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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

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

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3601 - 3625 of 5,951 Reviews for Introduction to Data Science in Python

By Hassan N

Dec 24, 2019

tnx

By Thomas F

Jun 21, 2019

:-)

By Jan-Jaap G d S

Nov 18, 2017

n/a

By JME

Oct 3, 2017

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By Sk M u

Oct 22, 2024

no

By Nirav N

Mar 10, 2023

NA

By afraj m [ T ]

Jul 13, 2020

no

By Aditi N

Dec 31, 2019

ok

By Ankit S

Jun 6, 2022

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Jun 13, 2021

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Sep 4, 2020

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Aug 20, 2020

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Jun 1, 2020

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May 14, 2019

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Mar 11, 2019

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By Srinivasarao M

Feb 4, 2019

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By David A D V

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By Anyi L

Aug 20, 2018

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By Khushpreet S

Apr 23, 2018

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By Thomas

Dec 29, 2017

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By James R

Feb 5, 2017

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