Dec 10, 2017
Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!
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 .
автор: Pieter J S M•
Jun 09, 2019
This course was very much helpful to understand Pandas as a Data Science tool. I started to understand the way you need to think, whenever you use Pandas. Especially the assignments were very good. A very small exception is the assignment in week 3, in which you have to clean your data frame. That was a bit too extensive, I think. I rather used that time and efforts to learn to apply more statistical methods.
But overall: this course exceeded my expectation and I am very much helped by it!
автор: Ajit S•
May 28, 2017
This is a very helpful course. The main advantage is that you will learn a lot of new ways to do operations over data. And this is an intermediary course that assumes that you already know about statistics, mathematics behind data. From my experience I want to tell that if you are taking this course don't just rely on the video this course provide (however videos gives you full context on the work that has to be done), you have to do your own research and reading from external sources too.
автор: Bala G•
Nov 21, 2016
This course was excellent...I first found the course odd since the instructor went through the material quite quickly in the lectures. It took me a while to figure out that the material was available as a course download. Once I found that it was easy to follow along with the instructor...need two monitors ideally for this to work. If you cannot step through the Jupyter notebook as the instructor goes through the material, you will be lost...and you will not get the most out of the class.
Feb 16, 2019
Awesome course for anyone looking to venture into the field of Data Science. The instructor puts forth various concepts lucidly and concisely without any irrelevant extraneous details. Beware though, if you are pursuing this for the sake of learning statistics, you might be disapppointed. The instructor adopts more of a tool-based approach teaching you pandas to solve your problems the way you want to. That said, kudos to Coursera and U Michigan for putting this course together.
автор: Kevin B•
Jun 16, 2019
Great course overall. I feel like the final output for run_ttest is incorrect though. There are two regions that belong in the university town buckets, but are missed due to capitalization differences, Illinois -DeKalb and Florida-DeLand. I made the region lowercase before merging and got (False, 0.011132653194002319, 'university town') as the output. When my grade came back as 5/10 I knew if I removed the cast to lowercase it would be correct. Thank you for everything!
автор: Derrick G•
Aug 13, 2019
There are plenty of how-to videos and tutorials on YouTube to get caught up on the basics, and there are lots of Data Science classes on coursera and other platforms that go deep into theory and stats. This is the first Data Science in Python class that I have found to strike a balance of practical and theoretical at an intro level.
The video and audio quality is great as well. Start here. Then move on to the deeper and more specific courses on stats or machine learning.
автор: Paresh D•
Jun 11, 2019
Fantastic course.I have learned a lot.I really enjoyed playing with various data frames in the assignment.Discussion Forums were very useful.Special Thanx to Yusuf,who used to help me in clearing my doubts.The only thing with which I am dissatisfied is the teaching instructor.He has enough knowledge and is a genius,but his teaching style is mundane.I wish this course was taught by Dr.Chuck.I really like the way Dr.Chuck taught Python for Everybody specialization
автор: Abdul S•
Aug 21, 2017
One of the best courses I've attended in the Coursera. The programming assignments were tough. But I think in some assignments instructions were not clear or were not available at single place. Ideally all the instructions/hints etc should be placed inside the notebook for assignments.
Overall the course challenged my learning. And I needed to do lots of googling to look into stackoverflow, pandas documentation etc to reach the correct answers. Awesome course.
автор: Shreyashi G•
Feb 12, 2019
This course is a high level and precise introduction to the python programming skills necessary for any data analysis exercise. It is adequately paced which is great for anyone who has some prior knowledge of python. The assignments are particularly challenging which I thoroughly enjoyed. The lectures would effectively introduce a concept and the assignment to follow would test the understanding thoroughly - a structure which in my opinion worked great!
автор: Zhao J•
Feb 25, 2017
It's a great course! The assignment is amazing! It takes me several hours or even one or two days to finish it. I have to say the assignment is really valuable. Professor Brook is also great and the video is greatly filmed. It's worth taking if you have already learned some of python and want to know more about python in data analysis. I have already learned the book Learn Python the Hard Way and played with python for a while before I take this course.
автор: Gustavo W•
Nov 19, 2016
Really good course BUT be prepared for a very fast pace of the lectures. I'd placed in the "advance beginner" or "intermediate low" level, therefore, you need to have previous knowledge of Python. As in College, lectures and assignments are somewhat related, but you will spend some additional time investigating by yourself to get the appropriate responses. Again, just like College where Lectures are level 2-3 but assignments are level 7-8 (out of 10).
автор: Chirag R•
Jun 27, 2019
The course was pretty exhaustive and I felt like I learnt everything that this course intended to teach me. The assignments were pretty tough, given that I had no experience of Python before this, but that's down to me for not taking the "Python for Everyone" course, as recommended by our professor. A few more interactive and intermediate level problems could go a long way in making the course takers better skilled and equipped with Python.
