CS 562: Big Data Algorithms¶

Instructor:	Sunil Shende
Class Schedule:	M 6pm - 8:50pm in BSB 134 (Camden) and synchronous conferencing on Canvas (BigBlueButton)
Office:	308 Business & Science Building
Office Hours:	MW from 1:30pm to 2:30pm
Tel:	Campus extension 6122
Email:	shende AT camden DOT rutgers DOT edu

This course provides an introduction to algorithms and techniques for processing very large data sets, including both offline and streamed data. The focus is on developing a clear understanding of the mathematical basis for big data algorithms for data mining (similarity detection, clustering, association rules for frequent itemsets, link analysis) and machine learning (supervised and unsupervised learning models, regression, support vector machines etc.). Students will also work with Python-based libraries like pandas and scikit-learn to develop software for big data applications.

By way of preparation for the course, students are expected to be comfortable with basic discrete mathematics, probability theory, data structures, elementary algorithms and programming in a high-level language like Python or Java.

This class is supported by DataCamp, a learning platform for data science. We will be using some of their short, hands-on courses on PySpark and other topics relevant to the course where you learn through a combination of short expert videos and hands-on-the-keyboard exercises.