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Capstone: Retrieving, Processing, and Visualizing Data with Python

Capstone: Retrieving, Processing, and Visualizing Data with Python

This course is part of Python for Everybody Specialization

Instructor: Charles Russell Severance

322,853 already enrolled

Included with

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7 modules

Gain insight into a topic and learn the fundamentals.

14,420 reviews

Beginner level

No prior experience required

Flexible schedule

9 hours to complete

Learn at your own pace

98%

Most learners liked this course

7 modules

Gain insight into a topic and learn the fundamentals.

14,420 reviews

Beginner level

No prior experience required

Flexible schedule

9 hours to complete

Learn at your own pace

98%

Most learners liked this course

What you'll learn

Make use of unicode characters and strings
Understand the basics of building a search engine
Select and process the data of your choice
Create email data visualizations

Skills you'll gain

Tools you'll learn

Python Programming

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

1 assignment

Taught in English

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Build your subject-matter expertise

This course is part of the Python for Everybody Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 7 modules in this course

In the capstone, students will build a series of applications to retrieve, process and visualize data using Python. The projects will involve all the elements of the specialization. In the first part of the capstone, students will do some visualizations to become familiar with the technologies in use and then will pursue their own project to visualize some other data that they have or can find. Chapters 15 and 16 from the book “Python for Everybody” will serve as the backbone for the capstone. This course covers Python 3.

Module details

Congratulations to everyone for making it this far. Before you begin, please view the Introduction video and read the Capstone Overview. The Course Resources section contains additional course-wide material that you may want to refer to in future weeks.

What's included

4 videos5 readings1 assignment

4 videosTotal 36 minutes

Introduction: Welcome to the Class3 minutes
Unicode Characters and Strings17 minutes
Office Hours in Den Haag, Netherlands4 minutes
Interview: John Resig and Pam Fox - Khan Academy12 minutes

5 readingsTotal 50 minutes

Capstone Overview10 minutes
Help Us Learn More About You!10 minutes
Course Syllabus10 minutes
Python Textbook10 minutes
Capstone Completion Options10 minutes

1 assignment

Python for Everybody - A Review0 minutes

This week we will download and run a simple version of the Google PageRank Algorithm and practice spidering some content. The assignment is peer-graded, and the first of three optional Honors assignments in the course. This a continuation of the material covered in Course 4 of the specialization, and is based on Chapter 16 of the textbook.

What's included

6 videos2 readings1 app item

6 videosTotal 61 minutes

Page Rank Overview8 minutes
Worked Example: Page Rank - Spidering17 minutes
Worked Example: Page Rank - Computation16 minutes
Worked Example: Page Rank - Visualization7 minutes
Office Hours Detroit, Michigan2 minutes
Interview: Anil Jain - Image Processing12 minutes

2 readingsTotal 20 minutes

Building a Search Engine - Introduction10 minutes
Peer Graded Assignment - Instructor Input10 minutes

1 app itemTotal 60 minutes

Peer Grade: Page Rank60 minutes

The optional Capstone project is your opportunity to select, process, and visualize the data of your choice, and receive feedback from your peers. The project is not graded, and can be as simple or complex as you like. This week's assignment is to identify a data source and make a short discussion forum post describing the data source and outlining some possible analysis that could be done with it. You will not be required to use the data source presented here for your actual analysis.

What's included

2 videos2 readings1 discussion prompt

In our second optional Honors assignment, we will retrieve and process email data from the Sakai open source project. Video lectures will walk you through the process of retrieving, cleaning up, and modeling the data.

What's included

5 videos1 reading1 app item

5 videosTotal 49 minutes

Gmane Introduction6 minutes
Worked Example: Gmane / Mail - Retrieval17 minutes
Worked Example: Gmane / Mail - Model13 minutes
Office Hours Baltimore, MD1 minute
Interview: Bruce Schneier - Building Cryptographic Systems11 minutes

1 readingTotal 10 minutes

Spidering and Modeling Email Data - Introduction10 minutes

1 app itemTotal 60 minutes

Loading and Modeling Mail Data60 minutes

The task for this week is to make a discussion thread post that reflects the progress you have made to date in retrieving and cleaning up your data source so can perform your analysis. Feedback from other students is encouraged to help you refine the process.

What's included

1 video1 reading1 discussion prompt

In the final optional Honors assignment, we will do two visualizations of the email data you have retrieved and processed: a word cloud to visualize the frequency distribution and a timeline to show how the data is changing over time.

What's included

3 videos1 reading1 app item

This week you will discuss the analysis of your data to the class. While many of the projects will result in a visualization of the data, any other results of analyzing the data are equally valued, so use whatever form of analysis and display is most appropriate to the data set you have selected.

What's included

2 videos3 readings1 discussion prompt

2 videosTotal 14 minutes

Office Hours - Dr. Chuck's Office - Ann Arbor, Michigan2 minutes
Video: Steve Jobs, NeXT and the Internet12 minutes

3 readingsTotal 23 minutes

Visualizing new Data Sources - Introduction10 minutes
Post-Course Survey10 minutes
A special reason to celebrate your success 3 minutes

1 discussion promptTotal 10 minutes

Data Analysis and Visualization10 minutes

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Instructor

Instructor ratings

(1,189 ratings)

Charles Russell Severance

University of Michigan

60 Courses4,883,429 learners

Offered by

University of Michigan

Learner reviews

5 stars
82.42%
4 stars
12.26%
3 stars
3.34%
2 stars
1.02%
1 star
0.94%

Showing 3 of 14420

Reviewed on Apr 19, 2017

Excellent, simply the best experience of on line education I have had, the course is extremely complete and useful, the support of the staff of mentors is remarkable also, I am extremely grateful.

Reviewed on Mar 22, 2019

This is a great course. I like this course very much because I can retrieve, process and visualize data in Python in a very good way I never used before. This course is very useful in real world.

Reviewed on Oct 30, 2016

The sample solution and explanations are very good since it gives a complete whole picture of doing a big data analysis project. The assignment is very easy, but good to get the specialization.

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