Course name: INFSCI 2160 Data Mining (Spring 2017)
Instructor: Dr. Yu-Ru Lin <yurulin at pitt.edu>
office hours: TBA (by appointment)
Piazza Class Link: https://piazza.com/pitt/spring2017/infsci2160/home
TAs: see Piazza
Class Meeting Time: Wednesday 3:00pm--5:50pm
Location: IS Bldg 405
This course focuses on both concepts and practice. We will introduce (a) the core data mining concepts and (b) practical skills for applying data mining techniques to solve real-world problems.
Students are expected to be familiar with the basics of Linear Algebra, Probability and Statistics, and should be comfortable with programming. We will use R as the primary analysis platform, and hence familiarity of R is preferred.
Attendance is mandatory and will be recorded. Arriving late and leaving early without permission will affect your grade. If you must be absent please contact me in advance. Three or more absences will result in automatic failure of the course except in extraordinary circumstances.
Grades are based on three major activities listed below. Assignments are due as scheduled, and grades on late work will be decreased by 10% per day late. See the assignment page for more details.
This course will use materials from several recommended books listed below. The first and the third book are available online over Pitt network. The second book is available online. There will be reading assignments over the course of the semester. Links to the electronic copies of these readings will be provided. There are also other recommended books for further reading and for learning R.
See the list of recommended readings.
See the course schedule page.
See the university policies page.