Introduction to Databases and Data Mining
The first lecture for the semester will be held on September 5 in CAS 211. There are no labs on September 5.
- 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.
- David G. Sullivan, Ph.D., Master Lecturer
(see the staff page for contact information and office hours)
- MWF, 1:25-2:15 pm, CAS 211
- All students must attend the one-hour lab session for which they are enrolled.
- 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%)
- Preparation and participation (10%)
- Course Materials
Textbook: There is no required textbook for the course. We will provide detailed lecture notes and optional supplemental readings.
In-class software: We will be using the Top Hat platform for in-class activities and attendance. More detail will be provided in lecture.