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.
Capstone: Retrieving, Processing, and Visualizing Data with Python
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Capstone: Retrieving, Processing, and Visualizing Data with Python
This course is part of Python for Everybody Specialization
Instructor: Charles Russell Severance
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4.7
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Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
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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
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Assessments
1 assignment
Taught in English
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This course is part of the Python for Everybody Specialization
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There are 7 modules in this course
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
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
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
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
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4.9 (1,087 ratings)Offered by
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University of Michigan
University of Michigan
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