University of Michigan
Capstone: Retrieving, Processing, and Visualizing Data with Python
University of Michigan

Capstone: Retrieving, Processing, and Visualizing Data with Python

Sponsored by Pontificia Universidad Católica del Perú

293,044 already enrolled

Gain insight into a topic and learn the fundamentals.
4.7

(13,938 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
Learn at your own pace
98%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.7

(13,938 reviews)

Beginner level
No prior experience required
Flexible schedule
Approx. 9 hours
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

Details to know

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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
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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

Instructor

Instructor ratings
4.9 (1,086 ratings)
Charles Russell Severance
University of Michigan
60 Courses4,364,242 learners

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4.7

13,938 reviews

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MP
5

Reviewed on Apr 22, 2024

BC
5

Reviewed on Apr 28, 2020

NS
5

Reviewed on Apr 9, 2016

Recommended if you're interested in Data Science

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