Prerequisite:
MSCI:9100 or MBA:8150 Business Analytics
Required Textbooks:
Data Science for Business: What you need to know about data mining and data-analytic thinking, F. Provost and T. Fawcett. O'Reilly, 2013.
Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery, G. Williams. Springer, 2011.
Readings from other sources may be made available in class.
Required Software:
Each student will be expected to bring a laptop computer to each class meeting. Any modern operating systems should be fine, although I will be using Windows for examples. The following software will need to be installed:
Course description:
In this course you will learn the basics of data science, particularly data mining, as applied to business problems. Our focus will be on the process of turning raw data into intelligent decisions, and on the algorithms that are commonly used to build predictive models and find relevant patterns in data. Class sessions will be a mixture of conceptual material and hands-on practice.
Time permitting, we will explore the following topics:
Grading:
35% Homeworks
30% Midterm
30% Final exam
5% Class participation
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. You will be responsible for knowing everything that happens in class, and everything that is posted to the ICON site. If you have to miss a class, you should notify the instructor ahead of time and obtain notes from a classmate afterward.
Late assignments:
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 will be considered evidence of academic dishonesty and prosecuted as such.
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/undergraduate/honorcode/.
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. Details of the University policy of cross enrollments may be found at http://www.uiowa.edu/~provost/deos/crossenroll.doc
The Tippie College of Business and the University of Iowa are committed to providing students with an environment free from sexual harassment. If you feel that you are being or have been harassed or you are not sure what constitutes sexual harassment, you are encouraged to visit the University website, http://www.sexualharassment.uiowa.edu/index.php, and to seek assistance from department chairs, the Dean's Office, the University Ombuds Office, or the Office of Equal Opportunity and Diversity.
In order to participate in this class, it may be necessary to reveal to other students the names of students who are enrolled in this course. If you do not want your name revealed to other students enrolled in this course, please contact me in writing by the end of the first week of classes.
If any member of this class feels that he or she has a disability and needs special accomodations of any nature, I will work with you to provide reasonable accomodations to ensure that you have a fair opportunity to perform in this class. Please advise me of such disability and the desired accomodation during the first week of the class.