• Academic Year 2024/2025 o ACM 216: Markov Chains, discrete stochastic processes and applications. o ACM 118: Stochastic Processes and Regression. • Academic Year 2023/2024 o ACM 216: Markov Chains, discrete stochastic processes and applications. o ACM 118: Stochastic Processes and Regression. • Academic Year 2022/2023 o ACM 216: Markov Chains, discrete stochastic processes and applications. o ACM 118: Stochastic Processes and Regression. • Academic Year 2021/2022 o ACM 216: Markov Chains, discrete stochastic processes and applications. o ACM 118: Stochastic Processes and Regression. • Academic Year 2020/2021 o ACM 216: Markov Chains, discrete stochastic processes and applications. o ACM 118: Stochastic Processes and Regression. • Academic Year 2019/2020 o ACM 216: Markov Chains, discrete stochastic processes and applications. o ACM 118: Stochastic Processes and Regression. • Academic Year 2018/2019 o CMS/ACM/EE 117: Probability and Random Processes o ACM 216: Markov Chains, discrete stochastic processes and applications • Academic Year 2017/2018 o CMS/ACM/EE 117: Probability and Random Processes o ACM 216: Markov Chains, discrete stochastic processes and applications • Academic Year 2016/2017 o CMS/ACM/EE 117: Probability and Random Processes o ACM 216: Markov Chains, discrete stochastic processes and applications • Academic Year 2015/2016 o CMS/ACM 116: Introduction to stochastic processes and modeling. o ACM 216: Markov Chains, discrete stochastic processes and applications. • Academic Year 2014/2015 o ACM/EE 116: Introduction to stochastic processes and modeling. o ACM 216: Markov Chains, discrete stochastic processes and applications. • Academic Year 2013/2014 o ACM/EE 116: Introduction to stochastic processes and modeling. o ACM 216: Markov Chains, discrete stochastic processes and applications. • Academic Year 2012/2013 o ACM 216: Markov Chains, discrete stochastic processes and applications. o ACM 217: Stochastic Differential Equations and applications. • Academic Year 2011/2012 o ACM 95/100b: Introductory methods of applied mathematics. • Academic Year 2010/2011 o ACM/EE 116: Introduction to probability and random processes with applications. o ACM 270: Advanced Topics in Optimization. • Academic Year 2009/2010 o ACM/EE 116: Introduction to probability and random processes with applications. o ACM 113: Introduction to Optimization • Academic Year 2008/2009 o ACM/EE 116: Introduction to probability and random processes with applications. o ACM 216: Markov Chains and Martingales. • Academic Year 2007/2008 o ACM/EE 116: Introduction to probability models with applications. o ACM 216: Markov Chains, Discrete Stochastic Processes and Applications. • Academic Year 2006/2007 o ACM/EE 116: Introduction to probability models with applications. o ACM 256: Large Deviations and Concentration Inequalities. • Academic Year 2005/2006 o ACM 216 (Winter): Markov Chains, Discrete Stochastic Processes and Applications. o ACM 217 (Spring): Stochastic Differential Equations and Applications. • Academic Year 2004/2005 o ACM 201a (Fall) and ACM201b (Winter) Partial Differential Equations