DATA- Data Science
DATA 210 Introduction to Data Science (3)
Prerequisite: COSC-110, CIV-110, and either second-year standing or 28 completed credits. An introduction to concepts, tools, and techniques in data science including data acquisition, cleaning, analysis, modeling, and visualization. No prior familiarity with data science is assumed. (CTN)
DATA 310 Data Visualization (3)
Prerequisite: Second-year standing. Studies principles of effective visualization based on insights from many disciplines, including cartography, psychology, cognitive science, and graphic design. Students will learn to analyze visualizations based on these principles and apply the principles to create effective visualizations of their own. (CTN)
DATA 440 Applied Machine Learning (3)
Prerequisites: MATH-131, COSC-110. The course focuses on the regression, classification, and clustering tasks with the scikit-learn machine learning library in Python. The basic data structures used in machine learning such as numpy arrays and pandas data frames will be introduced in the beginning of the course. Students will spend a significant amount of time out of class designing, writing, collaborating on, and debugging Python programs.