EECE.5440 Computational Data-Driven Modeling I
Id: 040889
Credits: 3-3
Description
Computational Data-Driven Modeling (CDM) I is the first in a sequence of two courses designed to introduce the student to basics skills in exploratory data analysis and data-driven computational modeling using foundational concepts drawn from linear algebra, probability, statistics, random processes, time-series analysis and dynamical systems. In CDM-1 students will learn to apply regression and classification algorithms on multivariate data and assess performance of these models. An interactive project-driven approach is taken using the Python programming platform and its associated open-source libraries for statistical modeling, data analysis and machine-learning. A review of the tools and techniques from probability and statistics will be undertaken.
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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.