STAT 220 - Fundamentals of Data Science

A broad introduction to the fast-growing field of data science within the broader context of statistics, including Data Handling, Visualization, Reproducibility, Predictive Modeling, and Machine Learning. It will investigate the advantages and boundaries of traditional statistical inference, why traditional statistical inference techniques are sometimes not enough, and differences in rhetorical and philosophical models between the two. Ethical issues in analytics and related areas (big data, genomics, etc.) will be discussed throughout.

Some sections may be offered in a hybrid setting.

Prerequisites: Completion of the Essential Skill in Statistics. Additional skills in computer coding and/or spreadsheets are required.
Credit(s): 3