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 & MANIPULATION (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 3900 DATA SCIENCE INTERNSHIP (1)
Internships provide opportunities for well-qualified, upper-division students to work in a professional setting and gain valuable experience, while assisting a host agency with its mission. These can be found locally or in other places and can be with a government agency, non-profit organization, or private enterprise. Students may take up to three times for an DSC elective.
Prerequisite: none
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: none
Corequisite: DSC 3100 or permission of the instructor
Offered: as needed

DSC 4850 SPECIAL TOPICS (1-4)
Formal courses given infrequently to explore in depth a comparatively narrow subject that me be topical or of special interest.
Prerequisite: permission of the department chair
Offered: as needed

DSC 4990 INDEPENDENT STUDY IN DATA SCIENCE (1-4)
An opportunity for a well-qualified, upper-division student to engage in special research in his/her major.
Prerequisite: Requires approval by the faculty advisor, the supervising professor, the department chair, and the college dean before approval by Provost. Credits to be determined.
Offered: as needed