Organisation : Interdisciplinary School of Scientific Computing
Announcement : Syllabus
Name Of Exam : M.Sc Entrance Exam

Home Page : http://issc.unipune.ac.in/
Download Syllabus Here : http://issc.unipune.ac.in/syllabus.php

M.Sc Entrance Exam Syllabus :
Sem I :
Principles of Programming Languages I :
Introduction and Motivation Algorithm Analysis Techniques, Algorithm Design Techniques, Graph Theory, NP-Completeness.

Software Engineering :
Introduction to software engineering, The software process, Software engineering practice, Software constructions and implementation, Advance topics in software engineering

Advance Database Management Concepts(ADBMC):
Review of Database management concepts. Data storage, Database file structure and Implementation of Indexes Query processing and optimization Transaction management Parallel and distributed databases Object oriented database design Data Mining

Mathematics for Scientific Computing :
Functions, Limits, Continuity, Differentiation & Integration Linear Algebra and Matrices Infinite Series Fourier Series and Fourier Integral Ordinary Differential Equations Partial Differentiation Vector Analysis

Computational Laboratory I :
Experts from industry will guide projects, which will be based on current technologies.

Sem II :
Principles of Programming Languages II :
C++
Basic Facilities Data types,Variables, declarations Pointers and arrays and Structures Dynamic memory. Expressions and statements Various Types Of Functions (Inline, Friend etc) Namespases and Exceptions Concept Of Classes, Types of Classes. Encapsulation, Conversions, type Promotion, Default Arguments And Type Casts. Operator Overloading Inheritance, Virtual Functions. Templates. Exception Handling.

LISP
Introduction, The LISP Programming Language, Pattern Matching, Knowledge Representation Searching

Operating System Concepts :
Introduction to UNIX Implementation of buffer cache File system, Process, Process Scheduler, Memory Mangement Techniques Time and Clock, I/O Subsystems, Interprocess Communication, and thread communication

Numerical Methods For Scientific Computing I :
Number Systems and errors Linear Equations Algebraic eigenvalue problem Curve Fitting and Functional approximation Numerical Differentiation & Integration

Computational Laboratory II :
Experts from industry will guide projects, which will be based on current technologies.

Sem III :
Network Concepts :
Review of basic concepts of Data Communication, Transport and Session Protocols, Internetworking, Presentation Layer, Application Layer, Fiber Optic Networks, Satellite Networks

Scientific Visualization :
Introduction to computer graphics, Raster graphics techniques, Vectors and their use in graphics, Transformation of pictures, 3-D viewing with synthetic camera, 3-D graphics, Write Frame Models, Hidden Line and Surface Removal, Backface Culling, Light and Shading Models , Rendering Polygonal Masks Flat, gouraud, phone shading, Ray Tracing, Introduction to multimedia and animation

Numerical Methods for Scientific Computing II :
Numerical Differentiation and Integration, Numerical Methods for Ordinary Differential Equations, Optimization - Golden Search Methods, Brents procedure, quasi-Newton Methods, Direction Set Methods


Electives :
EL-1 : Parallel Computing and Grid Computing
Introduction Solving Problem in parallel Structure of parallel computers Programming parallel computers Case Studies Grid Computing

EL-2 : Application of Computers to Chemistry
Computational Chemistry, Fundamentals of Chemistry, Molecular Representations and Search Molecular Graphics and fitting Force Field (FF) Methods Classical energy minimization techniques Conformational Analysis, Semi-empirical QM calculations Molecular Docking Molecular Descriptors Quantitative Structure Activity, Relationship Futuristic modeling techniques

EL-3 : Statistical Computing
Introduction to statistical computing, Random Number Generation, Monte Carlo Methods, Non-linear Statistical Methods, Multiple Linear Regression Analysis

EL-4 : Computer Application if Physics
Monte Carlo Methods, Numerical Solutions of Schrodinger equations, Electronic Structure Calculation on simple solids, Classical Molecular Dynamics

EL-5 : Biological Sequence Analysis
Analysis of DNA and Protein sequence, Sequence alignment, Fragment assembly, Genome sequence assembly, Neural network concepts and secondary structure prediction Probabilistic models, Evolutionary analysis

EL-6 : Modeling of Biological Systems
Concepts and principles of modeling. Limitations of models, Models of behavior, Modeling in Epidemiology and Public Health SIR models

EL-7 : Artificial Intelligence
Introduction to Artificial Intelligence Game playing Knowledge representation using predicate logic Knowledge representation using non monotonic logic Planning Perception Learning Neural Networks Natural language processing Expert system

EL-8 : Soft Computing
Fuzzy logic, Neural Networks, Genetic Algorithms

EL-9 : Design Concepts and Modeling
Introduction to design process, Inception phase, Elaboration phase, Construction phase, Transition phase

EL-10 : Software Testing
Introduction to software testing and analysis, Specification-based testing techniques, Code-based testing techniques, Unit testing, Integration testing, OO-oriented testing, Model-based testing, Static analysis, Dynamic analysis, Regression testing, Methods of test data generation and validation, Program slicing and its application, Reliability analysis, Formal methods; verification methods; oracles, System and acceptance testing