Academic Calendar 2023-2024

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MINE 272 Applied Data Science

MINE 272  Applied Data Science  Units: 4.50  

This course presents a comprehensive overview of the key elements of data science for engineers. Topics include data cleaning, organization and manipulation, data collection, visualization and noise filtering. Data analysis techniques including regression, decision trees, feature selection, clustering and classification are covered. Emphasis is on spatial analysis and visualization, as well as the analysis of time series. An introduction to advanced topics such as deep learning, big data management and analysis is provided. The focus is on the practical application of data science in the engineering context to make predictions and decisions based on the statistical inference of data.
(Lec: 3, Lab: 3, Tut: 0)

Requirements: Prerequisites: APSC 142 or APSC 143 or CISC 101 or MNTC 313, and CHEE 209 or STAT 263 or MECH 203 or MTHE 224 or ENPH 253 or permission of the department Corequisites: Exclusions: CISC 251, CMPE 251  
Offering Term: W  
CEAB Units:    
Mathematics 0  
Natural Sciences 0  
Complementary Studies 0  
Engineering Science 54  
Engineering Design 0  
Offering Faculty: Smith Engineering