Masters in Scientific Computing - Syllabus

    Semester I

  • SC-101 Principles of Programming Languages I
  • SC-102 Software Engineering
  • SC-103 Advanced Database Management Concepts
  • SC-104 Mathematics For Scientific Computing
  • SC-105 Computational Laboratory I

    Semester II

  • SC-201 Principles of Programming Languages II
  • SC-202 Operating System Concepts
  • SC-203 Elective
  • SC-204 Numerical Methods for Scientific Computing I
  • SC-205 Computational Laboratory II

    Semester III

  • SC-301 Network Concepts
  • SC-302 Scientific Visualization
  • SC-303 Elective
  • SC-304 Numerical Methods for Scientific Computing II
  • SC-305 Elective

    Semester IV

  • SC-401 Industrial Training
  • At the end of the FOURTH semester, student will be examined.

Detailed Semester Wise Syllabus

  • SC-101 Principles of Programming Languages I
  • Introduction and Motivation Algorithm Analysis Techniques, Algorithm Design Techniques, Graph Theory, NP-Completeness
  • SC-102 Software Engineering
  • Introduction to software engineering, The software process, Software engineering practice, Software constructions and implementation, Advance topics in software engineering
  • 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
  • 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
  • SC-105 Computational Laboratory I
  • Experts from industry will guide projects, which will be based on current technologies
  • 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
  • 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
  • SC-203 Elective
  • One of the ELECTIVE give below
  • SC-204 Numerical Mehtods for Scientific Computing I
  • Number Systems and errors Linear Equations Algebraic eigenvalue problem Curve Fitting and Functional approximation Numerical Differentiation & Integration
  • SC-205 Computational Laboratory I
  • Experts from industry will guide projects, which will be based on current technologies
  • 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
  • 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
  • SC-303 Elective
  • One of the ELECTIVE give below
  • SC-304 Numerical Mehtods 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
  • SC-305 Elective
  • One of the ELECTIVE give below

    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