Data Analysis with Python

4.7
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13,450 个评分

186,485 人已注册

授课教师： Joseph Santarcangelo

字幕：阿拉伯语（Arabic）, 法语（French）,

提供方

IBM

课程信息

626,275 次近期查看

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more!
Topics covered:

1) Importing Datasets
2) Cleaning the Data
3) Data frame manipulation
4) Summarizing the Data
5) Building machine learning Regression models
6) Building data pipelines

 Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts:

Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions.

If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.  

LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

学生职业成果

23%

完成这些课程后已开始新的职业生涯

25%

通过此课程获得实实在在的工作福利

11%

加薪或升职

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。

初级

完成时间大约为13 小时

英语（English）

字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 土耳其语（Turkish）, 英语（English）, 西班牙语（Spanish）, 波斯语

您将获得的技能

Predictive ModellingPython ProgrammingData AnalysisData Visualization (DataViz)Model Selection

学生职业成果

23%

完成这些课程后已开始新的职业生涯

25%

通过此课程获得实实在在的工作福利

11%

加薪或升职

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。

初级

完成时间大约为13 小时

英语（English）

讲师

授课教师评分

4.61/5 （1,528 个评分）

Joseph Santarcangelo

Ph.D., Data Scientist at IBM

IBM Developer Skills Network

493,037 个学生

21 门课程

提供方

IBM

IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.

教学大纲 - 您将从这门课程中学到什么

内容评分93%（22,530 个评分）

周

周 1

完成时间为 2 小时

Importing Datasets

完成时间为 2 小时

6 个视频（总计 20 分钟）, 1 个阅读材料, 6 个测验

6 个视频

The Problem1分钟

Understanding the Data2分钟

Python Packages for Data Science2分钟

Importing and Exporting Data in Python4分钟

Getting Started Analyzing Data in Python4分钟

Accessing Databases with Python4分钟

1 个阅读材料

Lesson Summary1分钟

5 个练习

Practice Quiz: Understanding the Data2分钟

Practice Quiz: Python Packages for Data Science2分钟

Practice Quiz: Importing and Exporting Data in Python2分钟

Practice Quiz: Getting Started Analyzing Data in Python2分钟

Graded Quiz: Importing Datasets10分钟

周

周 2

完成时间为 2 小时

Data Wrangling

完成时间为 2 小时

6 个视频（总计 19 分钟）, 1 个阅读材料, 6 个测验

6 个视频

Pre-processing Data in Python2分钟

Dealing with Missing Values in Python6分钟

Data Formatting in Python3分钟

Data Normalization in Python3分钟

Binning in Python1分钟

Turning categorical variables into quantitative variables in Python2分钟

1 个阅读材料

Lesson Summary10分钟

5 个练习

Practice Quiz: Dealing with Missing Values in Python6分钟

Practice Quiz: Data Formatting in Python2分钟

Practice Quiz: Data Normalization in Python2分钟

Practice Quiz: Turning categorical variables into quantitative variables in Python2分钟

Graded Quiz: Data Wrangling10分钟

周

周 3

完成时间为 2 小时

Exploratory Data Analysis

完成时间为 2 小时

6 个视频（总计 20 分钟）, 1 个阅读材料, 6 个测验

6 个视频

Exploratory Data Analysis1分钟

Descriptive Statistics4分钟

GroupBy in Python3分钟

Correlation2分钟

Correlation - Statistics2分钟

Association between two categorical variables: Chi-Square4分钟

1 个阅读材料

Lesson Summary1分钟

5 个练习

Practice Quiz: Descriptive Statistics2分钟

Practice Quiz: GroupBy in Python2分钟

Correlation4分钟

Practice Quiz: Correlation - Statistics2分钟

Graded Quiz: Exploratory Data Analysis10分钟

周

周 4

完成时间为 2 小时

Model Development

完成时间为 2 小时

6 个视频（总计 27 分钟）, 1 个阅读材料, 6 个测验

6 个视频

Model Development1分钟

Linear Regression and Multiple Linear Regression6分钟

Model Evaluation using Visualization4分钟

Polynomial Regression and Pipelines4分钟

Measures for In-Sample Evaluation3分钟

Prediction and Decision Making5分钟

1 个阅读材料

Lesson Summary1分钟

5 个练习

Practice Quiz: Linear Regression and Multiple Linear Regression4分钟

Practice Quiz: Model Evaluation using Visualization4分钟

Practice Quiz: Polynomial Regression and Pipelines2分钟

Practice Quiz: Measures for In-Sample Evaluation2分钟

Graded Quiz: Model Development10分钟

审阅

4.7

1972 条评论

5 stars
75.39%
4 stars
18.99%
3 stars
3.99%
2 stars
0.93%
1 star
0.66%

来自DATA ANALYSIS WITH PYTHON的热门评论

由 SC 提供May 5, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

由 RP 提供Apr 19, 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

由 MA 提供Jul 28, 2020

AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.

由 HS 提供Jul 29, 2020

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently.overall best course in making anyone eager to learn from basics to handle advances with ease.

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Will I earn university credit for completing the Course?
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Data Analysis with Python

课程信息

学生职业成果

23%

25%

11%

您将获得的技能

学生职业成果

23%

25%

11%

讲师

Joseph Santarcangelo

提供方

IBM

教学大纲 - 您将从这门课程中学到什么

周 1

Importing Datasets

周 2

Data Wrangling

周 3

Exploratory Data Analysis

周 4

Model Development

周 5

Model Evaluation

周 6

Final Assignment

审阅

来自DATA ANALYSIS WITH PYTHON的热门评论

常见问题

开拓职业生涯或促进职业发展

浏览热门主题

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在线获得学位或证书

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Data Analysis with Python

课程信息

学生职业成果

23%

25%

11%

您将获得的技能

学生职业成果

23%

25%

11%

讲师

Joseph Santarcangelo

提供方

IBM

教学大纲 - 您将从这门课程中学到什么

周 1

Importing Datasets

周 2

Data Wrangling

周 3

Exploratory Data Analysis

周 4

Model Development

周 5

Model Evaluation

周 6

Final Assignment

审阅

来自DATA ANALYSIS WITH PYTHON的热门评论

常见问题

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开拓职业生涯或促进职业发展

浏览热门主题

提升团队技能

在线获得学位或证书

Coursera

社区

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