The basics of linear algebra and differential equations, with an emphasis on general physical and
engineering applications. Aimed at students who need the material for future coursework but do not
need as much depth and rigor as provided by MATH240/MATH461 and MATH246.
a C- or better in MATH 141
Introduction to effective and intuitive visual representations of data, including customizing graphics, plotting arrays, statistical graphics, and representing time series.
An introduction to data science i.e., the end-to-end process of going from unstructured, messy data to knowledge and actionable insights. Provides a broad overview of several topics including statistical data analysis, basic data mining and machine learning algorithms, large-scale data management, cloud computing, and information visualization.
Introduction to basic discrete mathematical and linear algebraic structures and use of these mathematical structures to solve programming problems. Logic, set theory, formal proof methodology, functions, and basic linear algebra.
DATA110 or DATA120; and MATH141.
Course dedicated to the study of ethical issues associated with data science, including data collections, gathering existing data, ethical use of data, data analysis with teams, repeatability and reproducibility of data analysis, and academic and scientific integrity.
STAT100, MATH135, or any 400-level STAT course.