IS
555
Data Science for Organizations
End-to-end data science workflows using R, with a focus on strategy, team management, and real-world experience. Students will become thoughtful, detail-oriented, utility-focused data professionals who appreciate the grit required to deliver real-world, meaningful value through data assets.
Methods
Students will be able to assemble, store, manipulate, visualize, and refresh a real-world dataset that informs a meaningful problem space
Collaborate
Students will be able to collaborate in a team setting to effectively create, evaluate, maintain, and update an end-to-end machine learning model pipeline that produces value in the problem space
Evaluate
Students will be able to defend model choice in terms of algorithm, validity, performance, and practical relevance to both data-savvy and non-technical stakeholders
Ethics
Students will be able to identify (and be conversational about) sources of bias, performance issues, and ethical and regulatory considerations, and explain how these will affect stakeholders and others.