This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Data Science is an interdisciplinary undergraduate program at SFU involving coursework in four different areas: Statistics, Computing Science, Mathematics, and Business. The program was designed in ...

Data management and data science are interrelated disciplines that are central to the modern digital landscape. At the core of their contributions lies the management, processing and analysis of large ...

Offered: Winter (TTh 9:30-10:50 a.m.) and Spring (TTh 12:30-1:50 p.m.) Foundations of Data Science will cover the fundamentals of data science and the context within which this field operates. This ...

Data engineering and data science are complementary disciplines that have come to define modern approaches to managing, processing, and extracting value from vast and complex data sets. Data ...

Positron is Posit's new, free IDE for data science. Users can work with Python and R. It explicitly does not replace RStudio. A central feature of Positron is the Variable & Data Frame Explorer. It ...

Editor’s note: This is part of a series of stories featuring master’s degree programs at the University of Chicago. Bradley Stoller knew the University of Chicago was an ideal fit to pursue a master’s ...