar resources, but I did learn from them.

Most of my frustration was in fact coming from their outdated Autotrader - for those who plan to do the assignments on local Jupyter Notebook, you'll run into some confusion and frustration with their Autograder as their Pandas are not as updated as your Pandas. This means that even though your code can run perfectly correct on your local, it doesn't mean it would do the same with the Autograde after you uploaded for grading. I spent tons of time, not on debugging exactly, but on figuring out why my code won't just execute after submission. I guess my advice to avoid similar frustration would be just writing assignments in the Jupyter Notebook on Coursera.

As for the video lectures, I agree that they could and should be made better in terms of pedagogy. I'm sure the professor and the teaching assistance are absolutely knowledgable on the subject, but their teaching style is way too stiff. Basically they were just reading off a prepared script, which was not colloquial at all, and they rush through it. I don't think coding skills can be taught in the way of lectures as if delivering a TV speech. Honestly, lots of free youtube videos are better at online teaching than this course.

This is an intermediate level course in python, but entitling it as 'Introduction to Data Science in Python' kinda devalued how much of strength people have to spend on finishing it.

But all in all, I did learn a lot from completing this course, thanks to the well-designed assignments. I would recommend this course to those who wouldn't mind spending more time doing their own thinking and research.

von Sercan B

Jul 15, 2020

Assignments should be peer-reviewed. Spent most of my time trying to figure out why my code run successfully on Jupyter Notebook but not getting any grades on Coursera Grading system. Especially the Assignment 3 was a nightmare for me. Eventough I was getting the right outputs on Jupyter Notebook I had to spent several extra days to fit my code for the Coursera Grading System. Apart from that assignments are forcing learners to get more insight in python individually, which was great for me. If you're total beginner to Python there is very high chance that you may drop the course due to assignments.

von Aman j

May 07, 2019

Concepts could have been taught with more explanation. I prefer learning from books. On trying this video course, it seems VERY tough & so time-consuming to learn. Elaborate explanations could have been provided.

Or at least if I could say, I already knew basic Python but learned Pandas for the first time. Advanced Pandas should be explained with more videos, more steps.

I needed to replay video parts countless times because of only higher level explanation in videos

von Benjamin L

Jan 03, 2019

Almost every course everyone complain about assignments being hard..... but this one is EXCEPTIONALLY hard. Last question of assignment 4 is compulsory to pass the course and trust me it will bring to you trauma and pain like you have never imagined before.

Otherwise the lecturer is actually pretty good, and the other assignments are great for learning!!! I really think they overkilled it with assignment 4 though

von Pascal B

Jul 27, 2019

Generally, very good selection of content. The explanations are insufficient for passing the assignments tho, which means that most of the course work is self-study from the web. The buggy auto-grader sometime made the submission of the assignments quite a pain as one has to find a way to change the code in a way that still produces the right answer but doesn't blow up the auto-grader.

von Minyi Y

Nov 20, 2016

The content and assignments are certainly useful and relevant. However, the lectures are too short and do not help much with doing the assignment. As a beginner, I relied heavily on google and the discussion forum to get through the assignment. And I am not sure if i can actually tackle similar problems again without referring back to the pre-mentioned resources.

von Julien

Sep 20, 2018

Interesting course covering the main introduction topics to Data Science, however there is a too large gap between the theoretical (videos, Jupiter notebook examples, ...) lessons provided and the knowledge required to perform the assignment. The time to do individual research to perform the assignment is tremendous. This is not an easy course at all.

von Claude P

Nov 20, 2016

More concise coding tutorials and less "search on your own on the internet" needed. It is great to get to know the online community and the course needs more coding example directly relat to exams.

von Tom M

Dec 29, 2018

A lot of self directed learning, bordering on excessive. Sometimes it takes some investigation to figure out why the autograder did not pass you. Overall, I felt I learned a lot, much on my own.

von Pamela T

Feb 02, 2019

This is a great overview for python, but the materials/videos/slides are very elementary compared to the sophistication of the homework. Required many more hours than the estimates.

von Colleen K

Sep 22, 2018

I learned a lot by doing assignments, but the course materials are not helpful. Stackflow and Python documents guide me much more than the course itself.

von Erico L

Mar 02, 2019

I don't think I've learned much along the course. I had to pick a few concepts here and there, but I don't think that the way in which those are explained would stick.

Also, the course seems rushed: I'm not sure what the end game of these courses is, but I think it's an incredible wasted opportunity when it comes to MOOCs, as there could be more lengthy videos and more and better ungraded exercises (something that in this particular course do not exist) and much, much better explained assignments (I guess adding there the info from the forums by the teaching stuff would not hurt).

