Clinical Professor, School of Information
Capstone: Retrieving, Processing, and Visualizing Data with Python
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
7 Modules
7 Hours
1 hr per module (approx.)
Rating
About Capstone: Retrieving, Processing, and Visualizing Data with Python
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.
Skills You'll Gain
- Data Analysis
- Database Design
- Data Visualization
- Descriptive Statistics
- Matplotlib (Python Package)
- Pandas (Python Package)
- Python For Data Analysis
- Python (Programming Language)
- Statistical Graphics
What You'll Earn
- Certificate of Completion:
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Welcome Message
Welcome to Capstone: Retrieving, Processing, and Visualizing Data with Python, a course where you will build applications to retrieve, process, and visualize data using Python 3. You will apply knowledge from the Python for Everybody series to create visualizations, analyze large datasets, and complete your own project using real-world data. This hands-on capstone will strengthen your programming and data analysis skills.
This abbreviated syllabus description was created with the help of AI tools and reviewed by staff. The full syllabus is available to those who enroll in the course.
Course Schedule
Module 1: Welcome to the Capstone
- Video: Welcome to the class
- Reading: Optional: Please give us your mailing address
- Reading: Help us learn more about you!
- Reading: Capstone Overview
- Reading: Technology Notes for this Course
- Video: Demonstrating the Presentation Gallery
- App Item: Peer Presentation: Welcome to the class
- Video: Office Hours in Den Haag, Netherlands
- Video: Interview: John Resig and Pam Fox - Khan Academy
- Graded: Python for Everybody - A Review
Module 2: Building a Search Engine
- Reading: Building a Search Engine - Introduction
- Video: Page Rank Overview
- Video: Worked Example: Page Rank - Spidering
- Video: Worked Example: Page Rank - Computation
- Video: Worked Example: Page Rank - Visualization
- Video: Office Hours Detroit, Michigan
- Video: Interview: Anil Jain - Image Processing
- Reading: Peer Graded Assignment - Instructor Input
- Graded: Peer Grade: Page Rank
Module 3: Exploring Data Sources (Project)
- Reading: Identifying Your Data Source - Introduction
- Reading: List of Data Sources (Instructional Staff Curated)
- Discussion Prompt: Identifying a Data Source
- Video: Dr. Chuck's New Kitten - Sakaiger
- Video: Interview: Bruce Schneier - The Security Mindset
Module 4: Spidering and Modeling Email Data
- Reading: Spidering and Modeling Email Data - Introduction
- Video: Gmane Introduction
- Video: Worked Example: Gmane / Mail - Retrieval
- Video: Worked Example: Gmane / Mail - Model
- Video: Office Hours Baltimore, MD
- Video: Interview: Bruce Schneier - Building Cryptographic Systems
- Graded: Loading and Modeling Mail Data
Module 5: Accessing New Data Sources (Project)
- Reading: Accessing New Data Sources - Introduction
- Discussion Prompt: Analyzing a Data Source
- Video: Office Hours: Dr. Chuck Pretends to be Anthony Bourdain
Module 6: Visualizing Email Data
- Reading: Visualizing Email Data
- Video: Worked Example: Gmane / Mail - Visualization
- Video: Office Hours, Montreal, Canada
- Video: Interview: Nathaniel Borenstein - The Father of MIME
- Graded: Visualizing Email Data
Module 7: Visualizing New Data Sources (Project)
- Reading: Visualizing new Data Sources - Introduction
- Discussion Prompt: Data Analysis and Visualization
- Video: Office Hours - Dr. Chuck's Office - Ann Arbor, Michigan
- Video: Video: Steve Jobs, NeXT and the Internet
- Reading: Post-Course Survey
- Reading: A special reason to celebrate your success
Grading Policy
Your course grade is based on completing the Python for Everybody - A Review graded assignment. There are also optional assignments available to those who are interested in earning an honors distinction in the course.
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Beginner Level
No prior experience required
