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
26,560 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:

5176 - 5200 of 5,824 Reviews for Introduction to Data Science in Python

By Fede C

May 17, 2020

The instructors did not explain functions well enough, is like they were always in hurry to finish and go to the next lecture. I end up reviewing a lot of internet materials to finish the assessments.

By Marty D

Oct 16, 2019

Lectures spend a lot of time on watching a person talk to a camera. Projects are pretty good, though auto-grader is a pain to debug. TA & Moderators are excellent and so is community taking course.

By Caroline M

Oct 29, 2017

Good overall and I liked the instructor. However the assignments are extremely difficult, especially Week 4 and there are not a lot of online resources made available. Definitely not for a beginner!

By murray d

Apr 21, 2020

Really a struggle to navigate around the discussion forums. The autograder is also a huge challenge. If you can make the actual tests that it runs available up-front would save a lot of time.

By Yiyi C

Jun 23, 2018

The course schedule is tight. I feel like a little bit hard for non-cs major learners. The good thing is you could still upload your homework even after the deadline before the last day of course.

By Jae H H

Apr 3, 2018

The course offers very little guidance. Nevertheless, I learned a lot but it's really not that well structured. The course also makes you do homework on something that is not covered in the class.

By Wei L

May 11, 2018

i like the course content. but the assignments need improvement as i wasted lot of time due to unclear instructions. also if the professor can compile more content into slides that will be great.

By Nidhin J T

Sep 25, 2017

It’s very fast paced. Personally I would prefer to spend more time on each topic particularly since it deals with the basics of data science and is very important to understand each topic clearly

By Alexander K

Jan 17, 2017

Skills acquired when finishing this first course are very useful and applicable. However, lectures and assignments are almost unrelated. This course is nothing for people who are new to python.

By Ruban S

Apr 7, 2019

The coursework validation could use some work to be more concise with error messages but it's OK as long as you work with it.

Content is good and seems to give a decent coverage to the basics.

By Henrik R

Jul 1, 2022

Assignments often only accept certain solutions and go beyond what was taught in the class. Otherwise the course is pretty good, but you will spend hours after hours stuck in the assignments.

By Luis V

Mar 22, 2021

Great course, but the programming assignments take too long time and are more than python only assignments, researching about geography or where a team belongs to, that takes a lot of time.

By Mark E

Mar 14, 2017

This course relies almost exclusively on self learning of the details of pandas. It would be greatly improved by examples of how to use pandas to solve problems similar to the assignments.

By Kevin d V

Dec 6, 2017

I learned a lot. But be aware that programming skills are a requirement for this course and that you will have to research the web (stackoverflow, pandas documentation) on your own a lot.

By Sebastian R

Dec 3, 2019

Good course i.g! But it is quite annoying, that the auto grader (python 3.5 ?) does not behave like the online coursera notebook (python 3.6.2), which leads to errors at the evaluation.

By M J

Dec 21, 2017

Course material is good, covers the right topics to get started with python and pandas. Assignments and especially the grading process require a bit more patience than I was expecting.

By Kalle A

Jan 3, 2018

I enjoyed the course, but I think the exercises could be improved a bit. Especially in the last two ones could have better explanations and examples of what's expected from the answer.

By wilfried l

Dec 26, 2019

You will learn a lot, by yourself to solve the assignment.

Which could be see as a good way to learn

Time to do each assignment is clearly under estimated. You can multiply by 2 easily

By Juan C M

Jul 4, 2020

Too much self-learning taking into account that this is supposed to be a course, could make example projects for better understanding instead of jumping right away to the assignment.

By Itzhak K

Nov 5, 2019

The course was fine, but the last assignment was too hard for me. And I think that for Introduction to data science - the first course in the series it shouldn't be so complicated.

By Rhishikesh J

Mar 29, 2018

Amazing course for an introduction to the pandas library and its main data structures Series and DataFrame.

Improvements could be made to the hypothesis testing section of the course.

By Aarya B

Sep 15, 2019

Great explanation. But the speed of tutor is quite fast, so one needs to rewatch again and again. And for better understanding one has to practice questions from external resources.

By arley s c l

Nov 1, 2022

I think i could be better if in a single module we checkout just a single dataframe and try to extract and transform the most data as possible insted do it with severals of them.

By Fei Y

Oct 28, 2018

You should break assignment into smaller substeps. You should also provide more comments like 'your dataframe size is incorrect or starting from which line you result has error'.

By Lucas S D S

Jun 16, 2020

It's a really challenging course for someone with an intermediate level of Python and pandas, I really enjoyed . The only minor point is the quality of the theory on the videos.