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学生对 University of Michigan 提供的 Introduction to Data Science in Python 的评价和反馈

4.5
27,240 个评分

课程概述

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....

热门审阅

KL

Mar 11, 2018

A very nice introduction to libraries/skills used by data scientists. The auto-grader was extremely annoying though. Also, I felt that some of the questions on the assignments were a bit ambiguous.

ME

Jul 26, 2020

Quizzes were very challenging and interesting. I learned alot. The main drawback in this course is that the materials are insufficient to answer the assignments.And some questions were not so clear.

筛选依据:

1826 - Introduction to Data Science in Python 的 1850 个评论(共 5,986 个)

创建者 Nishant

Jun 1, 2020

The study material of this course is well organised and thanks to lecturer ..

创建者 Md. A I

May 6, 2020

I would give 4.5. one of the best course in coursera. the trainer was awesome.

创建者 Alex C

Feb 12, 2020

A lot of information and definitely need more than 4 week(6-8h) to accomplish.

创建者 Aravind G

Oct 11, 2019

Its very good cousrea , I have done in coursera and it cleared all my concepts

创建者 Akarsha S

Aug 18, 2019

Very Interesting course , and really beneficial for people new to Data Science

创建者 Raunak S

Jun 8, 2019

create more courses as such and allow unprivileged individuals access to them.

创建者 Prashant M

Apr 27, 2019

Requires a lot of home work , but good learning <3, thank you for the guidance

创建者 Carlos B

Jul 17, 2017

At the moment, a very interesting experience. It seems very similar to Matlab.

创建者 Sikko P v ' K

Jan 22, 2017

very practical and efficient - high useful skills gained per time spent ratio!

创建者 Roshith G

Nov 13, 2021

its an amazing course I have learnt a lot Thanks a lot University Of Michigan

创建者 RAHUL J J

Jul 27, 2021

Very useful course. But you need to have a little python knowledge beforehand

创建者 Ali Z

Aug 16, 2020

Best Data Science Course. Learned new techniques and Insight of Data Science.

创建者 Levente L

May 27, 2020

Requires some self learning/searching but I liked the challenging assingments

创建者 Shantel D

May 5, 2020

Super challenging, but you definitely learn a lot of industry relevant theory

创建者 Hashan M

Apr 12, 2020

This course is great as it was. Itself contains full content to guide A to Z.

创建者 Chiranjeetsinh J

Apr 8, 2019

Great exercises and very god hands-on learning experience with pandas library

创建者 Wesley A B J

Sep 3, 2018

Great introductory course overall, but requires a lot of self study from you.

创建者 goro

Aug 19, 2018

it is a great source if you are a beginner in pandas it will help you so much

创建者 Mahsa A

Jun 24, 2018

This course was very helpful to start learning about data science and python.

创建者 Alene K R

Oct 12, 2017

Chris Brooks is a fantastic instructor. The lectures are clear and engaging.

创建者 Alexander B (

Nov 19, 2016

Awsome course with good balance betweern Challange,Reasearch and Progression.

创建者 Luis O

Apr 5, 2021

It is a difficult course but if you take it seriosly you will learn a lot of

创建者 Hasan M

Sep 8, 2020

Good course, but there is a gap between the assignments and course lectures.

创建者 Andres A R G

Jul 15, 2020

This course is very useful, I am so glad and thankfulness with courses team.