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Learner Reviews & Feedback for Data Analysis Using Python by University of Pennsylvania

66 ratings
26 reviews

About the Course

This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization....

Top reviews

Apr 12, 2021

Excellent course. Assignments /home work explaination need to be rethought. Special thanks to Jahnavi for helping through out the course.

Apr 13, 2021

I can't really put it into words or appreciate enough how wonderful and valuable this course is.

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1 - 25 of 28 Reviews for Data Analysis Using Python

By Kanwar L G

Apr 13, 2021

Excellent course. Assignments /home work explaination need to be rethought. Special thanks to Jahnavi for helping through out the course.

By Ezekiel R

Jan 30, 2021

Units Tests in the assignements are a bit buggy but they do give scope to research. Would be nice if the questions then are to the point.

By Hüseyin C Ü

Feb 24, 2021

Video lectures were split() into short fragments which I enjoyed very much. Brandon, the professor of the class is very much involved with the audience and he is not monotonous. This is a huge plus! The only point of improvement that I would like to mention is; in some assignments the ask could be more clear. However, this comes with a hidden advantage, it gets you researching the Python libraries/documents, and learn about more advanced topics with trial and error. This is not a class to just watch the lectures, if you like to do self-research and looking for a foundational class to build upon, don't miss it. Make sure to install pyCharm and Jupyter in your local machine to test your code more efficiently (he walks your through how to do that during the class). All in all, this is a high-quality class that deserves five stars, especially recommended for finance professionals.

By Izhar A

Jul 27, 2021

One of the best courses I've ever taken! This course is an introduction to Data Analysis and Data Visualization using popular python libraries such as Numpy and Matplotlib. The course content is wisely crafted with sufficient in-depth knowledge and a lot of practice exercises on offer. I highly recommend this to everyone seeking a basic understanding of the aforementioned libraries and python programming in general.

By John L

Feb 10, 2021

The instructor, Brandon Krakowsky, is excellent. His instructions are clear and descriptive. He also seems to know when to repeat explanations or specific details. The technical support using Jupyter Notebook is very good. My only complaint is that the auto-grading sometimes doesn't consider that the order of completion may vary while the final results are effectively the same.

By Hxeny _ f

Apr 14, 2021

This course was very informative and challenging enough to keep my interest. Once I started I did not want to stop. This is my first set of courses in Python and I feel it gives a very good understanding of the language.

By Sepideh A

Apr 14, 2021

I can't really put it into words or appreciate enough how wonderful and valuable this course is.

By Gourish K

Mar 27, 2021

Good introductory course. Brandon Krakowsky explained all the concepts clearly.

By Marjorie H

Apr 15, 2021

A great course to learn data analysis and visualization using Python

By Joan O

May 4, 2021

this was very useful and well prepared course. Thanks a lot

By Alexander P

Feb 11, 2021

Practice makes perfect, and this course is truly practical

By Kagiso K D

Jul 22, 2021

Great content and stimulating assessments

By Masahisa W

Jun 29, 2021

C​rystal clear for begineers

By Wael K

Jul 24, 2021

well organized.

By J H

Jul 16, 2021

On one hand this is a really good course and the slides are excellent and enough to teach you all you will need to know. However, the assignments are not always clear about what you should do and you may find that having the right columns in the wrong order is enough to mark you wrong. This being said, if you look at the output from the errors it will give you an indication of exactly why the test failed and what the test was actually looking for.

By David T

Jun 17, 2021

It was a good class. The assignments are fairly straightforward and the videos are bite-sized so you don't have to sift through hours upon hours of video. As for improvement, I think it's more an issue with Coursera itself rather than the instructor or UPenn, but I sometimes feel like it's hard to know how much I've retained from the class.

By Luke H

May 24, 2021

I'd like for this to be a little more in-depth. I had fun with the data visualisations. However, probably more of manipulating the data would be good.

By Anne L

Mar 25, 2021

Very informative course. However lessons feel more like telling than teaching. The lecturer could go more in depth.

By Alejandro M

Feb 8, 2021

Videos touching same theme were too short (26 sec, 1 min, etc.) and disruptive. Wish there could be more practices.

By Akash K

Apr 13, 2021

course is overall good but face some problem in understanding of homework questions, proper explanation is needed

By Farshad S

Jul 30, 2021

it would be better if sections were covered more of panda and matplotlib and even seaborn

By Moturu N S

Jul 30, 2021

Very good introduction to data analysis using python

By Daniel P

Dec 17, 2020

Short but very informative course. I like it!

By Vivian H

Dec 31, 2020


By Aayushi J

May 6, 2021

Course was very good to learn pre-processing and visualization and also gives good practice. The questions in the homework exercises could be more clear as in what they are expecting as the output. The way it has been put out makes few exercises confusing for us to understand in order to solve them. Response by the teaching staff on the forum can be quicker, sometimes it's frustrating for the coder if they are stuck and we don't get response atleast in 12 hours. Right now it goes beyond 24 hours.