CSIS - 320. Machine Learning

(2 hours lecture, 2 hours laboratory)
3 credit(s)
Machine learning is the subfield of artificial intelligence that uses data mining and statistical pattern recognition to “learn” algorithms to classify data, make predictions and solve data intense problems. Topics include: Supervised learning using regression, support vector machines, and neural networks; Unsupervised learning including clustering, dimensionality reduction, and recommender systems. Students will engage in hands-on activities to design and implement learning algorithms and systems for solving problems in areas such as robotics, text understanding, computer vision, medical informatics, database mining, and other areas. Computer use fee.

Prerequisite(s): CSIS 210 , and (MATH 110 or QBUS 110 )
Attribute: ARTS, DASC