Computer Science 105
Introduction to Databases and Data Mining
- January 21
- 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 fall semester will be held on Wednesday,
January 21 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, consult the syllabus
or contact Dr. Sullivan.
Please check this page regularly throughout the semester for announcements
and course materials.
- 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
- 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.