For being a course of intermediate level, the videos and explanations are too short; there are even places where things are left totally unexplained.

Even if it's supposed (and even encouraged) that the students seek information on their own, the lack of context in some places makes it rather difficult. this is specialy more so with the questions that are interwined in the videos, as normally in order to answer them corretly you have to go out and find the related info (something that totally disrupts watching the videos).

finally, the assignments are a wreckage; some of the questions are incredible difficult to understand, if not out right impossible. The fact that there's a lot of information added to the forums by the etaching stuff, up to the point that the more complicated questions are easily answered with that same infromation, proves this.

I do think there are examples of courses in Coursera: I recently completed "Mathematics for Machine Learning: Linear Algebra" and even thought I don't think it's not without its issues, I find it a much more challenging, entertaining and fun course, that covers in a good way its subject.

I have to commend the people from the teaching stuff that are in the forums, thought, as it's the only course in which I found people from the teaching area activelly participating, and helping the students.

von Zayd A

May 28, 2019

I had done "Python for Everybody" from Charles Severance which I had found excellent, with the instructor being passionate and the pace being just about right. I had assumed it would be similar for "Introduction to Data Science in Python", but that wasn't case. The delivery of the course is at a very very fast pace, you don't even have time to stop and absorb the functions and methods that you are supposed to learn. The instructor and the research assistant will list the functions and methods one after the other without pausing. The assignment is then extremely hard with no resemblance to the material in the course (I couldn't do it even after having reviewed the videos). After holding on for the first 2 weeks (it's a very useful topic after all), I gave up and decided to learn from the "learning the Pandas library book", which is a very good summary of the main Pandas functions and methods (and which was recommended by Dr Christopher Brooks), and I was able to follow it very easily.

von Sibo C

Sep 01, 2019

Overall: I felt this course was useful but pretty time-consuming. The course had relatively limited taught material and relied a lot on searching & self-studying. If you have a fair amount of time it is a good choice.

Pros: You learn through doing assignments which are well supported by mentors/community. Also, you get used to studying through googling problems and learning from websites such as Stackoverflow.

Cons: Whilst this learning method definitely had its merits, it could be quite time-consuming for someone seeking to gain introductory-level skills quickly. You could find yourself in situations where you spend hours searching for something quite elementary and could easily have been taught to you, which could be frustrating. I personally think this course could be improved by adding a bit more small quizzes for beginners to play around with the basics, before requiring them to self-learn through searches.

von Carl M

Nov 14, 2019

Poorly worded questions (that are mentioned throughout the discussion board), older version of pandas and the course resources don't help you with course. Get ready to 'learn' by looking in StackOverflow or reading the volumes upon volumes of python/pandas documentation. In other words, expect to spend 15 hours a week per week (obviously it will vary)

von Olena K

Mar 28, 2019

The lectures are not good. They go too quickly. They're about 5 minutes long, but you have to stop every minute or 30 seconds and rewind to understand what the instructor is saying. He just goes way too fast, and it's very frustrating. Really ruins the experience.

von Yizi Z

Nov 09, 2018

There is only few minutes taught video courses each week, although the reading materials and topics are quite interesting. The learning of python coding rely heavily on your own trial and error, which you could do even without this course.

von Chris L

Dec 17, 2019

It never felt like the material was covered in enough depth to give me confidence in the ability to do the assignments.

von Lee S

Dec 19, 2018

Starts off well, then escalates way too quickly. Assignment 4 is incredibly complex and has poor guidance notes.

von Georgios A

Jan 07, 2019

Too difficult, poor connection between lectures and assignments

von Kannan S

Nov 21, 2016

This is in fact the worst course so far. Mainly because of auto grader. Here are my reasons.

Actually I did not complete the course at all. But I suddenly got a message saying that I have completed the course. I was working on the first problem of the 4th assignment. I did a provisional submission to see if my answer was right. Auto grader reported the grade for the 3rd assignment and said that I have passed the course. Any submission I did after that was not graded at all.

The assignments are not very clear. Looks like I had a older version of the questions while others had a different version. I was stuck in a particular problem because auto grader did not give me a clear feedback as to why I was incorrect. I wasted too much time on this already.

The assignments require too much research outside what is covered in the videos. I don't feel that is right. The assignment requires that we research on Stack Overflow and Pandas documentation. I strongly feel that such activities should be performed only outside the course work when we try to solve real world problems. Course assignments should be reasonably given based only the materials covered in video. This was taking too much time.

