European Masters Program in Language and Communication Technologies
Syllabi of Selected Courses offered at the FUB
The courses listed in (A) are obligatory for students of the European Masters Program in Language and Communication Technologies. If a student has already passed exams covering their topics he/she is suggested to follow the optional courses in the class (B).
- (A): Obligatory Courses
- Introduction to Artificial Intelligence Introduction to AI, Intelligent Agents. Problem solving and search techniques. Constraint satisfaction problems. Introduction to games. Introduction to planning.
- Advanced Algorithms Introduction and overview. Computational geometry. Graph algorithms and network optimization. Algorithm analysis techniques. Numerical algorithms. Linear programming. Approximation algorithms. Randomized algorithms. Online algorithms and competitive analysis.
- Advanced Statistics Tests of hypothesis about a population mean and about a population portion; Comparing two population means and determining the sample size. Testing the assumption of equal population variances; Comparing two population proportions and determining the sample size. Multinomial experiments and contingency table analysis; Simple linear regression: the least square approach, the coefficients of correlation and determination, using the model for prediction; Quality, processes and systems. Statistical control and control charts, charts for monitoring the mean and the variation.
- Computational Linguistics Why is language/speech difficult and interesting?; Ambiguity, communication, inference ...; Phonetics, Morphology, Syntax; Semantics; Pragmatics; Formal Grammars, Parsing; Logic and NLP; Corpora, Ontologies, Wordnet. History of the field.
- Computational Logic Computational Logic: motivation and importance of the field. Propositional and First Order Logic: deduction, proof theory, automated theorem proving. Higher Order Logic. Induction and Abduction. Constraint (Logic) Programming. Non-monotonic reasoning.
- Cross-Language Information Technologies Statistical framework of machine translation; Models and algorithms for various application areas; Document translation; Speech translation; Cross-language information access; Experimental work with available software.
- Data Warehousing and Data Mining Visual data mining. Statistical primer: parameter estimation, quality metrics of parameter estimation, hypothesis testing, Bayes theorem, histograms, scatter plots, regression. Classification algorithms. Clustering algorithms. Association rules. Web mining. Spatial mining. Temporal mining. Data Warehousing. OLAP. The multi-dimensional join. Data integration. Data quality.
- Digital Libraries Digitization, storage, and interchange; Digital objects, composites, and packages; Metadata, cataloging, author submission; Naming, repositories, archives; Spaces (conceptual, geographical, 2/3D, VR); Architectures (agents, buses, wrappers/mediators), interoperability; Services (searching, linking, browsing, and so forth); Intellectual property rights management, privacy, protection (watermarking); Archiving and preservation, integrity Enterprise Application Integration; Design and architecture of large information systems; Commercial web sites, scientific servers, data clusters; Middleware, databases, programming languages and distributed systems; Web data
- Foundations of Databases Relational query languages, conjunctive queries, relational calculus, query processing and optimization, datalog and recursion, datalog evaluation, negation in datalog, complexity and expressiveness of query languages, incomplete information, disjunctive databases.
- Human Computer Interaction Introduction to Human Computer Interaction. ACM model for HCI: human, computer, use and context, development process. Human and computers' characteristics. User modeling: cultural and cognitive aspects. The design process. Experiencing building applications through various methods and systems. Techniques for prototyping and implementing graphical user interfaces. Evaluating interface quality to apply the training in industry. Guidelines for building applications for different appliances: PDA, cellphones, industrial devices, computers etc.
- Intelligent Interfaces The program will cover the topics of multimodal, tangible & conversational interfaces with special emphasis on the need of informed design and evaluation. Topics are covered from a broad multidisciplinary perspective, with an emphasis on real-world users and usage contexts. In addition to weekly classroom lectures, guest lectures, and discussion, this class includes a hands-on practicum component in which students participate in state-of-the-art research and interface design to complete a team project.
- Introduction to Linguistics Morphology; Phonetics; Phonology; Syntax; Semantics.
