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Data Science Course Offerings

DSC 205 Introduction to Data Science

3 credits

This is an introductory course for the Data Science major.  Data Science is a study of information, what it represents and how it can be used as a valuable resource for answering questions and forming strategies.  Student will be introduced to several software tools used in data science and learn how to formulate hypotheses concerning data, analyze data and report results.  The R programming language will be introduced.  Pre-requisites:  CSC 116 and MAT 215.  Spring

DSC 305 Data Analysis and Visualization

3 credits

This course will introduce students to the field by covering trending modeling, analysis and visualization techniques in the field of data science.  It will emphasize practical challenges involving complex real-world data and include several case studies and hands-on work with the R programming language.  Prerequisites:  DSC 205 or MAT 215.  Fall

DSC 306 Data Mining

3 credits

This course serves as an introduction to data mining for students.  Students will learn about many commonly used methods for predictive and descriptive analytics tasks.  They will also learn to assess the methods’ predictive and practical utility.  Pre-requisites:  CSC 208 and DSC 205, or DSC 305.  Spring

DSC 405 Web Analytics and Mining

3 credits

This course covers the areas of web analytics, text mining, web mining, and practical application domains.  Web analytics studies the metrics of web sites. Google analytics is used for collection of web site data and doing the analysis.  Text mining covers the analysis of text including content extraction, string matching, clustering, classification, and recommendation systems.  Web crawlers, social web and game metrics and the Internet of Things (IoT) will be discussed.  Pre-requisite:  DSC 306.  Fall

DSC 406 Machine Learning

3 credits

Machine learning is the science of getting computers to act without being explicitly programmed.  This course is designed to give the student a thorough grounding in the methodologies, technologies, mathematics and algorithms currently needed by data science professionals to build data products using machine learning.  Pre-requisite:  DSC 306.  Spring