Chevron Left
Back to Introduction to Data Science in Python

Learner Reviews & Feedback for Introduction to Data Science in Python by University of Michigan

4.5
stars
26,999 ratings

About the 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

CB

Invalid date

The assessments, quizzes, and course coverage are quite good. The main points are covered, although it does not cover everything. Additionally, it provides opportunities to learn and conduct research.

PB

Invalid date

It is a great course to get started in the field of data science. It just require basic knowledge of python. This course teaches you basics of numpy and pandas and how to apply them in data science

Filter by:

5051 - 5075 of 5,941 Reviews for Introduction to Data Science in Python

By Prateek G

•

Apr 28, 2020

liked it

By Xuanan S

•

Dec 26, 2019

a

b

i

t

h

a

r

d

By Avi R

•

May 19, 2019

Awesome!

By Lionel_Guo

•

Mar 8, 2019

too hard

By Danish A

•

May 3, 2017

good one

By Hritvik D

•

Aug 7, 2020

awesome

By Nirman T

•

Aug 1, 2020

pogger!

By CHARCHIL 1

•

Jun 5, 2020

Helpful

By Vincent V

•

May 22, 2018

great !

By John P

•

Feb 25, 2018

Thanks

By Moe K O

•

Sep 25, 2020

Good.

By Jaisal S

•

Aug 21, 2020

Great

By Jogeswar S

•

Sep 13, 2024

good

By LINGAM N B

•

Apr 28, 2023

good

By Dev S

•

May 5, 2022

nice

By Vansh G

•

Apr 24, 2022

good

By Lucky K

•

Mar 28, 2022

Nice

By GOUTAM K

•

Aug 26, 2021

good

By SHUBHAM S C

•

Sep 4, 2020

nice

By sidharth k 0

•

Aug 24, 2020

good

By yogesh d

•

Jul 31, 2020

good

By Parth G

•

Jul 9, 2020

Good

By Hemaraj D

•

Jun 28, 2020

Good

By DIVYA A

•

Jun 15, 2020

BEST

By UMANG B

•

Jun 13, 2020

good