CIS 3803 - Introduction to Data Science

Credits: 3 Fall

The objective of this course is to introduce the student to fundamental data science concepts, methods, processes and technologies. The course will cover processes and tools for collecting, cleaning, sharing, analyzing and visualizing data. Students will become familiar with methods for statistical inference, regression analysis, and supervised and unsupervised data mining. Specific data mining methods include: k-nearest neighbors and naive Bayes, decision trees, and clustering.

Prerequisites: CIS 2713 and MATH 2003 all with grade “C” or better. MATH 2003 can be concurrent.