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Learner Reviews & Feedback for Introduction to Data Science in Python by University of Michigan

4.5
stars
23,655 ratings
5,311 reviews

About the Course

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 reviews

PK
May 9, 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 15, 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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5101 - 5125 of 5,235 Reviews for Introduction to Data Science in Python

By Shivani P

Jul 9, 2019

The lectures were not enough for the assignments provided

By Alejandro P 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 Harshith S

May 23, 2019

Dint teach anything used in the assignments properly

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 Alexander K

Apr 14, 2020

Nothing new. I recalled what I knew

By Stefano M

May 27, 2019

The lessons were too fast and dense

By Daniele

Mar 1, 2018

Theory is not related to exercises

By 김민섭

Apr 27, 2020

Good materials, annoying grading.

By Nachiketa N

Aug 21, 2020

Should have been more detailed

By LUKAS E G

Sep 11, 2020

Better reading a pandas book.

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.

By Victor U

Apr 4, 2017

The course is a great course in terms of the knowledge and experience of the instructor and the helpfulness of the staff. I gave it 2 stars for two reasons.

1) The videos are deceptively short. In MOOC instructional design, you normally design short videos because the attention span of an online learner is tends to be much shorter than an in-person university student. However, in this course, even though the video is short, it is really 5-10 times longer because they speed over the equations and teaching so fast that you have to pause and replay and rewind and replay several times while trying it yourself. So the timings are not truly accurate. If you were actually teaching it in a classroom with actual students you would go much more slowly. In this case, I wish they were more honest with the times by actually typing the code in real time while teaching. I would have preferred a lecture to make it more digestible.

2) The hardest thing for me about the course was the fact that instead of practicing computational thinking within data science (decomposition, algorithmic thinking, etc.), I was really just searching on stack overflow for how to put it into python. It's poor instructional design to only teach somethings and expect students to complete assignments without giving them all the tools they will use in the assignment. It would be ok if it were an accidental mistake, but this seems to be purposeful. This happened not just in course assignments but sometimes even in mid-roll video-overlaid quizzes where the answer was something not explained or taught or shown. This was really strange to me and caused a huge amount of time to be spent searching online or trying mid-lecture problems to no avail. It cause all the timings of the course to be off (#1 caused the video timings to be severely off and #2 meant that the course assignment estimates were HUGELY miscalculated). Good instructional design would mean that the professor should show all the tools one could use to faithfully complete and achieve the assignment. For some reason that was avoided again and again in this course.

Great material though. I loved learning. I just wish it were better structured and supported and that I learned more about the work rather than just searching online for how to write something.

By zhou x

Nov 28, 2016

Well, first thing I am going to say this is not going to be looking good, however correct me if I got anything wrong or being unfair.

To be honest, I am very frustrated with this course! It is a very good topic that I am very interested and that's the reason I am enrolled , but the support and the structure of it is very disappointing!

Example like this(https://www.coursera.org/learn/python-data-analysis/discussions/weeks/3/threads/0kwIpLJDEeawPhIF4bjuNg), question is not even specified and waste me so much time looking for the requirement and post discussion board and wait hopefully somebody is going to reply!

Same for the ScimEn file , which again the file name was not specified in the question!

From last secession, assignment two have lots of confusing around what exactly the question is asking about and again lots of time being wasted just to figure out the question!

The support is poor as well, not like other course , I would usually get a answer within the same day , but this one is really when you are lucky! Plus the staff rarely response!

In short, I hope the staff of the course would see this. This is a good topic but the course are poorly designed with very limited support!I mean if you are truly love the topic , you should pass on the passion to your students and design the course that students not only learn the material in the course but also can know how to ask questions and find out the questions themselves ,but first like learning any skills students needs to ask lots of questions ! I am not going to mention that ,coz even the question in the course is full of error !!

Unless, the whole purpose is to make some money , then it make sense , however if it is that case , I am not going to enrol in this course any more.

By Lucian C

Apr 24, 2020

After having done quite a few other courses from UMICH (mostly taught by prof. Charles), I had high expectations from this one. I must sadly say I am extremely dissapointed.

1) The course itself doesn't teach anything. The videos basically say: "Here's pandas. It has functions. Good luck". If you want to learn what to do, you are encouraged and have to search it online, because such materials are not provided in the course.

In my opinion it cannot be called a course, if all it does it says "Hey, there exists this thing called Python and Pandas. If you want to learn about it, go do it somewhere else. You're welcome! "

A responsible course would provided well strucured materials for students to study. Videos showing a proff. reading off slides are not particularly useful.

2) Assignments are messy and it seems not much thought has been put into them. Whilst I do like the challenge itself, spending 3 hours figuring out why the autograder gave me no points is completely useless and frustrating: you get no feedback, no hints, no nothing. Eventually you may be able to find some hints on the forum, but seriously....those 3 hours could be way better spent on some actual materials, rather then trying to figure out a formatting issue.

I could go into more detail, but you get the idea. I was really excited about this specialization, but I will not continue with it. Again - I've nothing against a challenge - so a more difficult curricula - but I cannot work with a completely lack of curricula and structure , as well as materials.