This is the second course on advanced methods and tools for Statistical Computing. This
course will introduce classical methods, including the EM algorithm and its variants. It also
will cover basic convex optimization theory and advanced computing tools and techniques for
big data and learning algorithms. Prereq: Math 233; a course in linear algebra at level of Math 309 or Math 429; multivariable-calculus-based probability and mathematical statistics (Math/SDS 493-494 or Math/SDS 3211/4211); Experience with a high-level programming language like R, Python, C++, etc.
Course Attributes:
