Fall 2024 Course Syllabus
| Class Schedule | Course Project |
BELL 2286, 11:00am-12:15pm Tuesday & Thursday
| Instructor: | Xintao Wu |
| Office: | JBHT 516, (479) 575-6519 |
| Email: | xintaowu at uark dot edu |
| URL: | http://sail.uark.edu |
| Prerequisite: | (CSCE 31903 or CSCE 3193H3 or DASC 21003) or (CSCE 20104 and INEG 23303 and INEG 23104) or (CSCE 20104 and STAT 30133 and STAT 30043)) |
| Office Hours: | 10:00-11:00am Tuesday & Thursday |
Course Material:
Jiawei Han, Jian Pei, and Hanghang Tong. Data Mining: Concepts and Techniques, 4th edition, Morgan Kaufmann, 2022. ISBN: 978-0-12-811760-6
Charu C. Aggarwal, Data Mining, The Text Book. Springer (optional)
Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman. Mining of Massive Datasets., 2014 (optional)
Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Introduction to Data Mining, Addison Wesley, ISBN:0-321-32136-7 (optional)
Trevor Hastie, Robert Tibshirani, and Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2009. (optional)
Grading
Homework and Quiz 10% Term Project 30% Midterm 20% Final Exam 40%
Teaching Assistant
Bertrand Munihuzi Kalisa bmkalisa@uark.edu, office hours: 1:00-3:30pm Wednesday & Friday, JBHT 434
Course Description
Topics include data preprocessing; data warehousing and online analytical processing; data cube; mining frequent patterns, associations and correlations; supervised learning including decision tree induction, naïve Bayesian classification, support vector machine and K-nearest neighbor learning; unsupervised learning including K-means clustering and hierarchical clustering; outlier analysis; and data mining in cloud computing, social media, bioinformatics and healthcare applications.