Applied Data Science Research

Catalog description

This is a project based data science research class, in which project teams identify a research project under the guidance of a domain expert professor. For enrollment, students should provide an abstract of their research plan and data science question that they will address in the course as well as potential datasets that will be used. The research is structured as a data analysis project including the 6 steps of developing a reproducible data science project, including 1: Define the ADS question, 2: Identify, locate, and/or generate the data 3: Exploratory data analysis 4: Statistical modeling and prediction 5: Synthesizing the results in the domain context 6: Creation of reproducible research, Including code, datasets, documentation and reports. During the course special topic lectures will include Ethics, Privacy, Openness, Security, Ethics. Value. The M section of DSCI 352 is for students focusing on Materials Data Science. Offered as DSCI 352 , DSCI 352M and DSCI 452 . Prereq: DSCI 351 or DSCI 351M or DSCI 451 .