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

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23,422 Bewertungen
5,260 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
9. Mai 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
15. März 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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4501 - 4525 von 5,183 Bewertungen für Introduction to Data Science in Python

von An D

6. Juni 2018

The material felt very brief. Felt like this was suppose to be a refresher course. The lecture videos are not very helpful in its delivery. I wished there were more visual aids to help me understand the lectures more. Most of the time, it's just the lecturer sitting there talking and some quick screens of the Jupyter codes. I walked away with a brief overall idea of the material instead of an in-depth understanding of the concept. The assignments were challenging and I felt like they were very helpful. Expect to spend a LOT of time researching for the assignments.

von MARIA F V M

28. Juni 2020

This course was challenging taking into account that I don't have a lot of experience in phyton. I'm not going to lie, i would have prefer that the videos and the lectures give us more tools to solve the challenging assigments. I have to confess, I spent a lot of hours solving these assigmments, firstly, they are not easy and secondly, the auto-grader doesn't give you a real feedback on which you can work to fix the code. The way I see things, the autograder needs to improve and the content of the course will be better if it is more related with the assigmments.

von Andrew I

24. Feb. 2020

I learned a lot through this course, in particular searching the docs and skimming stackoverflow. It was very helpful. I do hope though, that the grader and materials will be updated in the future.

It caused me annoyance to battle with grader. It was not grading properly what in my offline jupyther-notebook runs just fine. I hope that this part of UX, or better - SX (student experience) will be mastered, so that students would concentrate on learning and not on trying to submit the assignment to the obsolete grader. Please, do solve this problem. It matters.

von Rakesh S

7. Okt. 2018

Course material is good esp. the assignments force you to learn a lot more. However, the instruction is not comprehensive. A few assignments were also ambiguous. The support forum is quite good but it would have been much better 1) if instructors would cover key topics a bit more in detail, 2) Easy to find auto grader scripts so one can understand the error or provide a better feedback mechanism from autograder. I had a spelling error in the answer and it took me 4 hours to correct it. Once I had the autograder code, the bug was very easy to catch.

von Thomas L

7. Jan. 2018

I am somewhat satisfied as I did learn some python skills. I paid for this course because I wanted an efficient way to learn python programming. The far cheaper alternative is to get a python book and work through it yourself. I thought this would be a more time efficient alternative to self study. It is somewhat more time efficient. The questions in the assignments are not clear, this results in you spending a lot of time not learning python but figuring out the semantics of the question. There should be a knowledge check at the end of each week.

von Joe P

17. Jan. 2017

I found this course useful since I had no previous experience of Pandas or the statistical features of Python. I have programming experience and feel I would have found it quite a challenge otherwise, but not prohibitively so. Chris is great at explaining things in an accessible manner, and I'm very much looking forward to going into more detail in the rest of the specialisation. I would have enjoyed a little more focus on statistics etc and a little less on the mechanics of the library, but understand why it had to be approached this way.

von Will D

13. Okt. 2020

Great course material. Grading issues due to Python versions was a pain. The discussion forum may have been more helpful with smaller groups (18k posts in a given week is overwhelming!) Nice to have access to the larger group brain, but I bet having chats with cohorts of 10-100 people would make the course feel more intimate and engaging. Also, the pace of lectures felt like the prof was reading text off a screen rather than a "real" lecture with natural pauses, which made it difficult to follow along with code as the prof was speaking.

von Nadine R

19. Apr. 2018

This is course is classified as intermediate and a 10h commitment per week. For me this was an under estimation. It took me much longer. The problem with the course for me was, that the skills required for the assignments were not taught during the lectures and the assignments are poorly described. I ended up googling for hours. The links in the forums are very helpful, but I usually prefer to solve assignments on my own, which was not not possible for me in this course. I did learn a lot, but this was very unefficient.

von Stacey C R

10. Feb. 2018

Honestly, my opinion is that the material is "a little too difficult a little too early" .. not because an experienced programmers can't handle it, but because the urgency of getting the final assignment done forces a reversion back to more traditional programming techniques rather than instilling "Pandas like" programming techniques ... if anything .. "instructor solutions" should be given at the end of the course so we can go back and see "how we could have done it more elegantly" in the areas were are interested in.

von Keir M

10. Juni 2017

Not a bad course but would like to see more teaching of best practice solutions to some of the test and assignment questions. As most of the assignments require a lot of self-learning it would be nice to discover if our solutions are optimal or not. As it stands you can get a perfect score by writing for loops or other inefficient solution when there are quite possibly built-in pandas functions which could achieve the same thing more efficiently. Would like to learn more about pandas and best-practice techniques.

von Mike L

10. Juli 2019

The course materials is very practical. The lectures are very clear and self-contained. The only reason I gave 3 stars is that the homework takes too much time. I spent a lot of time digging into online forums to find out the nuts and bolts to finish the projects. Fortunately the teaching staffs are very helpful. The time spent for homework is too much for my preference. Maybe this is the way to learn this type of information. I don't know. Having said that, the materials and lecture qualities are great.