- Programming Languages The role of programming languages. Imperative Programming. Data representation. Procedure activation. Object Oriented Programming. Logic Programming Paradigm: Propositional Logic, Programming, First Order Logic Programming: Prolog, Prolog techniques and advanced techniques, Constraint logic programming. Functional Programming, Typed Functional Programming: Lisp, Scheme. Concurrent Programming. Languages for hardware description: VHDL
- Automatic Speech Recognition Introduction to spoken language interfaces; Human speech production and perception systems; Speech signal representation; Pattern classification; Acoustic modeling; Language modeling; Word hypotheses generation.
- Technical Scientific Communication Organizational patterns and outlining. Audience analysis. Correspondence, sales letters. Short reports, summaries, abstracts. Technical descriptions, manuals. Oral presentations. Analytical reports.
- Text Processing Data and knowledge driven methodologies for text processing; Morpho-syntactic analysis; Content extraction; Part of speech tagging; Shallow parsing; Terminology recognition; Named entities recognition; Word sense disambiguation.
- Theory of Computing Finite automata, regular expressions, properties of regular languages, context-free grammars and languages, pushdown automata, Turing Machines, undecidability, computational complexity, NP-completeness, polynomial hierarchy
- Knowledge Representation A review of computational logic. Knowledge Representation. Structural description logics. Propositional description logics. Knowledge bases. Modal logics. Logics and databases
- (B): Optional Courses
- Compilers Introduction to the Notion of Compiler. Lexical Analyzer. Syntax Analysis and Parser construction: 1. Top-Down Parser 2. Bottom-Up Parser 3. Operator-Precedence Parsing 4. LR Parser. Syntax-Directed Translation to Translate Programming Language Constructs. Semantic Analysis: Type Checking. Code Generation and Principles of Code Optimization.
- Concurrent Object-Oriented Programming Approaches to concurrent programming; Formal models of concurrency; Concurrency and object-orientation; SCOOP model
- Database Programming design and architecture of large scale information systems; multi-tier architectures, applications servers, web applications, middleware; database programming: store procedures, triggers, cursors; ODBC, JDBC, CORBA
- Database management system Storage and File Structure; Indexing and Hashing; Query Processing; Query Optimization; Transactions; Concurrency Control; Recovery System
- Formal Methods Propositional and First Order Logic. Modeling Systems as Transition Systems. Temporal Logics: 1. Linear Temporal Logic (LTL) 2. Computation Tree Logic (CTL and CTL*) Model Checking CTL formulas. Ordered Binary Decision Diagrams (OBDD's). CTL Symbolic Model Checking.
- Formal Languages Finite state machines and applications. Theory of finite automata and regular languages. Formal Grammars, Context-free grammars and languages.
- Internet Technologies Web applications design; Tools and languages to develop web applications; Mobile applications design; Tools and languages to develop mobile applications
- Intelligent Systems Search and constraint satisfaction; Knowledge representation and reasoning systems; Machine learning; Neural networks; AI Planning Systems
- Logic Agents that Reason Logically; Motivating the course; Propositional Logic; Foundations of Propositional Logic; Deduction in Propositional Logic; First Order Logic; Foundations of First Order Logic; Using First Order Logic; Representation, Reasoning, and Logic; Conceptual Modelling and Logic; Entity Relationship diagrams; UML class diagrams.
- Multimedia Retrieval Organization of large multimedia documents; Searching text, picture, music, voice, and video documents; Feature extraction; Indexing
- Non Classical Logics Modal logics; Non-monotonic logics; Process logics
- Semantic Web Technologies Semantic Markup; Resource Description Framework (RDF); Languages for the Semantic Web (OWL); Ontologies; Tools for Ontology Construction; Reasoning Engines; Semantic Web-enabled Agents; Applications
- Knowledge Bases and Databases Languages for conceptual data modeling and ontology design; Intelligent information access; Query processing in knowledge based systems; Knowledge base integration; Distributed knowledge based systems
- XML and Semistructured Databases Semistructured data models, XML, DTD, XMLSchema, XPath, XQuery, expressive power of XML query languages, storage of XML in RDBMS, tools for querying XML data.