To earn an MBA x Artificial Intelligence, students must complete the 16 credits of MBA core curriculum, corporate residency, and 12 credit hours from the Khoury College of Computer Sciences listed below. You will also complete 12 credits from a second business concentration of your choosing, and 15 elective credits of which 3 must be experiential in nature.
Required MBA x Artificial Intelligence Courses
Introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Topics include heuristic search and game trees, knowledge representation using predicate calculus, automated deduction and its applications, problem solving and planning, and introduction to machine learning. Required course work includes the creation of working programs that solve problems, reason logically, and/or improve their own performance using techniques presented in the course.
CS 5100 | 4 credits
Provides an introduction to the computational modeling of human language, the ongoing effort to create computer programs that can communicate with people in natural language, and current applications of the natural language field, such as automated document classification, intelligent query processing, and information extraction. Topics include computational models of grammar and automatic parsing, statistical language models and the analysis of large text corpuses, natural language semantics and programs that understand language, models of discourse structure, and language use by intelligent agents. Course work includes formal and mathematical analysis of language models, and implementation of working programs that analyze and interpret natural language text.
CS 6120 | 4 credits
Provides a broad look at a variety of techniques used in machine learning and data mining; and also examines issues associated with their use. Topics include algorithms for supervised learning including decision tree induction, artificial neural networks, instance-based learning, probabilistic methods, and support vector machines; unsupervised learning; and reinforcement learning. Also covers computational learning theory and other methods for analyzing and measuring the performance of learning algorithms. Coursework includes a programming term project.
CS 6140 | 4 credits
The curriculum is subject to change by D’Amore-McKim faculty. Please monitor for updates.