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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

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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

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.

DM

Nov 21, 2016

Great course! I liked how the focus was mainly on the practical aspects of data science. No 'dry' course material. I know much more about the practical side of data analysis than before! Thank you!

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3551 - Introduction to Data Science in Python 的 3575 个评论（共 5,987 个）

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Sep 19, 2024

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