Introduction to Data Science in Python

This course will introduce the learner to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions. The course will also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis. The course will end with a statistics primer, showing how various statistical measures can be applied to pandas DataFrames. By the end of the 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.

OpenCourser is compensated by Coursera. Learn more.

From Coursera
Institution University of Michigan
Instructor Christopher Brooks
Price Free (with limitations) or $79 for a Verified Certificate
Language English (English)
Subjects Computer Science Data Science Data Analysis Software Development
4.00 based on 1 review

Like this course?

Save it for later.

This course teaches valuable skills


Annual Salary

Estimated earnings for individuals who use skills taught in this course. Figure based on US average salary and career skills data.

Write a review

Reviews for this course


Hal ET (Guest) says:

There's a lot of great content packed into this course. The information learned is useful and it really brought my data science game up another level. Unfortunately, one big gripe I had with this course are the assignments. They take a very long time to complete and the autograder rejects answers without giving much detail, so you spend a couple of hours tearing your hair out wondering what went wrong. Hopefully they can make assignments + grader better in the future.

What learners are saying BETA

university of michigan

...I'm not going to waste any more money on University of Michigan courses.

Kudos to Coursera and University of Michigan!Very informative introduction to Data Science using Python…

The University of Michigan does not disappoint and neither does the delightful instructor Christopher Brooks.

Thanks Coursera and University of Michigan.Autograder is hard to understand and has no feedback… was a lot of time spent with the grader…

easy to follow

Instructor does a great job of explaining the content with easy to follow examples.

Once I found that it was easy to follow along with the instructor.…

highly recommend this

I highly recommend this course to anyone serious about python and data manipulation.

too much time

This was taking too much time.TThe discussion forums are not giving clear hints…

for data science

...anyway I like this course .After having taken several Data Science…

You can find this course in these lists: