2CSSID_S2_NLP.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_NLP.inf}

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

\setabstract{
	Natural Language Processing (NLP) is an interdisciplinary field that combines linguistics, computer science, and artificial intelligence to enable computers to understand and generate human language. 
	With advanced models like OpenAI's GPT and Google's BERT, NLP has become crucial across various industries. 
	It is often included in artificial intelligence (AI) and data science curricula as it is a key application of AI. 
	This course covers both research and development aspects of NLP, addressing a wide range of topics such as lexicon, syntax, semantics, pragmatics, and discourse. 
	While it shares similarities with compilation courses, NLP uniquely addresses the inherent ambiguity of natural language, unlike the well-defined structure of programming languages.
}

%=================================================================
% objectives
%=================================================================

\addobjective{Understand some linguistic concepts and problems}
\addobjective{Apply concepts covered in the prerequisites to solve NLP tasks}
\addobjective{Discover some available NLP tools and resources}
\addobjective{Understand research directions in NLP}
\addobjective{Design and implement solutions to NLP problems}


%=================================================================
% prerequisites
%=================================================================

\addprerequisite{Advanced Data structures (CP-S2)}
\addprerequisite{Stochastic convergences and inferential statistics (CP-S4)}
\addprerequisite{Automata Theory, Formal Languages, and Computability (CS-S1)}
\addprerequisite{Numerical Analysis (CS-S1)}
\addprerequisite{Data Analysis (CS-S2)}
\addprerequisite{Machine learning (CS-S3)}
\addprerequisite{Deep learning (CS-S3)}
\addprerequisite{Complexity and Problem Solving (CS-S3)}
\addprerequisite{Knowledge representation and reasoning (CS-S4)}
\addprerequisite{Optimization Techniques and Artificial Intelligence (CS-S4)}
\addprerequisite{Stochastic Processes, Models and Simulation (CS-S4)}


%=================================================================
% Chapters' outline
%=================================================================

\addchapter{Introduction to NLP}{7}{
	\begin{itemize}
		\item History
		\item Language processing levels
		\item Applications of NLP
		\item NLP Challenges
	\end{itemize}
}

\addchapter{ML for NLP}{10}{
	\begin{itemize}
		\item MLP-only architectures
		\item CNN-based architectures
		\item RNN-based architectures
		\item Transformer-based architectures
	\end{itemize}
}

\addchapter{Basic text processing}{10}{
	\begin{itemize}
		\item Characters processing
		\item Text Segmentation
		\item Text normalization and filtering
		\item Morphology processing
	\end{itemize}
}

\addchapter{Sequence processing}{11}{
	\begin{itemize}
		\item Language models
		\item Sequence labeling
		\item Part of Speech (PoS) tagging
	\end{itemize}
}

\addchapter{Parsing}{14}{
	\begin{itemize}
		\item Syntactic structures
		\item Constituency parsing
		\item Dependency parsing
	\end{itemize}
}

\addchapter{Word semantics}{12}{
	\begin{itemize}
		\item Lexical databases
		\item Vector representation of words
		\item Word embedding
		\item Word Sense Disambiguation (WSD)
	\end{itemize}
}

\addchapter{Sentence semantics}{12}{
	\begin{itemize}
		\item Semantic roles
		\item Semantic roles labeling (SRL)
		\item Semantic representation of sentences
	\end{itemize}
}

\addchapter{Discourse}{10}{
	\begin{itemize}
		\item Coreference detection
		\item Discourse coherence
		\item Textual entailment
		\item Topic segmentation	
	\end{itemize}
}

\addchapter{Some applications}{14}{
	\begin{itemize}
		\item Transformation (Machine translation, Automatic text summarization)
		\item Interaction (Question-Answering, Dialogue systems)
		\item Classification (Sentiment analysis, Readability)
		\item Speech (Recognition, Synthesis)	
	\end{itemize}
}

%=================================================================
% Practicals and Tutorials
%=================================================================

\addpractical{Labs}{
	Implementing an application from scratch to learn some concepts like regular expressions, edit distance, Ngrams, HMM, etc. 
	Each year there is a new lab: Contacts' mining, Naive SpellChecker, Tweets' similarity, Autocompletion, Natural language detector, Tweets' grammaticality judgment, PoS tagging using HMMs, CKY, Plagiarism detection, Sentences' similarity based on their words.
}

\addpractical{Tutorials}{
	Discussing some exercices. It can be calculated such as Ngrams, HMMs, TF, word-word encoding. 
	It can be an application of a given method such as CKY parsing, Shift-Reduce parsing, graph-based parsing, semantic parsing, coreference and coherence. 
	It can be critical thinking; given a problem, discuss possible solutions or given a solution find its limits and how to fix it.
}

\addpractical{Workshops}{
	Designing and implementing an application using available API's. 
	The goal is to learn using tools to construct a functional application. 
	For example, PoS tagging using NLTK$<$HMM$>$ and flair$<$IOB-embedding$>$; RNN-based Machine translation using Keras; etc.
}

\addpractical{Online quizzes}{
	Answering a quiz at the end of each chapter. 
	The goal is to promote lecture review by students.
}

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

\addmethod{Lectures (presentations with open discussion)}
\addmethod{Labs}
\addmethod{Workshops}
\addmethod{Tutorials}
\addmethod{Online quizzes}

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

\addredactor{Abdelkrime}{Aries}{ab\_aries@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_NLP}
	
	
	\section{Redactor(s)}
	
	\printredactors
	
	\printreviewers
	



\end{document}