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Opiniones y comentarios de aprendices correspondientes a Introduction to Data Science in Python por parte de Universidad de Míchigan

17,044 calificaciones
3,890 revisiones

Acerca del Curso

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....

Principales revisiones


May 10, 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


Mar 16, 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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3026 - 3050 de 3,832 revisiones para Introduction to Data Science in Python

por 倪睿阳

Jul 01, 2018

Helped me acquaint with Python and Basic Data manipulating techniques!

por Jarrett C

Nov 20, 2016

This course is a challenging (and solid) introduction to using python.

por Shiva K K

Dec 28, 2017

Was extremely difficult to get the responses to all the assignments!!

por Ishita A

Apr 24, 2020

A little difficult for a beginner to follow but the course was good.

por Jagrut N S

Jan 18, 2020

It's really highly detailed and very good course for Data Scientist.

por m.usman a

Apr 07, 2019

brilliantly maintained and organized courses , but not for beginners

por Deleted A

Jun 27, 2018

A good python intro to familiarize with basic data science packages.

por Kartik S

Jun 06, 2018

Outstanding course to get a kick start in the field of Data Science.

por Chinmay P

Dec 23, 2017

Was a good course that touched up most of the basic python concepts.

por Chakshu G

Jan 18, 2017

Finding optimal solutions for the assignments would have helped more

por yotam h

Mar 22, 2020

great course! highly recommended if you like struggling by yourself

por nitin R

Mar 19, 2020

Course content is really good but can be explained in a better way.

por Vishen M

Oct 19, 2017

Really enjoyed. Assignments take a lot of time, but you learn alot.

por Ariana S C

Aug 17, 2017

Assignments need to provide better feedback when there is an error

por Vignesh R

Aug 08, 2017

Assignments are really good.Video Tutorials could have been better.

por Ioannis A

Dec 29, 2016

Nice lecture. Needs to have more videos and more advanced tutorials

por Veeresh I

Apr 01, 2020

Good course to learn the basic concepts to start with Data Science

por Sean L

Oct 18, 2019

Learned a lot, but mostly by self-learning when doing assignments.

por Yufei H

May 14, 2019

Chapter 2 and 3 are good for me, the rest chapters are too simple.

por Ashley R

Nov 20, 2018

some questions were vague but i guess thats part of the real world

por Aliyu A

Sep 12, 2017

A very good course. recommended for a intermediate data scientists

por aaron_lang

Jul 28, 2017

Overall, the course is pretty good in terms of practice questions.

por Elana A

Mar 22, 2017

Great course and valuable information, but frustrating autograder.

por Anil K C

May 06, 2020

Good assignments to get you to learn the Pandas library in python

por Sadia a S

Mar 21, 2020

It is a helpful course for working with python for data analysis.