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

4.5
stars
27,081 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

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

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.

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5326 - 5350 of 5,952 Reviews for Introduction to Data Science in Python

By Estapraq M K

Jan 7, 2018

The instructor doesn't explain that much, he could do better than that. It is an independent study. The only thing I enjoyed was the links and the articles, that was all.

By Micah D

May 2, 2018

Course has a great amount of information that is wonderful, but the instructional videos are less and less helpful as time goes on, and the autograder is the devil.

By Vishwakarthik R

Jul 28, 2017

The course content was good but the assignments were way too tough.The assignments should have been a bit easier because i lost interest due to the tough questions.

By Jan K

Jul 15, 2017

The programming assignments were a little frustrating.

I feel a little more time should be spent on the theory behind pandas and how the library works conceptually.

By Hong_Linshuo

Jul 9, 2019

I think the assignments waste too much of my time since I have no problems using proper programming skills, but have lots of problems catering to the auto grader.

By Taras P

Dec 10, 2016

Top free course about Data Science. But I think lectures must be more detailed and related to assignments. And assignments could be less ambiguous and more clear.

By Manuela D

Jan 3, 2018

Some exercises of the assignments where ways to difficult compared to what learned during lectures: much more details should be provided about data manipulation

By PRACHUR G

Apr 27, 2020

the course is really good but there are issues with autograder. Though they are addressed in forums you'll have to go through them and hence wasting your time.

By Joshua C

Jan 24, 2018

You'll spend more time struggling with the jupyter notebook (assignment platform) than actually writing or learning code. The lectures are really good, though.

By Yan X

Nov 4, 2019

Great content. But some assignment questions are not that clear and might cost you more time than its worth. And feedback from mentor is not that responsive.

By Abhijit G

Apr 27, 2018

The course is well designed and assignments are complex. What I did not like about this course is that the assignments are not well explained with examples.

By Narayan S

Aug 17, 2020

The main problem is with the auto grader. There are too many issues making it cumbersome to get the assignment submission right in one go. Please fix this.

By Parth M

Jul 12, 2020

Had to learn most of it by myself. Got discouraging at a certain point. Should have informed about the prerequisites.

Learn Numpy, Pandas before enrolling.

By Ryan T

May 18, 2020

Some parts were quickly rushed through and poorly explained. However, they did explain the bare bones of pandas, which was the main reason for this course.

By Pengyue S

Jul 1, 2018

There is one critical technical problem lying in the assignment three and already caused hundreds of students' grade blank in the forum, including myself.

By Nehal c

Jul 3, 2019

As a beginner I found it a bit of a brisk over the topic. There was a lack of basic questions. But in the end I was coping up and then the course ended.

By KUSHAL B

Jul 14, 2020

too fast in explaining it was bit difficult to keep up with the explanation,small code example were taught but assignments questions was too difficult

By Aram M

May 25, 2018

Great course material, but the autograder system was frustrating to work with for assignments, and often made me less motivated to work on the course.

By Himansu A

Jan 16, 2019

The course is okay for beginners as it is having only few lecturers for basics. Coursera experience was good. Overall i am satisfied with the course.

By Yaseen H

Sep 24, 2018

The assignments are not even close what is being taught. We are taking this course so we get everything in one place. Curriculum has to be improved

By Alvaro B F

Aug 30, 2021

I think the lecture about grouping could be improved with more practical examples, I had to search for external sources to understand the concept.

By Souvik B

Jun 8, 2020

Not at all for beginnners. Fast-paced with more focus on self-learning and grinding,rather than focussing more upon the concepts. Dry presentation.

By Константин К

Mar 4, 2018

Quite bad knowledge delivery from lectures. The course is rather self learning than course. A lot of vague points and uncertainties in assignments.

By VARUN K

Mar 4, 2017

The course instructor could have been more elaborate with the examples. I felt there was a wide gap between the exercises and the course material.

By Justin L

Dec 6, 2016

Assignments are challenging, but some questions are very vague and require lots of trial and error guesswork to get the autograder to accept them.