Clinical Professor, School of Information
Using Databases with Python
What You'll Learn
- Use the Create, Read, Update, and Delete operations to manage databases
- Explain the basics of Object Oriented Python
- Understand how data is stored across multiple tables in a database
- Utilize the Google Maps API to visualize data
5 Modules
15 Hours
3 hrs per module (approx.)
Rating
About Using Databases with Python
This course will introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course will use SQLite3 as its database. We will also build web crawlers and multi-step data gathering and visualization processes. We will use the D3.js library to do basic data visualization. This course will cover Chapters 14-15 of the book “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-13 of the textbook and the first three courses in this specialization. This course covers Python 3.
Skills You'll Gain
- Database Design
- Python (Programming Language)
- SQLite
- SQL (Programming Language)
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 Using Databases with Python, a course that introduces you to SQL, database design, and database-driven data analysis using Python 3. You will learn how to store, retrieve, model, and visualize data using SQLite3, web data collection workflows, and basic data visualization techniques. This course, which is part of the Python for Everybody series, emphasizes practical skills for working with relational databases as part of multi-step data gathering and analysis projects.
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: Object-Oriented Python
- Video: Welcome to Using Databases with Python
- Reading: Help us learn more about you!
- Reading: Python Textbook
- Reading: Course Syllabus
- Video: Unicode Characters and Strings
- Reading: Notice for Auditing Learners: Assignment Submission
- Video: Windows 10: Installing Python and Writing A Program
- Video: Windows: Taking Screen Shots
- Video: Macintosh: Using Python and Writing A Program
- Video: Macintosh: Taking Screen Shots
- Video: Object Oriented Definitions and Terminology
- Video: Our First Class and Object
- Video: Object Life Cycle
- Video: Object Inheritance
- Video: Bonus: Interview - Software Engineering - Bertrand Meyer
- Video: Bonus: Office Hours - London
Module 2: Basic Structured Query Language
- Video: Relational Databases
- Video: Using Databases
- Video: Single Table CRUD
- Video: Worked Example: Counting Email in a Database
- Video: Bonus: Office Hours Zagreb, Croatia
- Video: Interview: Elizabeth Fong - The Early Years of SQL
Module 3: Data Models and Relational SQL
- Video: Designing a Data Model
- Video: Representing a Data Model in Tables
- Video: Inserting Relational Data
- Video: Reconstructing Data with JOIN
- Video: Worked Example: Tracks.py
- Video: Bonus: Office Hours Perth, Australia
- Video: Bonus Interview: Niklaus Wirth
- Video: Bonus: Office Hours Barcelona
Module 4: Many-to-Many Relationships in SQL
- Video: Many-to-Many Relationships
- Video: Worked Example: roster.py
- Video: Bonus: Office Hours Mexico, City
- Video: Bonus Interview: Andrew Tannenbaum - Minix
Module 5: Databases and Visualization
- Video: Geocoding
- Video: Worked Example: Geodata
- Reading: Peer Graded Assignment - Instructor Input
- Video: Bonus: Office Hours - Amsterdam
- Video: Bonus Interview: Richard Stallman - Free Software Foundation
- Video: Bonus Interview: Brian Behlendorf - Apache Foundation
- Reading: Please Rate this Course on Class-Central
- Reading: Post-Course Survey
Grading Policy
Learners are evaluated through quizzes, hands-on database assignments, and a peer-graded visualization project. The course grade is based on five quizzes worth 50% (10% each), four activities worth 40% (10% each), and a peer-graded assignment worth 10%.
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
