CS 105


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Computer Science 105
Introduction to Databases and Data Mining


April 30
Office hours for the week of May 2:
  • Tuesday, 4-5 p.m.: Baichuan, EMA 302
  • Thursday, 10 a.m.-noon: Dr. Sullivan, PSY 228D
  • Thursday, 4-6 p.m., Nabeel, EMA 302

You can pick up quiz 3 from Baichuan during his office hours or at the final exam.

The final exam will be held on Saturday, May 7, from 12:30-2:30 p.m. in SCI 109.

Additional information about the exam is available here.

January 28
The announcements are now being posted on Blackboard.

January 20
Please complete Lab 0 ASAP.

If you did not receive a copy of the lecture notes and syllabus in lecture today, there are PDF versions available using the lectures link in the left-hand navigation bar.

The first lecture of the semester will be held on Wednesday, January 20, from 1-2 p.m. in CAS 211. Labs will not meet during the first week of class.

The key details of the course are given below. For more information contact Dr. Sullivan.

Please check this page regularly throughout the semester for announcements and course materials.

Course Information

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.

Prerequisites: none

David G. Sullivan, Ph.D.
Senior Lecturer on Computer Science
see the staff page for contact info. and office hours

MWF, 1-2 p.m., CAS 211

A2: Thursdays, 9-10 a.m.
A3: Thursdays, 10-11 a.m.
A4: Thursdays, 11 a.m.-12 p.m.
A5: Thursdays, 12 p.m.-1 p.m.
Labs are held in the CS teaching lab, EMA 304.

  • Nine problem sets
  • A final project, which will involve using the techniques covered in the course to organize and analyze a collection of data that interests you, to draw conclusions based on your analysis, and to present your results in a clear and compelling way
  • Three closed-book quizzes
  • Closed-book final exam
  • Attendance at and participation in both the lectures and labs

  • Policy on collaboration and academic honesty
  • Lateness: There will be a 10% deduction for homework that is up to 24 hours late. We will not accept any homework that is more than 24 hours late. Plan your time carefully, and don't wait until the last minute to begin an assignment. Starting early will give you ample time to ask questions and obtain assistance from members of the course staff.
  • Determining the final grade:
    • attendance/participation: 10%
    • assignments: 30%
    • final project: 10%
    • quizzes: 20%
    • final exam: 30%
  • The final exam will replace your lowest assignment grade if doing so helps your final grade. The final exam will also replace your lowest quiz grade if doing so helps your final grade.
  • Extensions and makeup quizzes/exams will only be given in documented cases of serious illness or other emergencies.
  • You cannot redo or complete extra work to improve your grade.
  • Incompletes will not be given.

We will provide lecture notes that fully cover all of the material you are expected to learn as part of the course. The following textbooks are optional: They will be available for purchase at Barnes & Noble. In addition, we will suggest optional readings for the other topics of the course as we cover them.