DATA 260

An intermediate course on data analytics in Python. Students begin by developing the skill to obtain data from Web APIs and work collaboratively using version control; all projects in the course are based on web-obtained data. The first major topic of the course emphasizes an attention to time/space complexity through the lens of k-nearest neighbors algorithms and decision trees. The second major topic is intermediate time series analysis with ARIMA. The last portion of the course addresses the basic ideas behind optimization- and randomization-based approaches to classification and regression in high-dimensional settings where classical algorithms fail. Throughout the course, students learn the underlying probability and calculus principles behind the way basic data analytics algorithms work.

Offered spring semester

001819

CO24 - SCIMATH (Nat Sci and Math), INTD - DATA (Data Analytics DATA)