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
26,910 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

Feb 6, 2023

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.

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:

4226 - 4250 of 5,918 Reviews for Introduction to Data Science in Python

By Harsh G

•

Jun 3, 2020

Last Assignment which is Hypothesis Testing could be more elaborated and more reading material could be provided there for better understanding.

By Jatin R

•

May 16, 2020

The course was Great. You got to learn so many things. The assignment is so challenging it will definitely increase your knowledge for the same.

By Víctor A M G

•

Jan 27, 2020

Very difficult course, very challenging in terms of the validation tool for the homework, but undoubtly I learned very much from it. Thank you !

By Amol V B

•

Jan 7, 2019

I would like to refer to all beginnner.. coursera is the best content to learn data science and Machine learning..

Amol Billale

AI & ML Researcher

By Saivijaay V K

•

Oct 12, 2022

The assignments were amazing to get the practical values but more statistical content is need to get the idea of chi-square, anova tests etc.,

By augustus e

•

May 11, 2020

Great course. I'll recommend changes for the assignments. Some were really vague, especially with the workings. It made them quite challenging.

By Wynona R N

•

May 7, 2020

This is a good course. It is challenging yet fun. Instructors are very helpful for the assignments. I believe I learned a lot from this course.

By Pawroosh M

•

Sep 9, 2019

I feel the pace of teaching the coding pieces should be slower and clearer. However, overall it is a decent jump-start to learning data science

By Ashutosh S

•

May 5, 2020

The course was great though the assignments should have more clarity in terms of the questions and language ambiguity should be taken care of.

By Purvansh s

•

Mar 31, 2020

It was a great experience to be a part of this course, the explanation was awesome, the hands-on practice was superb, I loved the course alot.

By Lazar M

•

Nov 17, 2019

I learned a lot about Pandas (Dataframe and Series), it's a powerful library. However the course didn't dig enough the statistics part. Thanks

By Mariusz K

•

Nov 10, 2019

Too little of expounding and too much of searching the net by oneself. Too few examples. It is a self-learning but what's the Course for then?

By Hungy Y

•

Aug 9, 2017

Do more examples & explain more theory on screen, rather than have the camera focus on the lecturer.

Highly useful intro tutorial. Thanks team.

By Tanishk S

•

Jun 17, 2017

if you are new to the field this should be in your way to excel. had a great time . pls do refer to the books suggested it is surely necessary

By Rahul K

•

Apr 23, 2021

Great course with everything well explained.

Its just the assignments are a bit tough and you have to explore a lot to get the answers right.

By 21_Keshav M

•

Aug 5, 2020

The Structure of Course is Great!! Although I would love to have mentors explain concepts a little more. Overall a great introductory course.

By Stefanie N

•

Nov 25, 2017

The help in the forum was good, the assignments were fun although I always had some problems with the grader at first, some resolved some not

By Roshni G

•

Feb 2, 2017

The assignments were challenging and cool. Lot of self-study needed to crack them. The lecture videos could have been a bit more interesting.

By Ashish B

•

Jul 3, 2020

The assignments were very interesting and the teaching also was very good. The main help was the provision of notes in the jupyter notebook

By Sven E

•

Nov 16, 2019

assignments quite challenging , way more time needed than the est. times given by coursera. happy I could finish it. on to the next course !

By Marc

•

Dec 8, 2017

Curso interesante para iniciarse en la librería pandas. A veces vas algo perdido pero dedicandole esfuerzo y atención aprendes muchas cosas.

By Jason R

•

Oct 16, 2017

Could have been more challenging and worked with more interested bigger datasets but was a great way to get up to speed on pandas abilities.

By Paula C R

•

Jun 20, 2017

The course is really nice, hands-on all the time. Some questions of the assignments could be improved to avoid ambiguity/subjectivity tough.

By Ishank T

•

May 31, 2020

Not beginner friendly, great assignments which require "stackoverflow" skill. you actually learn from assignment. Videos are not that great

By Dominic l H

•

Mar 5, 2018

good course overall but there needs to be more information on code profiling/optimizing it is really required to pass a part of question 4.