Coming Fall 2017
Topics include: version control, scripting languages, relational and non-relational databases, proper use of data structures, introduction to data science work flows, introduction to project management, and applications.
Topics include: platforms for scalable computing including Map Reduce, Hadoop, Spark, and HPC, setting up computing in cloud, and modern data science work flows.
Topics include: data visualization, data summaries, missing data, study design, communicating results, linear regression, ANOVA, decision trees, random forests, support vector machines, model diagnostics, cross validation, bootstrap, reproducible research skills. Hands on projects.
Individual project to further studies in data science research and allow students to engage in an established external entrepreneurship and/or policy environment.
Presentations from UTK/ORNL researchers, local industry partners, and others as related to data science, entrepreneurship, and policy.