Comprehensive introduction to predictive modeling, a cornerstone of data science and machine learning. Learn the fundamental concepts, techniques, and tools used to build models while emphasizing both theoretical understanding and …
This course covers fundamentals of data mining and machine learning within a common statistical framework. Topics include regression, classification, clustering, resampling, regularization, tree-based methods, ensembles, boosting, and Support Vector Machines. …
Bayesian inferential methods provide a foundation for machine learning under conditions of uncertainty. Bayesian machine learning techniques can help us to more effectively address the limits to our understanding of …
This course introduces first-year graduate students in the humanities and social sciences to the knowledge and skills fundamental to success in graduate school. Particular topics vary.
A graduate-level course on deep learning fundamentals and applications with emphasis on their broad applicability to problems across a range of disciplines. Topics include regularization, optimization, convolutional networks, sequence modeling, …
This course presents the simplest economic models explaining how individuals and organizations respond to changes in their circumstances and how they interact in markets, and it applies these models to …
The first part of a two-semester sequence in research methods and tools used to evaluate public policies. This course reviews basic mathematics and statistics used by policy analysts, and introduces …
Introduces fundamental concepts of computation, data structures, algorithms, & databases, focusing on their role in data science. Covers both theoretical studies & hands-on learning activities. Includes basic data structures, advanced …
The purpose of this course is to develop the student's ability to define and solve public problems. Subsidiary objectives of the course are to help the student to integrate the …
Covers the fundamentals of probability and stochastic processes. Students will become conversant in the tools of probability, clearly describing and implementing concepts related to random variables, properties of probability, distributions, …