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Jan 15, 2025
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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. When Offered: Even Spring
Hours: 3
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