Overview
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Data mining involves analysis of large databases and discovery of trends and patterns. The volume of data is growing at a remarkable rate, particularly in the fields of science, engineering, medicine, marketing, and finance. Creative implementation of machine learning and data mining can provide significant advantages.
CONCENTRATION IN MACHINE LEARNING AND DATA MINING
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Core Course1 |
Semester |
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Select any four of the following: |
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ISE364 |
Introduction to Machine Learning |
Fall |
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ISE365 |
Applied Data Mining |
Fall, Spring |
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ISE364/467 |
Mining of Large Data Sets |
Fall |
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ISE2302 |
Optimization Models and Applications |
Fall, Spring |
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CSE326/426 |
Fundamentals of Machine Learning |
Spring |
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CSE347/447 |
Data Mining |
Fall |
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Total Credits |
12 |
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1Additional courses selected in consultation with the program adviser may fulfill program requirements. No more than 6 credits can be taken at the 200 and 300 level.
2During enrollment, preference is given to ISE undergraduates
MEM Faculty Point of Contact: Prof. Donald Rockwell (E-mail)