Listed in: Computer Science, as COSC-254
Matteo Riondato (Section 01)
This course is an introduction to data mining, the area of computer science that deals with the development of efficient and accurate algorithms for extracting information from data. Topics may include: mining data streams and time series, the MapReduce/Spark model and large scale data analysis, significant patterns extraction, web and social networks analysis, recommendation systems, sampling and hypothesis testing, and dimensionality reduction. We will use interactive data analysis notebooks and large-scale data processing systems to implement and test data mining algorithms.
Requisite: COSC 211. Limited to 50 students. Spring semester. Professor Riondato.
How to handle overenrollment: Priority to majors
Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: (none specified)
Course Materials