Data Science (DSC) Courses

DSC 2100 INTRODUCTION TO DATA SCIENCE (3)
Introduction to foundational concepts and technologies used to work with, manipulate, and analyze data. Students will derive information and draw conclusions with large data sets through an introduction to R and Python.
Prerequisites: none
Offered: as needed  

DSC 3100 DATA VISUALIZATION & MANAIPULATION (3)
An introduction to data visualization and manipulation. Students will learn the importance of actionable dashboards enabling data-driven decisions using Qlik, Tableau, and/or Power BI. Students will also focus on the loading, manipulating, processing, cleaning, aggregating, and grouping of data through Python. Prior Python experience is necessary.
Prerequisites: CSC 2010 and DSC 2100 or permission of the instructor
Offered: as needed  

DSC 3500 INTRODUCTION TO MACHINE LEARNING MODELS (3)
An introduction to machine learning to determine what machine learning is and why it is used. Students will examine algorithms and systems that can learn without being explicitly programmed. Machine learning systems, machine learning involving regression, classification systems, training of linear models, closed-form solutions, support vector machines, and unsupervised learning techniques will be explored. This course is taught in Python.
Prerequisites: DSC 3100 or permission of the instructor
Offered: as needed  

DSC 4500 ETHICS IN MATHEMATICAL MODELING AND DATA SCIENCES (3)
An introduction exploring various ethical issues related to computing technology, mathematical sciences, and data science. Subjects include basic and advanced issues from social media privacy to implications of machine learning and artificial intelligence.
Prerequisites: DSC 3100 or permission of the instructor
Offered: as needed