M.Sc. Syllabus

• Semester 1

1. SC-101 Principles of Programming Languages I
   Introduction and Motivation Algorithm Analysis Techniques, Algorithm Design Techniques, Graph Theory, NP-Completeness
    

2. SC-102 Software Engineering
   Introduction to software engineering, The software process, Software engineering practice, Software constructions and implementation, Advance topics in software engineering
    

3. SC-103 Advanced Database Management Concepts
   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
    

4. SC-104 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
    

5. SC-105 Computational Laboratory I
   Experts from industry will guide projects, which will be based on current technologies.

• Semester 2

1. SC-201 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
    

2. SC-202 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
    

3. SC-203 Elective
    

4. SC-204 Numerical Methods for Scientific Computing I
   Number Systems and errors Linear Equations Algebraic eigenvalue problem Curve Fitting and Functional approximation Numerical Differentiation & Integration
    

5. SC-205 Computational Laboratory II
   Experts from industry will guide projects, which will be based on current technologies.

• Semester 3

1. SC-301 Network Concepts
   Review of basic concepts of Data Communication, Transport and Session Protocols, Internetworking, Presentation Layer, Application Layer, Fiber Optic Networks, Satellite Networks
    

2. SC-302 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
    

3. SC-303 Elective
    

4. SC-304 Numerical Methods for Scientific Computing II
   Numerical Differentiation and Integration, Numerical Methods for Ordinary Differential Equations, Optimization - Golden Search Methods, Brent’s procedure, quasi-Newton Methods, Direction Set Methods
    

5. SC-305 Elective
   
   EL - I Parallel Computing and Grid Computing
   Introduction Solving Problem in parallel Structure of parallel computers Programming parallel computers Case Studies Grid Computing
   
   EL - II Applications 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 - III Statistical Computing
   Introduction to statistical computing, Random Number Generation, Monte Carlo Methods, Non-linear Statistical Methods, Multiple Linear Regression Analysis
   
   EL - IV Computer Applications in Physics
   Monte Carlo Methods, Numerical Solutions of Schrodinger equations, Electronic Structure Calculation on simple solids, Classical Molecular Dynamics
   
   EL - V 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 - VI Modeling of Biological Systems
   Concepts and principles of modeling. Limitations of models, Models of behavior, Modeling in Epidemiology and Public Health SIR models
   
   EL - VII 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 - VIII 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
   
   EL - IX Soft Computing
   Fuzzy logic, Neural Networks, Genetic Algorithms
   
   EL - X Design Concepts and Modeling
   Introduction to design process, Inception phase, Elaboration phase, Construction phase, Transition phase

• Semester 4

1. SC-401 Industrial Training
   At the end of the FOURTH semester, student will be examined in the course R&D/Industrial Training.