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Apr 19, 2024
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CSC 260 - Analysis of Algorithms
Prerequisite(s): MAT 215 with a grade of “C-” or better and CSC 150 with a grade of “C-” or better, or permission from the instructor.
This course is a rigorous introduction of algorithms covering Machine Learning (ML), Artificial Intelligence (AI) and quantitative methods. It includes: Queuing Theory, Decision trees, Random Forest (RT), Clustering, Gradient Boosting Trees (GBT), Support Vector Machine Algorithms (SVM), Logistics regression, Exploratory Data Analysis (EDA), Probabilities (Poisson, Bi-nomial, normal) as well as covering concepts on Greedy, and non-greedy, algorithms. The student will gain proficiency with both R-Studio and the Python programming language through hands-on exercises and case studies.
Hours: 3
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