INFO 3950 - Data Analytics for Information Science

Spring. 3 credits. Student option grading.

Prerequisite: INFO 2950 or equivalent, plus substantial comfort with python programming in Jupyter notebook. Note: This course may not be taken for credit after or concurrently with CS 3780 or ECE 4200.

P. Ginsparg.

This course will cover intermediate-level applications of data science, with focus on discovery, interpretation, and communication of meaningful patterns in data. Topics will include regression, classification, clustering, and forecasting, with an overview of machine learning algorithms and statistical inference.