This course aims to bring students with different backgrounds in order to introduce the fundamentals of topological data analysis and time series applications with a number of hands-on and use-case examples in data science. The course will be one of the elective courses for students who plan to examine the shape of the data in their time series research in Statistics, Actuarial Sciences, Financial Mathematics, Scientific Computing, Mathematics.

This course provides students with  time series modeling, and Topological Data Analysis (TDA) that are recently used to examine the shape of the data in data science field . The topics include the fundamentals of many disparate fields such as algebraic topology, linear algebra, machine learning algorithms, statistics, and time series modeling in order to understand recent results in the TDA and time series field besides using the efficient software for the computation of things discussed in class, such as persistent homology. Real world cases will be presented throughout the course and students will get experience in data science platforms using Python or R programming language and High Performance Computing.