Prerequisite:
None. A basic understanding of probability and statistics (probability distributions, conditional probability, hypothesis tests) and elementary calculus will be assumed. Computing experience is a definite plus, but no programming will be required.
Textbook:
Required:Introduction to Data Mining,
P.-N. Tan, M. Steinbach and V. Kumar, Addison Wesley, 2005.
Readings from other sources may be made available in class.
Course description:
In this course you will learn the basics of data mining and knowledge discovery. Our focus will be on the algorithms that are commonly used to build predictive models and find relevant patterns in data. We will look at different ways of applying these techniques to real-world problems from domains such as marketing, health care, bioinformatics, and information retrieval. We will also discuss the different steps in the knowledge discovery process, particularly data cleansing and transformation.
Grading:
50% Homeworks
50% Final exam
The score - grade mapping will be determined by the instructor at the end of the course. The usual 90/80/70 cutoffs will be used as a baseline, but may be adjusted.
Attendance:
Attendance is not required but is strongly encouraged. No slides or other summary material will be made available, so class attendance is essential for learning the material. You will be responsible for knowing everything discussed in class, and everything that is posted to the ICON site.
Late assignments:
All assignments are expected to be turned in at the beginning of class on their assigned due date. Late assignments will be penalized 10% of the available points, and another 10% will be deducted for every 24-hour period after the original due date. In general, your best strategy is to turn in whatever you have finished when the assignment is due.
Class Policies:
Students are allowed to collaborate freely on homework assignments, but you should write the final submission independently to make sure you understand each step. Identical homework submissions or exam answers will be considered evidence of academic dishonesty.
Exam scores will be based on individual work. No discussion or outside sources are allowed during the exam.
Any act of academic dishonesty will result in a grade of zero for the assignment or exam. A second violation by the same student will result in a grade of F for the course. Appeals will be handled according to the honor code of the Tippie College of Business, found at http://tippie.uiowa.edu/honor-code.cfm.
All class policies on matters such as requirements, grading, and sanctions for academic dishonesty are governed by the College of Business. Students wishing to add or drop this course after the official deadline must receive the approval of the Dean of the College of Business.
The University will not tolerate sexual harassment, nor will it tolerate unwelcomed behavior of a sexual nature toward members of the University community when that behavior creates an intimidating or hostile environment for employment, education, on-campus living, or participation in a University activity. Incidents of sexual harassment should be reported immediately. To review the complete policy, please see https://opsmanual.uiowa.edu/students/sexual-misconduct-datingdomestic-violence-or-stalking-involving-students. For assistance in making a report, contact the Office of the Sexual Misconduct Response Coordinator at 319-335-6200 or see http://osmrc.uiowa.edu.
The University of Iowa is committed to providing an educational experience that is accessible to all students. A student may request academic accommodations for a disability (which includes but is not limited to mental health, attention, learning, vision, and physical or health-related conditions). A student seeking academic accommodations should first register with Student Disability Services (SDS) and then meet with the course instructor privately in the instructor's office to make particular arrangements. Reasonable accommodations are established through an interactive process among the student, instructor, and SDS. For more information, see http://sds.studentlife.uiowa.edu. Please make any necessary arrangements during the first week of class.
Content:
Time permitting, the following topics will be discussed. Other specialized topics may be added depending on the interests of the students and the whims of the instructor.