Introduction to Data Science in Python

开始时间: 08/08/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew



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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.

Python数据科学概论:本课程将向学习者介绍python编程环境的基础知识,包括基本的python编程技术,如lambda,读取和操作csv文件以及numpy库。该课程将介绍使用流行的python pandas数据科学库的数据处理和清理技术,并介绍Series和DataFrame的抽象作为用于数据分析的中心数据结构,以及有关如何使用诸如groupby,merge和有效地透视表。在本课程结束时,学生将能够获取表格数据,对其进行清理,操作以及进行基本的推论统计分析。 本课程应优先于其他任何使用Python的应用数据科学课程:应用绘图,制图和图形学Python中的数据表示,Python中的应用机器学习,Python中的应用文本挖掘,Python中的应用社交网络分析。


In this week you'll get an introduction to the field of data science, review common Python functionality and features which data scientists use, and be introduced to the Coursera Jupyter Notebook for the lectures. All of the course information on grading, prerequisites, and expectations are on the course syllabus, and you can find more information about the Jupyter Notebooks on our Course Resources page.





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