本课程是 Introduction to Programming with Python and Java 专项课程专项课程的一部分

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Brandon Krakowsky

16,344 人已注册

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隶属于 Master of Computer and Information Technology 学位
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Introduction to Programming with Python and Java 专项课程宾夕法尼亚大学

课程信息

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This course provides an introduction to basic data science techniques using Python.  Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib.  This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data.  Students will gain skills in data aggregation and summarization, as well as basic data visualization.

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根据您的日程表重置截止日期。

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

Coursera Labs

包括实践学习项目。

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第 2 门课程（共 4 门）

Introduction to Programming with Python and Java 专项课程

初级

High school or college math.

“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.

完成时间大约为17 小时

英语（English）

您将学到的内容有

Apply basic data science techniques using Python
Understand and apply core concepts like Data Frames and joining data, and use data analysis libraries like pandas, numpy, and matplotlib
Demonstrate how to load, inspect, and query real-world data, and answer basic questions about that data
Analyze data further by applying learned skills in data aggregation and summarization, as well as basic data visualization

您将获得的技能

Data Science
Python Libraries
Python Programming
Data Analysis
Data Visualization (DataViz)

可灵活调整截止日期

根据您的日程表重置截止日期。

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

Coursera Labs

包括实践学习项目。

了解更多关于 Coursera Labs 的信息

第 2 门课程（共 4 门）

Introduction to Programming with Python and Java 专项课程

初级

High school or college math.

“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.

完成时间大约为17 小时

英语（English）

授课教师

授课教师评分

4.45/5 （106 个评分）

Brandon Krakowsky

Lecturer

School of Engineering and Applied Science

72,996 个学生

7 门课程

提供方

宾夕法尼亚大学

立即开始攻读硕士学位

此课程隶属于宾夕法尼亚大学提供的 100% 在线 Master of Computer and Information Technology。如果您被录取参加全部课程，您的课程将计入您的学位学习进程。

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授课大纲 - 您将从这门课程中学到什么

周

周 1

完成时间为 6 小时

Module 1 : Loading, Querying, & Filtering Data Using the csv Module

This first module provides students with an overview of loading, inspecting, and exploring data using Python's simple csv library. To get started, this module includes a brief overview of Jupyter Notebook and a concise review of basic Python, including data structures, loops, and functions. This module showcases to the students an in-depth analysis of data stored in a .csv file, including basic querying, approaches for dealing with data errors, and how to filter and sort data based on a variety of criteria.

完成时间为 6 小时

8 个视频（总计 31 分钟）, 9 个阅读材料, 3 个测验

8 个视频

Course Introduction 53

About the Instructor : Brandon Krakowsky 1分钟

Downloading & Installing Jupyter Notebook35

Using Jupyter Notebook3分钟

Importing and reading a file using the csv module 3分钟

Coding demonstration : Analyzing the 500 Greatest Albums of All Time12分钟

Coding demonstration : Catching data errors and sorting7分钟

Coding demonstration : Calculating max and min1分钟

9 个阅读材料

Course Layout & Syllabus15分钟

Tips to succeed in this course10分钟

Module 1 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5分钟

Review of dictionaries10分钟

Review of lists5分钟

Review of loops10分钟

Review of functions5分钟

Lambda with max and min10分钟

Homework 1 - Instructions10分钟

2 个练习

Quiz 1 - Loading, Querying, & Filtering Data12分钟

Quiz 2 - Catching Errors & Sorting10分钟

周

周 2

完成时间为 5 小时

Module 2 : Loading, Querying, Joining & Filtering Data Using pandas

In this module, students are introduced to core concepts like the Data Frame and joining data. Students will get experience using pandas, an industry-standard data analysis library, to load and query real-world data and to answer questions about that data. This module demonstrates how to do advanced filtering and indexing, slice subsets of data, restrict data attributes in query results, and do basic computations over the data. Includes how to build a simple recommendation system, and approaches for cleaning data, dealing with missing values, and creating new data.

完成时间为 5 小时

14 个视频（总计 31 分钟）, 5 个阅读材料, 4 个测验

14 个视频

The pandas module 43

Loading data 1分钟

Inspecting data 1分钟

Querying data 47

Joining data 59

Code Along Exercise : Join data 6分钟

Slicing rows 2分钟

Querying data using boolean indexing6分钟

Code Along Exercise : Dive bar recommendation in Las Vegas 4分钟

Computations - sum() 1分钟

Computations - mean() 47

Other methods 26

Updating & creating data 43

Code Along Exercise : Add rating column 1分钟

5 个阅读材料

Module 2 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5分钟

Homework 2 - Instructions10分钟

Casting Data5分钟

Cleaning data & dealing with missing values3分钟

Homework 3 - Instructions10分钟

2 个练习

Quiz 3 - Loading, Inspecting, & Querying Data10分钟

Quiz 4 - Joining & Filtering Data10分钟

周

周 3

完成时间为 5 小时

Module 3 : Summarizing & Visualizing Data

This module takes data analysis a step further by providing an overview of the process of aggregating, summarizing, and visualizing data. Students are introduced to the concept of grouping and indexing data, and how to display results in a pivot table using pandas. This module also demonstrates how to prepare and visualize data using a histogram and scatterplot in Jupyter Notebook. Students will gain skills in data aggregation and summarization, as well as basic data visualization. In addition, students will get experience using data analysis libraries like numpy and matplotlib.

