Graduate Courses





  • CSE 5401 - Advanced Artificial Intelligence

    Topics:

    Introduction, Advanced search techniques in AI, Knowledge based system design, Advanced plan generating systems, Bayesian network and probabilistic reasoning, Learning in neural belief networks, Practical natural language processing, Computer vision, Introduction to Robotics.

  • CSE 5402 - Fuzzy Systems

    Topics:

    Basic Concepts of Fuzzy set theory; Fuzzy numbers; Aggregation operations of Fuzzy sets; The theory of approximate reasoning; Introduction to Fuzzy logic control; Fuzzy System Models and Developments; Fuzzy logic controllers; Defuzzification methods; Linguistic descriptions and their analytical forms; The flexible structure of fuzzy systems; Practical Aspects of Neural Networks.

  • CSE 5403 - Machine Learning

    Topics:

    Definition of learning systems, Goals and applications of machine learning, Inductive Classification, Decision Tree Learning, Ensemble Learning, Experimental Evaluation of Learning Algorithms, Computational Learning Theory, Rule Learning: Propositional and First-Order, Artificial Neural Networks, Support Vector Machines, Bayesian Learning, Instance-Based Learning, Text Classification, Clustering and Unsupervised Learning, Language Learning

  • CSE 5404 - Advanced Pattern Recognition

    Topics:

    Introduction to formal languages, String languages for pattern description, Higher dimensional pattern grammars, Syntax analysis as a recognition procedure, Stochastic languages, Error-correcting parsing for string languages, Error-correcting tree automata, Cluster analysis for syntactic patterns, Grammatical inference for syntactic pattern recognition, Application shape analysis of wave forms and contours, Syntactic approach to texture analysis.

  • CSE 5405 - Speech Recognition

    Topics:

    Introduction, Speech signal: production, perception and characterization, Signal processing and analysis; Pattern comparison techniques: distortion measures, spectral-distortion measures, time alignment and normalization; Recognition system design and implementation: source-coding, template training, performance analysis; Connected word models: two level DP, level building algorithm, one-pass algorithm; Continuous speech recognition: sub word units, statistical modeling, context-dependent units; Task oriented models.

  • CSE 5406 - Machine Translation

    Topics:

    Theoretical problems: Definition, Context dependency, interpretation and translation; Engineering problems of machine translation: Maintainability, tunability, modularity, and efficiency; Linguistics-based MT: Compositionality and isomorphism, Declarative frameworks, Constraint-based formalisms; Knowledge-based MT: Translation and understanding, Design of interlinguas, The conceptual lexicon; Statistics-based MT: E-M algorithms, Alignment of bilingual corpora, Translation templates; Example-based MT: Similarity measures, Levels of comparison; Treatment of context dependency: Knowledge-based transfer, Sublanguage-based MT, Translation units.

  • CSE 5407 - Knowledge Representation and Reasoning

    Topics:

    Knowledge representation, uses in computers; logic-based languages for KR; automated reasoning techniques and systems; applications of KR to ontologies and semantic web.

  • CSE 5408 - Advanced Data Mining

    Topics:

    Introduction; Data warehousing and OLAP technology for data mining; Data preprocessing; Data mining primitives, languages and systems; Descriptive data mining: characterization and comparison; Association analysis; Classification and prediction; Cluster analysis; Mining complex types of data; Applications and trends in data mining.

  • CSE 5451 - Evolutionary Algorithms

    Topics:

    Introduction to evolutionary algorithm; Selection: rank-based, roulette wheel, stochastic, local, truncation and tournament; Recombination: discrete, real valued and binary valued; Mutation: real valued and binary valued; Reinsertion: global and local; Population models: global- worker/farmer, local diffusion, and regional  migration; Co-evolution: cooperative and competitive; Learnable evolution model; Fast evolutionary programming; Application of evolutionary algorithms to: system design, telecommunication, robotics and other industrial areas.

  • CSE 5452 - Neural Networks

    Topics:

    Fundamentals of Neural Networks; Back propagation and related training algorithms; Hebbian learning; Cohonen-Grossberg learning; The BAM and the Hopfield Memory; Simulated Annealing; Different types of Neural Networks: Counter propagation, Probabilistic, Radial Basis Function, Generalized Regression, etc; Adaptive Resonance Theory; Dynamic Systems and neural Control; The Boltzmann Machine; Self-organizing Maps; Spatiotemporal Pattern Classification, The Neocognition; Practical Aspects of Neural Networks.

Copyright © 2017 Computer Science & Engineering Discipline.
Khulna University, Khulna 9208, Bangladesh
+880-41-720171-3 (Ext.-1069 office) (Ext.-1105 head) +880-41-2831551 (direct)
Email: info@cseku.ac.bd