Academic Calendar 2023-2024

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CMPE 333 Data Analytics

CMPE 333  Data Analytics  Units: 3.00  

Introduction to data analytics; data preparation; assessing performance; prediction methods such as decision trees, random forests, support vector machines, neural networks and rules; ensemble methods such as bagging and boosting; clustering techniques such as expectation-maximization, matrix decompositions, and biclustering; attribute selection.
(Lec: 3, Lab: 0, Tut: 0)

Requirements: PREREQ: APSC 142 or APSC 143, or programming experience recommended.  
Offering Term: W  
CEAB Units:    
Mathematics 10  
Natural Sciences 0  
Complementary Studies 0  
Engineering Science 14  
Engineering Design 12  
Offering Faculty: Faculty of Arts and Science