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
26,908 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

YH

Sep 28, 2021

This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.

PK

May 9, 2020

The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans

Filter by:

4651 - 4675 of 5,918 Reviews for Introduction to Data Science in Python

By Veeresh I

•

Mar 31, 2020

Good course to learn the basic concepts to start with Data Science

By Sean L

•

Oct 18, 2019

Learned a lot, but mostly by self-learning when doing assignments.

By Yufei H

•

May 14, 2019

Chapter 2 and 3 are good for me, the rest chapters are too simple.

By Ashley R

•

Nov 20, 2018

some questions were vague but i guess thats part of the real world

By Aliyu A

•

Sep 11, 2017

A very good course. recommended for a intermediate data scientists

By aaron_lang

•

Jul 27, 2017

Overall, the course is pretty good in terms of practice questions.

By Elana A

•

Mar 22, 2017

Great course and valuable information, but frustrating autograder.

By Maria C P Z

•

May 30, 2023

The assigments where really hard according to the topics thought.

By soham v s

•

Nov 3, 2021

it is good course for beginers , jupiter notebook is also a good.

By RUBY P

•

Aug 2, 2021

It is a good course to attend and start your data science journey

By Akanksha M

•

Jun 24, 2021

it was a nice course helped me understand more about data science

By Sangram K S

•

Jul 13, 2020

It was good. The session can be more interactive and interesting.

By Gian C T G

•

Jun 25, 2020

Need more excersices examples, some homeworks are quite difficult

By Subha M

•

May 31, 2020

The course was good. But few points were not that up to the mark.

By Anil K C

•

May 6, 2020

Good assignments to get you to learn the Pandas library in python

By Sadia a S

•

Mar 21, 2020

It is a helpful course for working with python for data analysis.

By Roy Y

•

Jul 17, 2019

A great introduction. But assignment grading a little bit tricky.

By hadeer a

•

Jul 15, 2018

The course was helpful, but the assignments weren't clear at all.

By Ahmed E

•

Jan 27, 2018

It is a challenging course specially for beginners and assignment

By Dhruba s R C

•

Aug 17, 2017

A very detailed course. A must do for Data Science enthusiasts...

By N181133 P L S

•

Jul 18, 2022

Really this course is amazing and lots of stuff given.Thank you

By Partha S

•

Jan 23, 2021

Its not an easy course and requires a lot of focus and attention

By MINGYANG Z

•

Jul 15, 2020

The instruction of the homework is sometimes hard to understand.

By Julian L

•

Jun 16, 2020

It would be much better if all the videos had Spanish subtitles.

By sourav g

•

May 21, 2020

If you could also provide written material, that would be great.