Databases and Data Mining
The first lecture for the fall semester will be held on September 7 in LSE B01.
Most of the course materials are available on this site using the links in the navigation bar.
The course announcements are found on Blackboard.
- Course description
- Databases are everywhere. Retailers use data about customers and purchases to increase profits. Researchers analyze genomic data to find treatments for diseases. Online music and video services use data mining to deliver customized recommendations. How does all this work? CS 105 examines how data is organized, analyzed, and displayed. Topics include relational databases and the SQL query language, the writing of programs to analyze data, the principles of data visualization, and data-mining techniques for discovering patterns in data. At the end of the course, students apply the topics they have learned to a collection of data that interests them. This course is a Math/CS divisional studies course.
- David G. Sullivan, Ph.D., Senior Lecturer
(see the staff page for contact information and office hours)
- MWF, 1-2, LSE B01
- All students must attend a one-hour lab session in the CS teaching lab, EMA 304.
- Nine problem sets (30% of the final grade)
- A final project (completed by teams of three students) (10%)
- Exams: three quizzes (20%) and a final exam (30%)
- Attendance and participation (10%)
- Textbooks (optional)
Database Concepts, 7th edition by David M. Kroenke and David J. Auer (Prentice Hall, 2015)
Python Programming: An Introduction to Computer Science, second edition by John Zelle (Franklin Beedle, 2010). Note: The first edition of this book is not an acceptable substitute.