автор: Joshua T C X•
Jun 11, 2019
This course is NOT for the those with zero experience in programming as it assumes some familiarity with concepts like object attributes, functions etc and requires you to spend some time reading up python/pandas documentation on your own. While I think that the professor could use simpler English to communicate more complicated concepts, overall it is a good course with good assignments that cover the key concepts required in data science.
автор: Zhenwei Z•
Feb 09, 2019
It's a great Course, covers a lot of stuff. It seems that the content allocation between lectures and homework is not well balanced. The lectures are quite short and fast, and the homework are heavy.
It would be great if the lectures can cover more details, especially the techniques that are used in homework. Also the if the homework can provide more instructions and descriptions and maybe some self-checking hints, it would be very helpful.
автор: Eunjae J•
Apr 23, 2017
Much harder than I thought. Very in-depth introductory learning of python.
Preferably better if you allow scripting in .py because notebook is rather heavy and hard to
debug while assignments..
Hope you cover a bit more in detail with language structure, as well as give hints for solving assignments, since many parts were pretty above course level.
I would say the assignments were hard even for an R practitioner learning python like myself.
автор: Mukesh K•
Nov 05, 2019
This is an excellent for those who want to learn python pandas. The course content is really good. The assignments are really helpful and they truly covers what is taught in the lectures. Had fun going through the video lectures and solving assignment. Though, in the last assignment 4, if a little bit of data description was added, it would have been good. Thanks for making the course and helping providing the content through Coursera.
Feb 05, 2017
This is very helpful course, my skills horned after undergoing through this sessions. My expertise and style of using python for data analysis changed. Articles and group discussions about P-hacking made me to realize the pitfalls, I may enter once I get addicted to proving my hypothesis correct. I got an idea, what better I can understand; when data speaks.
I am waiting for next module of this course. Please start it as possible.
автор: Rounak P•
Aug 13, 2018
This was a nice course even though I knew most of the stuff before hand lectures still had something new in store for me. However, I found the programming assignments challenging because even though the submission checked our solution if I got it wrong it was extremely difficult to pin down the mistake and the instructions itself couldn't through a light on my short-comings.
So I learned the hard way. It was a great experience.
автор: Walter O•
Dec 05, 2016
Overall I thought the level of the course was good. The programming assignments were complex and long enough that you had a good opportunity to re-inforce topics covered in the course. I already had a good bit of pandas experience so the course was helpful to re-inforce things I was already familiar with but hadn't been forced to try out. I think if you don't already have pandas experience the assignments might be tough.
Jan 19, 2018
Immersive and challenging introduction to python/scipy libraries in just one month.
The thing I like the most:
Assignments make you think twice, they are challenging enough to make you investigate further on your own about a probable solution
What I disagree:
Time marked for each activity in course (specially programming assignmenent resolution) is non realistic, actually takes much more than 1..5 hrs to solve the assignment
Oct 25, 2018
Challenging course. Worth the time and effort I put in. Instructor and the material is excellent.
One suggested improvement could be the guidance for assignments could be tagged better. It takes a lot of searching before one can find the right material. Both Sophie Greene and Yusuf Ertas provide excellent support. But if the guidance or tips can be made easily disoverable, it would save a lot of time.
автор: Paloma M•
Oct 24, 2017
Very nice introduction to the pandas library, with special focus on practical exercises. It might be a bit difficult if you have little experience with python, but it is not impossible. In my case, I needed more time than expected to finish my assigments because of my lack of experience with the language. Still, the forums are usually very active and the Teaching Staff is very helpful, so I'm glad I took this course.
автор: Alan J•
Nov 18, 2016
Really awesome course. It is a kind of do it yourself course.The assignments are tough to crack. I think a little bit of programming experience is neccessary. The lectures themselves only give the basic knowledge. The assignments make you do research on the relevant topics. The autograder is pretty bad, it gives false negatives a lot of times, but that i believe is Coursera's drawback and they are working on it.
автор: Beatriz I•
Jun 16, 2018
This is a really good course if you are a beginner and want to learn Python. Assignments are not easy, but not impossible, and that is the best way to learn. After passing the course now I feel I need to stop and go over everything again to be able to make my code Pandorable, because right now I know it is not, it works, and I understand it, but I know it can be better. Thanks to the team for this great course!
автор: Georgi S•
Jun 23, 2019
Nice introduction to pandas. Lectures are short and give just a quick overview of the different sections while the main learning comes from the assignments which require more individual effort and self-learning. Material requires some basic prior knowledge of Python and/or experience in another programming language. Would definitely recommend this course to people interested in data analytics with Python.