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

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.

this course was perfect for me, I learned alot from it.

I want to thank Jahnavi Chowdary quck reply and you helping me through out, you also deserve five stars

E​xcellent course and wonderful support from TAs. Appreciate the support.

Comprehensive review of how to uploade csv and xls files in jupyter notebook and processing with python and pandas. Then why 4 out of 5 stars? Because the questions in the assignments are not always really clear. But here again the upside: the supporting tutors are very responsive !

Great course for the beginners, would like to thank faculty and staff for making a great course, and the discussion forms were really helpful, Thanks to TAs for reverting back to all the questions.

This is a good course! I hope University of Pennsylvania will offer the more advanced course so I can enroll, too! Kudos to the instruction and to the staff.

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.

The course is very short. I expected more . Out of all the courses I have taken in coursera, this looked weak. The questions and instructions are ambiguous, could be more professional.

The lecture delivery is very good.

This course is way to skinny on the lecture-side of things and way too heavy on the homework-side.

I would not recommend it for people older than 18

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.

This course covers many areas of data analysis using the Python language. It is an excellent introduction to the world of data analysis, and a great furthering of development from the Intro to Python course that precedes it. I found it to be quite interesting and engaging, and it sparked a great deal of interest in data analysis in me, which previously was something that I didn't think I'd have much interest in. I am excited about the new level of knowledge and understanding of python I have attained, and also looking forward to learning more about python and data analysis.

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.

Overall, very well-crafted. Content is presented accessibly, with special attention put toward aggregating and plotting data. This class requires a bit more outside exploration in terms of understanding functions than Penn's Introductory Python course. The videos and discussion forums continue to be very helpful in developing solutions for some of the more challenging problems in the homework sets.

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.

Thank you for organizing this. I had best experience but I think i need further more exercises before the assignment begin, because i actually cant tell what the Qs wants. In Notes is too general.... i really there should be more scenarios and examples. but overall, great course. thanks

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.

The course material are very good but the instructor not teaching at all, you have to do all the things by yourself. But in general it gave so many knowledgeable information about using python for data analysis.

G​ood course, it gives you the basic info to pandas, numpy and matplotlib. It teaches you how to obtain dataframes, join, filter, group, summarize and visualize data. Short course but really worth it.

Understandable for beginners. But some questions in the tests are not clear. Even I get the same results, the answers are still not be passed.

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

Amazing course, got a pretty good idea in using python for data analysis and visualization.

Course aim towards histograms and scatter plots ensures dataframe syntax learning.

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

A great course to learn data analysis and visualization using Python