Nov 03, 2024  
Undergraduate Catalog 2022-2023 
    
Undergraduate Catalog 2022-2023 [ARCHIVED CATALOG]

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CSC 260 - Analysis of Algorithms


Prerequisite(s): CSC 161  and MAT 150  
This course is a rigorous introduction to analytical methods and algorithms. Included are classic problems (e.g., classification, prediction, greedy vs. non-greedy algorithms, and algorithm design strategies). Student learns how to work with data visualizations, Exploratory data Analysis (EDA), Decision Trees, Neural networks (CNN and RNN), Random Forest (RF), logistic regression, backwards step-wise regressions, Binomial distributions and Poisson distribution for advanced queuing algorithm analysis. The focus is both theory as well as hands-on experiences with an Integrated Development Environment (IDE) using the “R” libraries. Even Spring

Hours: 3



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