IE5561
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IE 5561 - Analytics and Data-Driven Decision Making (4 Cr.) Online may be available
Industrial and Systems Engineering (11138)
TIOT - College of Science and Engineering
Course description
Hands-on experience with modern methods for analytics and data-driven decision making. Methodologies such as linear and integer optimization and supervised and unsupervised learning will be brought together to address problems in a variety of areas such as healthcare, agriculture, sports, energy, and finance. Students will learn how to manipulate data, build and solve models, and interpret and visualize results using a high-level, dynamic programming language.
Prerequisites: IE 3521 or equivalent; IE 3011 or IE 5531 or equivalent; proficiency with a programming language such as R, Python, or C.
Prerequisites: IE 3521 or equivalent; IE 3011 or IE 5531 or equivalent; proficiency with a programming language such as R, Python, or C.
Minimum credits
4
Maximum credits
4
Is this course repeatable?
No
Grading basis
OPT - Student Option
Lecture
Fulfills the writing intensive requirement?
No
Typically offered term(s)
Every Spring