DSCI 100  First Year Seminar in Data Science  Credit: 1 (0-0-1)

Course Description: Introduction to problems and techniques in data science.
Prerequisite: None.
Registration Information: Freshman or sophomore Data Science majors only.
Term Offered: Fall.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 235  Data Wrangling  Credits: 2 (1-0-1)

Course Description: Introduce tools and techniques for handling, cleaning, extracting, and organizing data.
Prerequisite: None.
Registration Information: Must have concurrent registration in CS 220. Must register for lecture and recitation. This is a partial semester course.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 320  Optimization Methods in Data Science  Credits: 3 (3-0-0)

Course Description: Linear and non-linear programming, convex sets and functions, convex and non-convex optimization problems, duality, Newton's methods, barrier methods, linear equality and inequality constraints. Emphasis on computation methods and programming.
Prerequisite: (CS 163 or CS 164) and (MATH 151 and MATH 261) and (DSCI 369 or MATH 369).
Term Offered: Fall.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 335  Inferential Reasoning in Data Analysis  Credits: 3 (3-0-0)

Course Description: Sources of data collection errors and uncertainties, type of studies, interaction versus confounding, fair use of data, confidentiality and disclosure.
Prerequisite: CO 300 or CO 301B or CO 302 or JTC 300.
Term Offered: Spring.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 336  Data Graphics and Visualization  Credit: 1 (1-0-0)

Course Description: Data graphics and visualization techniques for data science.
Prerequisite: STAT 342.
Registration Information: This is a partial semester course.
Term Offered: Spring.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 369  Linear Algebra for Data Science  Credits: 4 (4-0-0)

Course Description: Techniques in linear algebra related to data science. Matrices, bases, subspaces, linear independence, dimension, change of basis, projections, linear systems of equations, least squares, matrix factorizations. Singular value decomposition, angles between subspaces.
Prerequisite: MATH 124 and MATH 126.
Term Offered: Fall.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 445  Statistical Machine Learning  Credits: 3 (3-0-0)

Course Description: Algorithms and statistical methods for regression, classification, and clustering; hands-on experience in analyzing data and running machine learning experiments.
Prerequisite: DSCI 320 and DSCI 369 and STAT 341.
Registration Information: Credit allowed for only one of the following: CS 445, CS 480A3, or DSCI 445.
Term Offered: Fall.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 473  Introduction to Geometric Data Analysis  Credits: 2 (2-0-0)

Course Description: Geometric techniques for analyzing high-dimensional and complex data. Techniques for data reduction and analysis.
Prerequisite: DSCI 369.
Registration Information: This is a partial semester course.
Term Offered: Fall.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 475  Topological Data Analysis  Credits: 2 (2-0-0)

Course Description: Topological techniques for analyzing high-dimensional or complex data. Topics include clustering, dendrograms, a visual introduction to topology, data modeling and visualization, and selected topics from nonlinear dimensionality reduction, graph-based models of data, Reeb graphs, multi-scale approaches to data, and persistent homology.
Prerequisite: DSCI 473.
Registration Information: This is a partial semester course.
Term Offered: Spring.
Grade Mode: Traditional.
Special Course Fee: No.

DSCI 478  Capstone Group Project in Data Science  Credits: 4 (0-0-8)

Course Description: Group-project-based capstone, in which small groups of students from each Data Science degree concentration work collectively on a problem in data science.
Prerequisite: DSCI 445.
Restriction: Must be a: Undergraduate.
Registration Information: Senior standing only.
Term Offered: Spring.
Grade Mode: Traditional.
Special Course Fee: No.