Courses

        COMP 5212: Machine Learning [2023S]

        COMP3721: Theory of Computation [2022F]

        CSIT5910: Machine Learning [2022F]

        MSBD5012:  Machine Learning [2022F]

        COMP 5212: Machine Learning [2022S]

        COMP3721: Theory of Computation [2021F]

        CSIT5910: Machine Learning [2021F]

        MSBD5012:  Machine Learning [2021F]

        COMP 5212: Machine Learning [2021S]

        COMP 3721: Theory of Computation [2020F]

        CSIT 5910: Machine Learning [2020F]

        MSBD 5012:  Machine Learning [2020F]

        COMP 5212: Machine Learning [2020S]

        COMP 3721: Theory of Computation [2019F]

        MSBD 5012:  Machine Learning [2019F]

        CSIT 6000G: Machine Learning [2019F]

        COMP 5213: Unsupervised and Reinforcement Learning [2019S]

        CSIT 6000G: Machine Learning [2019S]

        COMP 3721: Theory of Computation [2018F]

        MSBD 5012:  Machine Learning [2018F]

        COMP 5213: Introduction to Bayesian Networks [2018S]

        CSIT 6000G: Machine Learning [2018S]

        COMP 3721: Theory of Computation [2017F]

        COMP 5213: Introduction to Bayesian Networks [2017S]

        CSIT 5220: Reasoning and Decision under Uncertainty [2017S]

        COMP 3721: Theory of Computation [2016F]

        CSIT 5220: Reasoning and Decision under Uncertainty [2016Su]

        COMP 2711: Discrete Mathematical Tools for Computer Science [2016S]

        COMP 2711: Discrete Mathematical Tools for Computer Science [2015F]

        CSIT 5220: Reasoning and Decision under Uncertainty [2015Su]

        COMP 3721: Theory of Computation [2015S]

        COMP 2711: Discrete Mathematical Tools for Computer Science [2014F]

        COMP 5213: Introduction to Bayesian Networks [2014F]

        CSIT 5220: Reasoning and Decision under Uncertainty [2014su]

        COMP 2711: Discrete Mathematical Tools for Computer Science [2013F]

        CSIT 5220: Reasoning and Decision under Uncertainty [2013Su]

        COMP 2711: Discrete Mathematical Tools for Computer Science [2013S]

        COMP 6931A: Probabilistic Models for Unsupervised Learning [2013S]

        COMP 5213: Introduction to Bayesian Networks [2012F]

        CSIT 5220: Reasoning and Decision under Uncertainty [2012Su]

        COMP 2711: Discrete Mathematical Tools for Computer Science [2012Sp]

        CSIT 600N: Reasoning and Decision under Uncertainty [2011Su, 2010Su]

        COMP 170: Discrete Mathematical Tools for Computer Science [2011Sp, 2010Sp, 2009Sp]

        COMP 328: Machine Learning [2010F, 2010Sp, 2009Sp]

        COMP 538: Introduction to Bayesian Networks

        COMP104: Programming Fundamentals and Methodology

        COMP171: Data Structures and Algorithms

        COMP 201: Java Programming

        COMP 221: Fundamentals of AI

        COMP 271: Design and Analysis of Algorithms

        COMP 272: Theory of Computation

        COMP 327: Pattern Recognition

        COMP 527: Pattern Recognition