Spring 2021

Data Mining

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. Spring semester.  Assistant Professor Riondato.

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: Quantitative Reasoning. Students with documented disabilities who will require accommodations in this course should be in consultation with Accessibility Services and reach out to the faculty member as soon as possible to ensure that accommodations can be made in a timely manner.
COSC 254 - L/D

Section 01
M 12:30 PM - 01:50 PM ONLI ONLI
W 12:30 PM - 01:50 PM ONLI ONLI


2024-25: Not offered
Other years: Offered in Spring 2019, Spring 2021