3 courses with the subject DSCI, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DSCI 201INTRODUCTION TO DATA SCIENCE. An introduction to methods and
tools used to analyze and understand data. Topics include common toolkits for data analysis and visualization. Students engage in hands-on analysis of real-world data sets and discuss social issues related to data analysis. Prerequisites: Either Computer Science 111, or both Computer Science 141 and either Computer Science 155 or Mathematics 125. Corequisite: Statistics 131 or Psychology 201. Spring semester, three hours.
DSCI 431INTRODUCTION TO BIG DATA. The objective of this course is to introduce
key concepts and technologies of big data management. This course covers big data characteristics, storage, and processing. Students learn how to use multiple big data technologies, such as stream processing, in-memory databases, Hadoop MapReduce, NoSQL, and NewSQL systems. Prerequisites: Computer Science 220 and 244. Alternate years, spring semester, three hours.
DSCI 450APPLIED MODELING AND VISUALIZATION. The capstone course in
data science. Students apply modeling and visualization techniques to a large project, giving presentations about their results and writing a report. Legal and ethical issues in data science are examined. This course is designated Writing Intensive (WI), Speaking Intensive (SI), and Information Literacy (IL). Prerequisites: Mathematics 213 or Statistics 331; Mathematics 214 or 222; Data Science 201; Computer Science 222, 244; Data Science 431 or Computer Science 435. Spring semester, three hours.
