EECE.5470 Computational Data-Driven Modeling II

Id: 040890 Credits: 3-3

Description

Computational Data-Driven Modeling (CDM) II is the second in a sequence of two courses designed to introduce the student to skills in exploratory data analysis and data-driven computational modeling. CDM-II extends the students' knowledge on application of regression and classification algorithms in CDM-1 to more complex structures such as Bayesian networks and Hidden-Markov models. The focus will be on time-varying data using time-series and stat-space models such as Kalman filters, Markov Processes and Particle filters for prediction and forecasting. The application of neural networks and deep-learning will be discussed. Students will undertake case-studies in data analytics with collaboration from professionals in industry.

Prerequisites

EECE.5440 Computational Data-Driven Modeling I.

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Course prerequisites/corequisites are determined by the faculty and approved by the curriculum committees. Students are required to fulfill these requirements prior to enrollment. For courses offered through online or GPS delivery, students are responsible for confirming with the instructor or department that all enrollment requirements have been satisfied before registering.