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Introduction to Data Science in Python, University of Michigan

4.5
8,744 ratings
2,176 reviews

About this Course

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....

Top reviews

By 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 .

By 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!

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2,112 Reviews

By Himansu Acharjya

Jan 16, 2019

The course is okay for beginners as it is having only few lecturers for basics. Coursera experience was good. Overall i am satisfied with the course.

By Lucas Newkirk

Jan 16, 2019

A few tricky homework assignments but I really enjoyed this course! I learned many new things.

By Lee Adcock

Jan 15, 2019

Class was good, and the information was presented in a way that was straightforward to understand and apply. I wish the exercise autograder provided more feedback. Sometimes the lack of actionable information made it difficult to solve problems.

By Onur Erinc

Jan 15, 2019

1)Auto grading for assignments worked on and off (mostly off). I spent far more time for the auto grading than the time I spent for actually doing the assignments and learning stuff. I considered quitting after the first week and had to really force myself to go on.

2) This course requires Python experience. This should be made more clear in the course description. I struggled a lot because I lacked Python experience.

3) The instructors have pacing issues - especially the teaching assistant. They rush the important points.

4) I think the difficulty level of the quizes and assignments is not encouraging learning. I considered quitting after the first week. I'd have easier and more motivating earlier quizes/assignments; then build up on them.

By Carl Wilburn

Jan 15, 2019

I like the use of the Jupyter notebook. Don't have to wait for grades.

By Temuulen

Jan 14, 2019

Good. Looking forward to learn more!

By Nazeer Basha shaik

Jan 14, 2019

I like the course very much, it will be useful for career prospective. I have taken courses in different sites, but this is especially to good in practice , assignments and grading.

By Harold Nikoue

Jan 14, 2019

This course has an in-depth exposure to pandas, and how to manipulate dataframes. I found it quite challenging and rewarding, as it improved my knowledge of series, dataframes and data manipulations in Python.

By Dhananjai Sharma

Jan 13, 2019

Excellent course and to the point explanation. Although i believe video Lectures can be more fun. hank you for the course.

By Neel Gotecha

Jan 12, 2019

Excellent Course curriculum