CB
Feb 6, 2023
The assessments, quizzes, and course coverage are quite good. The main points are covered, although it does not cover everything. Additionally, it provides opportunities to learn and conduct research.
HC
May 3, 2018
It's very useful specially for new learner because it only dives into the part of python that data science need. I strongly recommend to anyone even if you don't have experience in programming before.
By Alex A
•Dec 22, 2017
Good content but too fast pace and confusing assigments.
By Camilo E A P
•Aug 27, 2019
Jupyter notebook for assignments do not work properly.
By Sayali B
•Jun 20, 2018
The questions are very hard and not covered in training
By Deepalakshmi K
•May 23, 2019
Dint teach anything used in the assignments properly
By Chris H
•Mar 22, 2023
not practical - no student interaction. just videos
By Abdullah B
•Sep 10, 2022
Not enough resources to solve the assignment.
By Joao V O C d B
•Jul 27, 2020
The problem is the lack of practical exercises
By Christalin D
•Jun 21, 2020
It's asking for money to continue the course
By Hari S S
•Jul 30, 2020
A bit more motivation needed in this course
By W N
•Nov 27, 2016
Good material, let down by instructors.
By laxmi n r j
•Sep 3, 2017
Its too fast paced and less elaborated
By Heike M H
•Mar 10, 2022
Not suitable for beginners in Python
By Alexander K
•Apr 13, 2020
Nothing new. I recalled what I knew
By Stefano M
•May 27, 2019
The lessons were too fast and dense
By Daniele D
•Mar 1, 2018
Theory is not related to exercises
By 김민ì„
•Apr 27, 2020
Good materials, annoying grading.
By Nachiketa N
•Aug 21, 2020
Should have been more detailed
By LUKAS E G
•Sep 10, 2020
Better reading a pandas book.
By Yaron L
•May 25, 2021
NOT ENOUGH PRACTIOTION!!!!
By zhangzhongquan
•Nov 12, 2017
it's not very good
By V
•Sep 11, 2017
Not much of a use.
By ANKIT A
•Sep 2, 2020
Less interesting
By DHRUV S
•May 5, 2020
hard assignments
By Arjunsiva S
•May 9, 2020
Too fast paced
By Nathaniel R
•Jun 12, 2020
This course was a travesty. 1. The version of Pandas being taught is not the current version.... so good luck applying this anywhere OR searching for help. 2. The lecture material was wiffle bat level then the assignments were mack truck level 3. I am a professional developer, I know how to use stack overflow and pandas documentation to solve problems. I was looking for a fundamental grounding of the materials. 4. I do feel I came away with a basic understanding of using pandas and python, but that's because I spent about 100 hours looking up answers to every question on here. 5. The lecture is so superficial that you'd learn a python way to do something, then a pandas way to do the same thing, then another pandas way to do something, then that would be the starting block for the assignment that would use advanced concepts. As a result I know 9 ways to do something simple with no recommended best pattern or understanding of when to use one or the other--and they all kind of muddle together now, but then spent dozens of hours researching the actual answers to the questions. "This is the way I like to do xyz, because of this. There are 3 other ways you may see and I'll briefly show you them" would be great. 6. For how important it is, the distinction between methods that mutate data and methods that don't was pretty minimal. 7. The online exercise thing is worthless. It uses an old version of pandas AND there are certain code breaking idiosyncracies in the tool AND it considers a pandas INT wrong if it's looking for an INT but there's no requirement in the question and no discussion of how to transform these or if there's any reason to do so other than to make the autograder happy. Look in the forum, there's straight answers like "an upgrade broke this, so it is not expected to work" which is a bad experience if you spend a few hours trying to debug code before looking up the answer. IT shakes your faith in all the exercieses. 8. This may be a coursera thing, but I'm learning this for WORK, I need to be able to get stuff working on my local PC. I see the autograder makes things easier, but it's basically a similar but different API. I literally spent 1 hour converting my code so the online grader would run for every 2.5 hours of local coding I did. It's debilitating. 9. This is probably a coursera problem, but it's really difficult to find the question you asked in the forum. Since you can't get through most of this course without forum assistance, that hurts. 10. I feel like I got gas lighted. You cannot do this class without already knowing python. This is mentioned in one of the lectures after you've already signed up. He recommends the Python for Everybody course, but it is very unclear from the Course Description before you pay money. Here are quotes from it, tell me if you would expect this to teach you python: *"This course will introduce the learner to the basics of the python programming environment", *"including fundamental python programming techniques such as lambdas", *"SKILLS YOU WILL GAIN: Python Programming". Then the forum is peppered with answers that say "This is not a python programming class". So... SUMMARY: This was my first coursera experience, I was very much looking forward to it and it really shook my confidence in the site. I did learn how to work pandas, but would have done just as well with a list of problems and a google. The "16 hours to complete" took me over 2 weeks of full time work--roughly 100 hours--due to both this disconnect between the lecture and the assignments and to the difficulties transforming working local code in a modern version to a buggy online grading system working on an old version of python but with some patches that also render legacy forums only 80% useful as well. The lectures manage to be both superficial and confusing (because they take a superficial topic then jam 4 ways to do the same thing into 30 minutes). And despite the course description you do not learn an intro to python here, just to data science. I will be trying one more coursera course, basically because all the other reviews on here say this is an abnormally poorly run one, but if they're all like this I will return to pluralsight soon.