About 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.
Created by: University of Michigan
Taught by: Charles Severance, Associate Professor
School of Information
| Basic Info |
Course 5 of 5 in the
Python for Everybody Specialization.
|
| Commitment | 6 weeks of study, 2-4 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Welcome to the Capstone
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.
4 videos, 4 readings
Graded: Using Encoded Data in Python 3
WEEK 2
Building a Search Engine
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 required assignments in the course. This a continuation of the material covered in C...
6 videos, 1 reading
Graded: Peer Grade: Page Rank
WEEK 3
Exploring Data Sources (Project)
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 ...
2 videos, 2 readings
WEEK 4
Spidering and Modeling Email Data
In our second required 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.
5 videos, 1 reading
Graded: Loading and Modeling Mail Data
WEEK 5
Accessing New Data Sources (Project)
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.
1 video, 1 reading
WEEK 6
Visualizing Email Data
In the final required 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.
3 videos, 1 reading
Graded: Visualizing Email Data
WEEK 7
Visualizing new Data Sources (Project)
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 appropria...
2 videos, 2 readings
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Pricing
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
Ratings and Reviews
A nice place to test your Python skills to analyze search engine data.
I was hoping for a climax in building my own set of scripts that would cover the whole specialization. That is a possibillity, but not required. I will try so anyway.
Despite of that I have learned a lot from this capstone project.
Excellent Python course !! Thank you Dr. Chuck
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