T

The discussion forums are not giving clear hints. When we are stuck in a problem, we are not able to proceed further. I still son't know the answers for certain problems because the coordinators do not explain the answers well. When we complete assignments we don't get to see the instructor's solution.

The video instructions were too fast paced. The instructors do not pause and explain critical aspects of the code.

Overall I am very disappointed with this course. There are much better videos on Youtube and Lynda than this . I am sorry. I never thought it would be this bad. The first course on Python from University of Michigan was really very good.

von Joseph G

Mar 03, 2018

Not sure whether this course is trying to reach data science or Python, but it does a poor job at both.

The class is a light-speed tour through NumPy and Pandas, definitely not for the neophyte Python developer (which I am not). There's 30-40 mins of lecture each week that's basically lightly narrated typing into a Jupyter notebook with only the slightest bit of additional explanation about what the instructor is doing, although the material covered is substantial. There's lot of important details that are glossed over -- forcing the student to pause the lecture and do offline research to understand what just happened.

Similarly, the assignments address and cover beyond the material covered, but the instruction is scarcely sufficient to understand the concepts required to complete them, so lots of Stack Overview and other research is required. And the automated grader, as expected, is completely literal so for complex problems, not much help in validating whether you're on the right track. Assignments take many multiples of the estimated time.

And because even for paying students (such as myself), you never get access to an answer key even after the assignment is due, you have no idea how closely your solution conformed to best practices, even if you arrived at the right answer. For coding, this makes all of the difference, particularly with large datasets that could consume considerable computing resources if not done correctly. I'm told this is because of potential cheating by learners.

How would I change this course? Simple: 3x more lecture material to actually explain what's going on, or down-scope the class so that the existing lecture time becomes adequate for the material.

von Hari B

Apr 09, 2017

Very poor course, badly taught and terrible value for money. The lessons are brief beyond any form of reasonableness, the teacher seems completely unconnected with his students. There is no detail at all and no logical progression. I took and passed this course with a view to doing the specialisation but I'm not going to waste any more money on University of Michigan courses. I've found similar courses on other platforms which cover the same material. The assignments were awful, in some cases they covered material to be presented the following week, in others the questions were wrongly stated and did not match the output from the machine grading. The machine grading itself gave you no clue as to where you went wrong. I'm not talking about the odd question here or there, I'm talking about consistently throughout every assignment. I don't normally, in fact ever, leave bad reviews, I usually just chalk it up to experience and move on but in this case, the course was so bad, I had to say something. I've done two other courses on Coursera with Rice University and the difference to this course is huge, while I would wholeheartedly recommend the Rice Intro to Python courses, Don't do this course, it is not coherently presented or graded. The mentors in the forum tried their best but even they had to admit the grading system was riddled with errors. Absolute rubbish, avoid and spend your money elsewhere.

von Albi K

Oct 30, 2019

I have just completed this course. I have learned quite a bit about the pandas library and that has nothing to do with this course.

The lectures seemed to be scripted; and extremely condensed. At best, they can be used as a sparse reference manual for some undefined subset of the pandas library.

The assignment 4 instructions encourage googling things. Basically "go forth and figure it out on your own" ... why would I need a full course for that piece of advice?

The autograder seems to forbid the usage of certain lines of code in Assignment 4. It will reject your answer and give you no feedback whatsoever with respect to the reasons why your answer was rejected.

As well, it has inconsistencies that will cost you time. The question on the recession_start() function will be graded as correct if recession_start() outputs a certain value, say x. Yet, in another question recession_start() is expected to output some other value y. Go figure. Not even a warning about it.

So, to sum up the salient points:

1. Autograder has holes.

2.Extremely condensed scripted lectures and sparsely sprinkled with practical advice.

3. Useful for letting you know that pandas exist.

Disappointing.

von Vikram A

Aug 08, 2017

This course is poorly done, and I'm sorry but in no way close to an intermediate level. Even knowing a fair amount of python, I struggled with learning from this course. I find it ironic that the teacher specializes in education and mostly sits in a chair and speaks code at you. There are very few visual aids to help.

Furthermore, individual topics are not broken down well, showing you how to develop a mastery over the fundamental data objects like a data frame before moving on to the next. Code that is demonstrated is typed out unreasonably fast, and very few examples are done on how to properly access the elements in different ways. The video where the grad student/post doc spits out code 3 lines a minutes made me laugh at how ridiculous it was as if it were an explanation.

I ended up very frustrated with this course, and I'm not convinced it's all me or my inability to learn. I suggest learning data science in python from another site, I'm already finding a different class much better and more understandable. Your mileage will obviously vary.