Course Catalogue

This module gives an overview of some of the different tiered application architectures (1, 2, 3, N tiers) and some sample designs. The course teaches some of the foundation skills required for building medium to large scale web-based applications, with a B2B e-commerce focus. The course introduces J2EE and Microsoft .NET as two technology architectures for implementing enterprise applications. Java Servlets and Java Server Pages (JSP), Java application servers, integration of data from multiple data sources and distribution of business logic in component-based applications. Multiple application-end delivery formats are considered including web browsers and WAP phones.

Introduction to Neural Network; ANN approach to recognition; ANN models, Design and development of ANN; back propagation model.

Introduction to pattern recognition. General pattern recognition concepts. Statistical pattern recognition. Supervised learning using parametric and non-parametric approaches. Linear discriminant functions and the discrete and binary feature cases. Unsupervised learning and clustering. Syntactic Pattern Recognition: Syntactic recognition via parsing and other grammars, graphical approach to syntactic pattern recognition, learning via grammatical inference. Neural Pattern Recognition: Neural pattern associators and matrix approaches, unsupervised learning in neural pattern recognition.

Introduction to Graphical data processing, Fundamentals of interactive graphics programming, Architecture of display devices and connectivity to a computer, Implementation of graphics concepts of two-dimensional and three-dimensional viewing, clipping and transformations, Hidden line algorithms, Raster graphics concepts: Architecture, algorithms and other image synthesis methods, Design of interactive graphic conversations.

Computational complexity, Parameterized complexity, Algorithms for combinatorial optimization, practical computing and heuristics, Approximation algorithms, LP based approximation algorithms, randomized algorithms, Experimental algorithmic, Algorithms in state-of-the-art fields like Bioinformatics, Grid Computing, VLSI design etc.