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  Courses    Aims
 Principles of Database Design(SPRING_2017)
* Introduction to Database * Introduction to the Relational Model * Introduction to SQL * Intermediate SQL * Advanced SQL * Formal Relational Query Languages * Database Design and the E-R Model * Relational Database Design * XML * Object-based Data Models

 Database management has evolved from a specialized computer application to a central component of a modern computing environment, and, as a result, knowledge about database systems has become an essential part of an education in computer science. In this course, the fundamental concepts of database management including aspects of database design, database languages, and database-system implementation will be presented.
 Special Topics (Statistical Natural Language Processing)(SPRING_2017)
* Introduction to NLP * Linguistics Levels and NLP Challenges * Matematical Fundations * Language Models, Smoothing, and evaluation * Machine Learning Overview * Part-of-Speech Tagging * Parsing * Named Entity Recognition * Semantic Analysis, Word Similarity, Word Sense Disambiguation * Semantics Role Labeling * Text Classification and Clustering * Topic Detection * NLP Application Systems

 Natural language processing (NLP) is one of the active topics in artificial intelligence. The main goal of this field is giving the ability of understanding human language to computers. Various systems such as question answering, sentiment analysis, information extraction and retrieval, machine translation, and summarization which have recently received researchers attention are working based on NLP. The basis of designing and implementing such systems is statistical methods for processing natu
 Technical English(SPRING_2017)
* Information technology * Computer software and hardware * Cloud computing * Linux * Search engines * Database and data mining * Artificial intelligence * Latex

 The goal of this course is improving the English language skills of students in the domain of computer engineering and information technology. The skills includes reading comprehension, listening and writing. To this aim, weekly exercises will be organized.
 Advanced Topics in Information Retrieval and Web Search(FALL_2016)
* Intorduction to IR and web search * Search engine architecture * Overview of traditional IR methods * IR evaluation * Advanced IR methods: language model-based, learning to rank * Overcoming word mismatch problem: language model-based approaches and query expansion approaches * Query log data analysis and Query Suggestion * Personalized search * Information extraction * Cross-Language IR * Question answering systems * Recommendation systems * Expert finding * Digital library * Multimedia retrieval

 By increasing the amount of data on the Web retrieving information become a challenging issue in the last years such that using traditional methods cannot answer user information need. To increase the performance of information search advanced retrieval techniques is required. The goal of this course is expanding the basic knowledge of students about information retrieval and web search and introducing advanced topics to be used for these tasks
 Statistical Natural Language Processing(FALL_2016)
* Introduction to NLP * Linguistics Levels and NLP Challenges * Matematical Fundations * Language Models, Smoothing, and evaluation * Machine Learning Overview * Part-of-Speech Tagging * Parsing * Named Entity Recognition * Semantic Analysis, Word Similarity, Word Sense Disambiguation * Semantics Role Labeling * Text Classification and Clustering * NLP Application Systems

 Natural language processing (NLP) is one of the active topics in artificial intelligence. The main goal of this field is giving the ability of understanding human language to computers. Various systems such as question answering, sentiment analysis, information extraction and retrieval, machine translation, and summarization which have recently received researchers attention are working based on NLP. The basis of designing and implementing such systems is statistical methods for processing text
 Technical English(FALL_2016)
* Information technology * Computer software and hardware * Cloud computing * Linux * Search engines * Database and data mining * Artificial intelligence * Latex

 The goal of this course is improving the English language skills of students in the domain of computer engineering and information technology. The skills includes reading comprehension, listening and writing. To this aim, weekly exercises will be organized.
 Principles of Database Design(SPRING_2016)
* Introduction to Database * Introduction to the Relational Model * Introduction to SQL * Intermediate SQL * Advanced SQL * Formal Relational Query Languages * Database Design and the E-R Model * Relational Database Design

 Database management has evolved from a specialized computer application to a central component of a modern computing environment, and, as a result, knowledge about database systems has become an essential part of an education in computer science. In this course, the fundamental concepts of database management including aspects of database design, database languages, and database-system implementation will be presented.
 Special Topics (Statistical Natural Language Processing)(SPRING_2016)
* Introduction to NLP * Linguistics Levels and NLP Challenges * Matematical Fundations * Language Models, Smoothing, and evaluation * Machine Learning Overview * Part-of-Speech Tagging * Parsing * Named Entity Recognition * Semantic Analysis, Word Similarity, Word Sense Disambiguation * Semantics Role Labeling * Text Classification and Clustering * Topic Detection * NLP Application Systems

 Natural language processing (NLP) is one of the active topics in artificial intelligence. The main goal of this field is giving the ability of understanding human language to computers. Various systems such as question answering, sentiment analysis, information extraction and retrieval, machine translation, and summarization which have recently received researchers attention are working based on NLP. The basis of designing and implementing such systems is statistical methods for processing natu

 
 
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