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Introduction to Data Science in Python, Universidad de Míchigan

4.5
10,018 calificaciones
2,388 revisiones

Acerca de este Curso

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....

Principales revisiones

por AU

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!

por SI

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 .

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2,324 revisiones

por Changyu Gao

Apr 20, 2019

A quick introduction to Python and Data Science. The assignments are not as easy as you might think. To those who feel the assignment of Week 4 daunting, keep going -- data cleaning per se is not a difficult task yet a somewhat tedious one.

Thanks to the course team. I shall continue towards the following courses.

por Marcel Kornacker

Apr 19, 2019

It would be nice if Coursera could update the Python environment used for the exercises and assignments to something recent. The version they're using (0.19) is fairly old. Every single assignment that I had running against 0.24 had to be altered in some way to work for 0.19.

por Paolo G. Hilado

Apr 19, 2019

I am quite unsure of where to send a mail to express my gratitude for the scholarship. As such, I guess this may be a good venue for it. Thank you for the scholarship Coursera and University of Michigan.

por Kevin McHale

Apr 18, 2019

This course lacked written material to accompany the videos and the reference books are presented in a much different flow, so you are left to jump through books and posts to get through anything. Having the content packaged and delivered in succinct format is what I was looking for and this did not provide that.

por Marco Natale

Apr 18, 2019

Sometimes the question are clear due to the lack of clear definitions. The assignments could be done much faster if one did not have to research the entire forum. Moreover, the autograder can be really frustrating.

por Shanaka Jayatilake

Apr 18, 2019

this goes through the basics once again. a very good course to brushup the forgotten python scripts on data handling and cleaning...

por sbabureddy

Apr 18, 2019

The course is based on getting hands on experience of pandas package and some hypothesis testing. be sure to learn basics of pandas and hypothesis testing before enrolling the course.

por Ankita Gulati

Apr 17, 2019

Really simple and easy to follow and learn :)

por Рычков Артем Владимирович

Apr 17, 2019

Последнее задание, требует подгонки данных? Очень странно..

por Ian McCallum

Apr 17, 2019

Really excellent lecture materials. Programming assignments are challenging, but have too many quirky aspects, and require time to debug (without additional learning). Would highly recommend