Data Science, Analytics and Engineering (Bayesian Machine Learning), MS

This concentration in Bayesian machine learning within the MS program in data science, analytics and engineering is offered in partnership with the School of Mathematical and Statistical Sciences. With its programs in statistics, applied mathematics and theoretical mathematics, the school is distinctly positioned to enable students to understand the statistical, probability and mathematical bases for the technical tools and emerging concepts in statistical and probabilistic machine learning and data science. The school also supports students' ability to collect, maintain, analyze, model and decide based on heterogeneous, time-dependent, noisy, biased, hierarchical and potentially large data sets. Bayesian thinking is particularly suited to addressing the difficult issues associated with these high-dimension complex modeling challenges. Bayesian learning, decision-making and computation have made a significant impact on many areas of data science. Hierarchical modeling, time series analysis, ensemble modeling, spatial modeling and causal modeling are among the various areas of expertise covered by this program. Students will be able to apply these tools in a variety of domains such as engineering, physics, biology, social sciences, economics and finance. More details: https://degrees.apps.asu.edu/masters-phd/major/ASU00/ESDSEBMLMS/data-science-analytics-and-engineering-bayesian-machine-learning-ms