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Learner Reviews & Feedback for Python for Data Analysis: Pandas & NumPy by Coursera Project Network

22 ratings
6 reviews

About the Course

In this hands-on project, we will understand the fundamentals of data analysis in Python and we will leverage the power of two important python libraries known as Numpy and pandas. NumPy and Pandas are two of the most widely used python libraries in data science. They offer high-performance, easy to use structures and data analysis tools. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....
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1 - 6 of 6 Reviews for Python for Data Analysis: Pandas & NumPy

By Nicholas S

Feb 22, 2021

One of the best projects I've done on Coursera. A MUST COMPLETE for anyone getting started with python! If you did this project three times over a few days you would have enough skills to start working on your own datasets.

By Samantha M

Jun 10, 2021

Good Project, I like the inclusion of the tasks hat allowed us to try out the things we learned. The only thing I would change is for the instructor to have gone more into the reason behind the fucntions used as well as the syntax. Good Project

By Mario C d A

May 23, 2021

Great to start learning. Great price/quality!

By Marc L

Apr 28, 2021

Great introduction!


Apr 14, 2021

very nice

By Evgeny K

Jun 9, 2021

Sorry. I have really tried to do my best to go through the project, since I appreciate the efforts of the instructor. He really tries to do a good job introducing a complicated topic in as simple fashion as possible. But... I have managed to finish just 3 steps of... how many? 12? Why so? Stay tuned guys (c) At step 1, I have noticed that the instructor does not follow the PEP8 guidelines in the code formatting. Ok, we'll live with this (even though it is stated that basic Python knowledge is required for the project. and PEP8 is among the first topics to be introduced...) I am not an expert in Python, just trying it as hobby, but even I see that the spacing in the code is ugly. In step 2 (mini-challenge) - the task says to generate the random numbers starting at 0, yet the answer given by the instructor puts 1 instead of 0. Well, the idea is still understandable, let us go on and excuse this glitch (this is not a typo, since it is also being said). By the way, "the basic knowledge of Python is required" - why not show here how to treat incorrect/erroneous user input? Would be just elegant, in my view. Then, in step 3 the instructor uses "sum" as a variable name. What the hell is this? Even the IDE showed in color that something strange was going on... By the way, the sum function should have been used just a few lines later (but it was not used - see the next item) - I am excited to see how surprised the instructor would be by the traceback to appear. Finally, in mini challenge 3 the "distance between two vectors" is calculated as the square root of element-wise sum of the vectors squared. Uffffff... Just before this task the instructor has encouraged us to go google what is the distance. I would love to see the definition which he has finally used for the 'official solution'. Basically this means that a distance between two vectors is a vector (???), and if the vectors are equal, the distance in nonzero (???). Sorry again, but I have had to stop at this point. At the end, this guided project is paid for - do I pay for killing my brain? Ah, and by the way, having passed 3 steps of 12 with the instructor, I have managed to answer the final quiz questions using a single attempt and about 3 minutes. Nope, I am not a pro - just yesterday I installed pandas and numpy on my PC. So, even the final quiz is so poorly planned that it required nothing from the guided project to cope with it. Once again, thank you for the attempt, but so far I would grade it with negative mark if it is possible. Hope this can be corrected - or otherwise I personally find this project unacceptable, and Coursera just loses its face by allowing it in without proper testing.