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

4.5
stars
25,673 ratings
5,718 reviews

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

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

YY

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.

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3751 - 3775 of 5,672 Reviews for Introduction to Data Science in Python

By Joseph D P

Oct 2, 2017

Very helpful for learning data science, but the videos go way too fast and don't cover nearly enough material to do the assignments. The assignments do force you to learn how to python, but through lots of googling, stack overflow and pandas documentation.

By Tahir M

May 22, 2017

They follow a practical approach and present you only the very relevant material so you do not stuck too much into theory. Note that this is an intermediate-level course and you need some experience, self-learning skills, and some patience to be successful.

By Gorripati p

Jan 9, 2021

This course will help us to get more knowledge on python & machine learning concepts thouroughly.

Also this cousera certificate gives benfits to us for semester usage and job point of view.

happy to learn so much of new concepts in online at our home

Thanks!!

By hasan s

Aug 5, 2018

The exercises and content was very good but instructions/explanations were not very detailed with most of the concepts left for self study. But overall a great course in terms of getting you started with pandas for effective data analytics on tabular data.

By Jim E

Jan 17, 2017

The content and the instruction were great: just the right level for someone like me with experience in other programming languages a decent familiarity with stats.

There were a few glitches with the auto-grader for the assignments, but nothing to onerous.

By E. U

Nov 12, 2016

A great intro to pandas. Challenging even for those with experience using the library. There were some struggles with the autogravder, but they were being worked out, and the integration of the Jupyter notebook system directly into the class is fantastic.

By Pankaj

Feb 21, 2017

While the course was great, the Jupyter notebooks and the background shells gave me several unnecessary errors. While this was a smaller issue, I think the practice Notebooks should be somewhat in line with the assignments. I struggles on Assignment #3.

By Tom M

Sep 18, 2017

The course was a unnecessarily hard because of the lack of feedback from the grader, unclear requirements / function definition in the final project and difference in the file downloaded for the project and the one used in the Coursera python notebook.

By Joanna N

Jan 15, 2020

Good materials and videos, iteresting exercises - the only thing I would improve is the exercises description - not for all of the exerisises it was clear enough for me (especially as I'm not from the US and I'm not familiar with your census data :) )

By Christoph H

Aug 26, 2020

I learned a lot through the challenging assignments, but the course materials (videos) are not very useful. They only cover the very basics for the assignments, so be prepared to study a lot on your own. Knowing pandas beforehand helps a lot too IMO.

By Anup J

Apr 21, 2020

This is an exceptional undertaking by the university of Michigian for benefit of the students in the field of data science and Machine Learning.This is perhaps the only course which focuses on real world application of data science skills to practice

By Isabel O

Jan 18, 2018

Good explanations, well structured. However, I wish the weekly content would have prepared better for the assignments. If I have to add another 3h per week to find the right advice on stack overflow, that must be stated somewhere so I can plan ahead.

By Carlos A R R

Jul 5, 2017

Very good course with a lot of material and challenging assignments. Gave it only 4 stars because in some assignments is more difficult to agree with the autograder than to get the correct answer (e.g., data type mismatch between float and float64).

By Shailesh K

Sep 9, 2021

​Excellent explanatory videos and lot is covered in just four week of course but it definitely need good grasp of pandas and numpy libraries for passing the assignnments. I definitely recommend this course as it will push you to learn and do more.

By Abhishek R

Mar 16, 2018

The content is really not good for novices. But the challenges I faced during assessments, did a lot of help. I can now understand the topics much better and at the least I am able to plan to clean the data and work on it much better than earlier.

By Nitesh R S

Mar 21, 2017

The course content is great. However, basic knowledge of python programming language is required. Since I didn't know python coding rules, I really struggled for a while. Maybe, basics of python in additional resources will help a lot of learners.

By Ahmad S

Oct 21, 2018

In my view, It is recommended to study a book on Python data analysis tool-kit panda and numpy. The course video quality is very good, instructor voice is clear and load. I highly recommended to take this course who wants to be a Data Scientist.

By vineeth s

Aug 4, 2018

This course would be recommended for anyone who has got good python skills already and want to do data analysis using python at a quick pace. Overall, It is fun doing the assignments and thinking more in a pandas way rather than in pythonic way.

By vishal r

May 5, 2020

The projects were extremely helpful to learn various concepts . The videos could have been a little more descriptive to equip us with a little more knowledge so as to tackle the projects with a little ease .apart from that it was really great

By Lee A

Jan 15, 2019

Class was good, and the information was presented in a way that was straightforward to understand and apply. I wish the exercise autograder provided more feedback. Sometimes the lack of actionable information made it difficult to solve problems.

By wondertweet

Apr 16, 2018

The course is a good introduction for data science and helps me learn pandas and numpy. You may not learn how to use these tools only form this online lesson, but you can be aware of what you need to know if you would like to work on this field.

By MONIKA C

Dec 28, 2019

Good, comprehensive course. At the end you are ready to get and clean data and make some simple analysis on your own. But you need a lot of effort to do programming assignments. Save double amount of time than it is estimated for this course.

By Xiaojie Z

Nov 26, 2018

This course provides good material. The assignments could be very difficult because the instructions were not clear. In real life, you would have a chance to clarify while it is difficult to do so in coursera.

Overall, it is a good course.

By Darren S

Nov 21, 2016

The course was great - the lectures were clear and simple; I learned a great deal! However, instructions for the assessments could have been clearer, and there were a few issues with the autograder (though I'm sure those will be weeded out).

By Richard B

Aug 21, 2018

Generally good - with challenging assignments, explanation could be better and grading unit tests more flexible.

Some of the content is rushed - but it is comprehensive and you need to have some python programming behind you before you start.