CIS 3813 - Advanced Data Science

Credits: 3 Spring, Even

The objective of this course is to introduce students to advanced data science concepts with a particular emphasis on practical applications of machine learning. Students will be exposed to a range of model based and algorithmic machine learning methods including linear regression, decision trees, neural networks and deep learning, support vector machines, classification trees, Naive Bayes, and random forests. The course will cover the process of building models including data collection, feature creation, algorithms, and evaluation. Students will gain hands-on experience with the Python SciKit machine learning library. Additional fee required.

Prerequisites: CIS 3803