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

4.5
stars
27,089 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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5751 - 5775 of 5,956 Reviews for Introduction to Data Science in Python

By Scott L

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Apr 16, 2020

Pointless course. They teach you very little. Google is your actual teacher.

By Ridhi G

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Feb 2, 2018

the level taught in the course did not match the level of given assignments.

By Alakesh B

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Jun 9, 2020

Lectures were not clear and too short. A lot of external study is required

By Cunyuan Z

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Jul 9, 2019

Lectures are useless. But the assignments CAN BE pretty good practices

By Jair G

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Jan 13, 2018

I felt lost using Python as a data analysis software with this course.

By yunxin y

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Dec 2, 2021

Too difficult as it was largely self learn + memorization, unguided.

By Louis c Y

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May 16, 2022

quite challenging to understand with lecturers assuming you know all

By pouya g

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Jul 1, 2019

the corrector system was very bad and i m not undrestod my mistake

By Hussain

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May 1, 2020

Very fewer video lectures and I felt Assignments to be very hard

By Rishi B

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Jul 22, 2018

I found the teacher boring, but his teaching was a little fast.

By Akansha M

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Jun 1, 2020

for an introduction course it was just too much to understand.

By Nishant B

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Jun 13, 2018

Very fast paced and concepts explanation was not upto the mark

By OdmaaByambasuren

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Nov 5, 2020

Too general. I was expecting more to learn from this course.

By shailja

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Jun 1, 2020

very tough tutorial is easy but assignment are very tough.

By Sean E O

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Nov 5, 2022

Assumes a fair bit of underlying knowledge prior to start

By Satyam c

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May 25, 2020

assignments are tough. didn't expect too much high level.

By Shivani P

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Jul 9, 2019

The lectures were not enough for the assignments provided

By Alejandro P A

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Dec 22, 2017

Good content but too fast pace and confusing assigments.

By Camilo E A P

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Aug 27, 2019

Jupyter notebook for assignments do not work properly.

By Sayali B

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Jun 20, 2018

The questions are very hard and not covered in training

By Deepalakshmi K

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May 23, 2019

Dint teach anything used in the assignments properly

By Chris H

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Mar 22, 2023

not practical - no student interaction. just videos

By Abdullah B

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Sep 10, 2022

Not enough resources to solve the assignment.

By Joao V O C d B

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Jul 27, 2020

The problem is the lack of practical exercises

By Christalin D

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Jun 21, 2020

It's asking for money to continue the course