2CSSID_S2_SPMS.tex

%\documentclass[]{esisyllabus}
\documentclass[info]{esisyllabus}

%=================================================================
% ADMIN
%=================================================================

\setcsdvalidation{CSD-XX/12/2024}
\setcsvalidation{CS-XX/12/2024}
\setversion{1.3}
\setyear{2024}

%=================================================================
% INFO and Assessment
%=================================================================
\input{2CSSID_S2_SPMS.inf}

%=================================================================
% Abstract
%=================================================================

\setabstract{
	This course will provide students with the fundamental notions of stochastic processes and simulation. It
	is divided into two main parts: Markov random processes (including: the Markov chain, the Poisson process
	and the birth and death processes) and simulation.
	Each of the parts will contain practically important application models such as: random walks, queuing
	models, MCMC, simulated annealing.
}

%=================================================================
% objectives
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\addobjective{Use the studied stochastic processes}
\addobjective{Apply appropriate queue models and provide performance parameters}
\addobjective{Use simulation techniques}

%=================================================================
% prerequisites
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\addprerequisite{Basic knowledge of probability statistics}

%=================================================================
% Chapters' outline
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\addchapter{Markov chains}{25}{
	\begin{itemize}
		\item Classification of states
		\item Absorbing Markov chains
		\item Reversible Markov Chains
		\item Ergodic Theorems
		\item Application: Random Walks
		\begin{itemize}
			\item Random Walk on Z and Zd
			\item Asymptotic Behavior
			\item Symmetric Random Walks
			\item PageRank Algorithm
		\end{itemize}
	\end{itemize}
}

\addchapter{Poisson process}{15}{
	\begin{itemize}
		\item 
	\end{itemize}
}

\addchapter{Birth and Death processes}{5}{
	\begin{itemize}
		\item 
	\end{itemize}
}

\addchapter{Queuing Models}{25}{
	\begin{itemize}
		\item Markov Models: Open and Closed Systems
		\item M/M/1 Model
		\item M/M/s Model
		\item M/M/S/L, M/M/S/S and M/M/$\infty$ Models
	\end{itemize}
}

\addchapter{Simulation}{20}{
	\begin{itemize}
		\item Random Number Generators
		\item Generation of Discrete and Continuous Random Variables According to Different
		Distributions
		\item Rejection Method
		\item Estimation of an Integral by the Monte Carlo Method
		\item Importance Sampling
		\item Variance Reduction Techniques
	\end{itemize}
}

\addchapter{MCMC}{10}{
	\begin{itemize}
		\item Gibbs Sampler
		\item MH Sampler
	\end{itemize}
}


%=================================================================
% Practicals and Tutorials
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%\addpractical{Labs}{
%	
%}

%=================================================================
% learning methods/tools
%=================================================================

\addmethod{Exercise sessions (TD)}
\addmethod{Practical work, using simulation techniques}

%=================================================================
% redactors & reviewers
%=================================================================

\addredactor{Naïma}{Bessah}{n\_bessah@esi.dz}

%\addreviewer{Abdelkrime}{Aries}{ab\_aries@esi.dz}


\begin{document}
	
	\section{Identification}

	\printidentification
	
	\section{Course description \& objectives}

	\printabstract
	
	\printobjectives
	
	\section{Prerequisites}
	
	\printprerequisites
	
	\section{Content}
	
	\subsection{Lectures}
	
	\printchapters
	
	\subsection{Tutorials/Practicals}
	
	\printpracticals
	
	\section{Learning methods/tools}
	
	\printmethods
	
	\section{Assessment}
	
	\printassessment

	\section{Bibliography}
	
	\bibliographystyle{apacite}
	\nocite{*}
	\renewcommand{\bibsection}{}
	\bibliography{2CSSID_S2_SPMS}
	
	
	\section{Redactor(s)}
	
	\printredactors
	
	\printreviewers
	



\end{document}