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

4.5
stars
24,276 ratings
5,438 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

SI
Mar 15, 2018

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .

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5176 - 5200 of 5,367 Reviews for Introduction to Data Science in Python

By KJ B

Jun 20, 2017

The code is already written, which means there is no opportunity to practice. More over, the examples have no baring on the homework problems. Would not recommend this course.

By Dr. P R

Jun 15, 2020

The lectures are not very useful in solving the assignments.

This cannot be said as an introductory course rather it requires good python skills before starting this course.

By Jose N N P

Feb 15, 2018

Lot's of problems with the autograder, lack of teaching staff support to answer questions in a timely manner. Assignments need to be more representative of class lectures.

By Bernard

Sep 7, 2019

Content wise is ok. An easy introduction. The bugs made it annoying. Especially Week 2 final exercise https://nzh13lxjj0.execute-api.us-east-1.amazonaws.com/prod/index/2/

By Marcin W

Jul 2, 2019

It would be a very nice course... if this guy was actually teaching and not explaining the basics and expecting people just to search online of the remaining 90%

By priyanshi b

May 19, 2020

the voice of the teacher is not loud plus the assignments are too tough to clear, I think a basic version of learning pandas should be there before this course.

By Deleted A

Jun 13, 2018

Too fast and need to break the content even smaller with frequent practise assignment and graded quiz, just make it like python for everybody specialization

By Dario M

Jun 18, 2019

I didn’t like how the subjects are explained, and i feel the grading system is not good at all. It would be better if assignments were graded by peers.

By Krishna P K

Sep 10, 2017

The course rushes through a lot of concepts and expects the learner to figure out real insights using public resources. The reference material is poor.

By Raghav G

Jul 13, 2020

A horrible course with very little detail than required, I had to access a lot of additional resources than coursera in order to complete this course.

By Shikhar S

Jun 2, 2019

The content of teaching in videos is a way too less than the level of asssignments .I had to make a lot of efforts on my own to understand the things.

By Josep R

Apr 17, 2018

The ways is taught is not very good - basically a lot info in short timespan. I don't think the Jupyter Notebooks format is the adequate for teaching.

By Kandregula V N A

Aug 26, 2020

its hard for beginners to understand in the flow , it took me time to complete the course by studying about the same concept in other resources too

By Manuel M

Feb 26, 2018

For some reason the format in which the lectures are organized lack a lot of tact and seem to be made with no pedagogic consideration whatsoever.

By Clement G

Sep 17, 2017

Explanations of python were pretty coarse, the video was not helping much. I feel like I spent time doing 99% of python and 1% of data science.

By Emil K

Jan 5, 2017

Many bugs, lecture content does not cover topics required to complete the assignments, assignment instructions are not written in a clear way.

By KAMAL G

Oct 7, 2018

The speaker speaks too fast for any useful "sharing". One need to do reverse engineering to understand the code and underlying concept.

By Adam R

Aug 20, 2018

Videos not very explanatory, ended up being a lot of self-teaching, video seemed too scripted and didn't really explain concepts well

By Chenfeng L

Nov 13, 2016

Good course materials and the assignment itself is pretty good, but the grader is buggy, not informative and wasted a lot of my time.

By Manya A

Jan 31, 2017

Too much focus on databases and database operations, rather than data science.

The assignments are too difficult for a 4 week course.

By MAHESWAR N

Jul 28, 2019

Assignments were not clearly documented, causing lot of time spent in understanding the requirements than implementing a solution.

By Dilpreet S N

Apr 2, 2020

The course is very fast-paced and explanations are not clear neither detailed, it looks like instructors are just doing formality

By Sarah S

Mar 30, 2021

This is a poorly taught course which tells you to go away and teach yourself data science rather than teaching you data science.

By Abhishek c

Jun 7, 2019

The learning is very fast paced.It seems like the trainer is in hurry.He just touched some keyword without going into details.

By Kush S

May 20, 2020

The instructor is very fast and assignments are very tough. Their is huge difference between the course and the structure.