von Polina B

14. Jan. 2017

I liked that the course was very assignment-oriented. It had a good structure and interesting additional readings. However, for people who are not familiar with pandas library it may be very challenging to pass assignments. This minimal guidance, I believe, results not in a better understanding, but in confused students writing bad code and spending hours not understanding online documentation. Overall, I really liked the idea and content of the course, but not how instructors approached the self-learning part.

von Michael C

23. Nov. 2016

I have two general comments:

The first comment is . . . there was too wide a gap between the lecture content and the assignments. The second comment I have is . . . I spent too much time trying to figure out what the autograder wanted and not enough time learning Data Science with Python. I can only imagine the work that it takes to develop and launch a course like this. In all, I'm very excited to be part of this program. My comments are critical but hopefully helpful and all your work is appreciated.

von William J

26. Jan. 2020

Course content was generally good although sometimes the lecturer brushes over topics that could do with more explanation. He may explain 10 things you can do in quick succession making it hard to remember all of the points. Exercises were good but there is a big jump on week 3 and 4 and relies on students to spend time themselves searching the web for solutions to the problems. Whilst it is good to be independent, asking for things that haven't been taught in the class can be hard for some.

von Jon-pierre H

26. Sep. 2018

This course teaches some useful techniques, but suffers greatly in it's ability to teach you those things. The hw's do not contain enough information, and submission errors are very vague in terms of explaining what is actually wrong. During lectures, too much time is spent on the presenters face. They have presentation slides and code examples that do not get enough video time. It is not at all useful to talk about techniques without giving any textual info about it. It's not easy to follow

von Gajesh B

8. Jan. 2017

It was a good course where i learned about new and great tools and techniques. I learned how to approach the data science problems using Pandas and Numpy. This would not serve as a great course for into to data science. Background with Database Management and Python really helps. Overall i learn about new and great tools and would definitely require Documentation while using the skills i learnt in this course. Overall Great Job by Professor Brooks. Would love to take more courses by him.

von Charles W

26. Feb. 2017

I enjoyed and found all of the lectures helpful, but lack of feedback after submitting assignments was a real problem, especially for the last assignment. A simple response of "this was answered incorrectly, points not awarded" isn't very constructive and was often frustrating. Bugs in being able to submit the assignment were also frustrating. I spent a good amount of time trying to fix my code, thinking it was incorrect, when in actuality the online submission was just not working.

von Tarun Y

6. Mai 2020

Course was good and i have learned and starting to refining my skills because of this course.

We have to do lot of practice and net browser to work on the assignment and only think that lacks in this course is the study material in the form of video i think,if the content of the video increased then this will be the perfect course plus there should be two assignment one related to what you have studied during video content and the programming assignment which test your skill test.

von fabien M

7. Juli 2020

I have mixed feelings.

1) the course is very interesting. It is an applied course, there is a lot to learn.

2) But very hard too. There are so many things, that you may have difficulties to memorize quickly through practices. Then, you end up roaming on stack overflow and pandas documentation because you just can memorize enough to process and have to rely heavily on the documentation.

If you are interested to dig into the python, this is very interesting (but quite hard)

von Alexandre M

10. Jan. 2019

This class definitely makes you learn, but not as much from the lectures and course materials themselves, as from the discussion forums (shout out to teaching staff and mentors for their great help) and online tools like Stack Overflow.

I understand that this is also a technique to make us more independent, but it seems like the professor just wanted to skim over this part in order to concentrate on some future / more advanced class that is more interesting to him.

von Thomas L

22. Jan. 2017

Although I learned a lot in this course, I found the lectures and assignments to be much too different from each other. I would like to see assignments where you must practice what is learned in the lecture. For myself, I feel I learned 1 set of concepts from the lectures and another set from the assignments by spending time on stack overflow and the pandas documentation. Both are good but the lectures and assignments did not "flow" together as I would have liked.

von Aram H

13. Nov. 2016

The course is very interesting. The Jupiter notebook is very useful.

I don't like that many examples are very US-specific. Some important terms may not be clear for people who live outside USA.

Update: I'm lowering my grade from 4 stars to 3 stars because of very confusing assignments. Often it's not clear the requirement of the task. It takes very long to understand. Also some assignments require methods and functions that were not covered in video lectures.

von Saurav K

13. Aug. 2020

course content is good,but the instructor tries to explain everything just by saying it. does not demonstrates it every time and does not dive deep into the concept,so that the learner may get more interested. and if you are stuck at any assignment question then it might happen that you won't get the answer even after seeing the videos. assignment contains some questions based on concept which are not discussed,so you have to figure them out yourselves.

von Pedro G d B R

2. Apr. 2020

Excellent lectures and explanatiom about Pandas features. But the Assignments could have more conection with the lectures of the correpondent week. Also the instructions to code the assignments are often bad written or lacking information, causing erroneus comprehension about what are being asked. These kind of problem cause a lot of misconceptions abou the task and cost a lot of time from the student just to really understand the assignment objective.

von Pascal V

3. Feb. 2020

The assignment of week 4 is wrongly explained in the jupyter notebook. It says that the price_ration is equal to quarter before recession divided by quarter bottom recession. When you do so you will never get a validated result. The only result validated is recession_bottom minus recession_start!

Giving assigments should include expected solution. Now you upload your file several times in order to figure out you are using the wrong formula.