完成时间为 5 小时

18 个视频（总计 22 分钟）, 5 个阅读材料, 4 个测验

18 个视频

Summarizing groups51

The numpy library 48

Pivot tables 29

Using an index 41

Code Along Exercise : Average review count and rating2分钟

Aggregate functions2分钟

Jupyter notebook magic functions 21

The matplotlib library 27

Histograms 36

Histograms Coding Demonstration : To show distribution of data 28

Histograms Coding Demonstration : Preparing data 1分钟

Histograms Coding Demonstration : Setting options for PyPlot 1分钟

Histograms Coding Demonstration : Displaying the visualization 3分钟

Scatterplots 34

Scatterplots Coding Demonstration : To compare data points on different dimensions12

Scatterplots Coding Demonstration : Preparing data 1分钟

Scatterplots Coding Demonstration : Setting options for PyPlot 2分钟

Scatterplots Coding Demonstration : Displaying the visualization 1分钟

5 个阅读材料

Module 3 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5分钟

Homework 4 - Instructions10分钟

Bar charts and plotting pivot tables7分钟

For reference: Seaborn2分钟

Homework 5 - Instructions10分钟

2 个练习

Quiz 5 - Summarizing Data10分钟

Quiz 6 - Visualizing Data12分钟

审阅

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1 star
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来自DATA ANALYSIS USING PYTHON的热门评论

由 PS 提供Feb 21, 2022

Great course for the beginners, would like to thank faculty and staff for making a great course, and the discussion forms were really helpful, Thanks to TAs for reverting back to all the questions.

由 JA 提供Sep 6, 2021

Good course, it gives you the basic info to pandas, numpy and matplotlib. It teaches you how to obtain dataframes, join, filter, group, summarize and visualize data. Short course but really worth it.

由 SD 提供Dec 19, 2022

This course is very good especially for newbies. i have learnt alot. Teaching is very sample anybody can understand

由 AM 提供Feb 7, 2021

Videos touching same theme were too short (26 sec, 1 min, etc.) and disruptive. Wish there could be more practices.

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关于 Introduction to Programming with Python and Java 专项课程

This Specialization starts out by teaching basic concepts in Python and ramps up to more complex subjects such as object-oriented programming and data structures in Java. By the time learners complete this series of four courses, they will be able to write fully-functional programs in both Python and Java, two of the most well-known and frequently used programming languages in the world today.

Introduction to Programming with Python and Java is for students and professionals who have minimal or no prior programming exposure. It’s for motivated learners who have experience with rigorous coursework, and are looking to gain a competitive edge in advancing their career. It’s for folks who are thinking about applying to the University of Pennsylvania’s online Master of Computer and Information Technology degree and want to sample some of the lecture videos and content from the first course in the program. We hope this Specialization is for you. Topics in this Specialization include language syntax, style, programming techniques, and coding conventions. Learn about best practices and good code design, code testing and test-driven development, code debugging, code and program documentation, and computational thinking.

常见问题

我什么时候能够访问课程视频和作业？
讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
有助学金吗？
是的。如果您负担不起学习计划的注册费，则可以在选择学习计划时申请助学金或奖学金。如果您选择的学习计划提供助学金或奖学金，则您将在描述页面上看到一个申请链接。
How much math do I need to know to take this course?
The only math that learners will need for this Specialization is arithmetic and basic concepts in logic.
This course was fun. How can I learn more?
If you enjoyed this course, we recommend Courses 1, 3 and 4 in the series!
If you would like to learn the fundamentals of computer science beyond the basics of programming, consider applying to the Master of Computer and Information and Technology (MCIT) at the University of Pennsylvania, an Ivy League computer science master’s program for people without a computer science background. For an on-campus experience, explore here. If you prefer an online setting, apply to MCIT Online. In fact, the lectures in this series are also used in the online degree program! The Specialization certificate will be viewed favorably by the admissions committee, so be sure to mention it when you apply.

还有其他问题吗？请访问学生帮助中心。

Data Analysis Using Python

课程信息

您将学到的内容有

您将获得的技能