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Offers students a capstone opportunity to practice data science skills learned in previous courses and to build a portfolio. Students practice visualization, data wrangling, and machine learning skills by applying them to semester-long term projects on real-world data. Students may either propose their own projects or choose from a selection of industry options. Emphasizes the overall data science process, including identification of the scientific problem, selection of appropriate machine learning methods, and visualization and communication of results. Lectures may include additional topics, including visualization, communication, and data science ethics.

Prerequisite(s): (CS 5800 with a minimum grade of C- or EECE 7205 with a minimum grade of C- ); DS 5110 with a minimum grade of C- ; DS 5220 with a minimum grade of C- ; DS 5230 with a minimum grade of C-