CSC-415 Final Project-I

COURSE TITLE: Final Project-I (CSC-415)

Credit Hours: 3


CSC-412 Operational Research

Course Name:            Operational Research (CSC-412)

Credit Hours:              3

Prerequisites:             None


Course Outlines: 

History and definition of O.R. Introduction to linear programming. Formulation  of LP model. Graphical solution of two variables. Standard Form. Simplex  method. Duality theory; Sensitivity Analysis, Primal and dual form. Gaussian  elimination. Transportation Problem, Assignment problem. Introduction to CPM and PERT techniques. Queuing Models, Inventory models, Dynamic  programming and simulation models

 

Reference Materials:

  1. Taha, H.A. (1998). “Operations Research”. Macmillan. London.
  2. Hillier, F.S. and Lieberman G. J. (1996). “Introduction to Operations  Research”, Holden Day.
  3. Gupta, P.K. & Hira, D.S. (1994). “Operations Research”. S. Chand &  Co., New Delhi.
  4. Bazarra, N.M., Jarvis J.J. and Sherali, H.D. (1990) “Linear Programming  and Network Flows”, John Wiley & Sons, 2nd ed.
  5. Ravindran, A., Philips, D.J and Sillerg, J.J. (1987). “Operations  Research: Principles and Practice” John Wiley.
  6. Bronson, R. (1983). “Operations Research – Schaums’ Outline Series” –  McGraw Hill.

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CSC-414 Advanced Software Engineering

Course Name:            Advanced Software Engineering (CSC-414)

Credit Hours:              3

Prerequisites:             Introduction to Software Engineering

 

Course Outlines:

System Development using Formal Techniques, Algebraic  specification, Abstract model specification, Verification: Proof Systems, Proof Techniques, Proof obligations, Design: Data refinement, operation refinement, Design decomposition. Software Reliability and Metrics. Macro models: productivity, effort. Defect models: Software reliability, Failures and fault, Software reliability modelling. Simple model, Markove modelling, Parameter estimation, Comparison of models. 

Reference Materials:

  1. Software Engineering 8E by Ian Sommerville, Addison Wesley; 8th Edition (2006). ISBN-10: 0321313798
  2. Systems Analysis and Design by Gary B. Shelly, Thomas J. Cashman and Harry J. Rosenblatt, Course Technology; 7th Edition (2007). ISBN-10: 1423912225
  3. Software Engineering: A Practitioner's Approach by Roger S. Pressman, McGraw Hill Science/Engineering/Math; 7th Edition (2009). ISBN-10: 0073375977

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CSC-413 Information Security

Course Name:            Information Security (CSC-413)

Credit Hours:              3

Prerequisites:             Data Communication and Computer Networks

 

Course Outline:

Basic notions of confidentiality, integrity, availability; authentication models; protection models; security kernels; Encryption, Hashing and Digital Signatures; audit; intrusion detection and response; database security, host-based and network-based security issues operational security issues; physical security issues; personnel security; policy formation and enforcement; access controls; information flow; legal and social issues; identification and authentication in local and distributed systems; classification and trust modeling; risk assessment

Reference Materials:

  1. Computer Security: Art and Science, Matthew Bishop
  2.  Cryptography and Network Security by William Stalling 6th Edition, 2012
  3. Principles of Information Security 3rd E by Michael E. Whitman and Herbert J. Mattord

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MS-411-BS Professional Practices

Course Name:            Professional Practices (MS-411-BS)

Credit Hours:              3

Prerequisites:            None

 

Course Outline:

Introduction, Computing Ethics, Philosophy of Ethics, Ethics and the Internet. Intellectual Copy Right, Accountability and Auditing, Social Application of Ethics.

Reference Materials:

  1.  Computer Ethics, Deborah G. Johnson, Pearson Education (2001) 3rd Edition or Latest Edition
  2. Professional Issues in Software Engineering, M.F. Bott et. al. (Latest Edition).


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CSC-411 Artificial Intelligence

Course Name:            Artificial Intelligence (CSC-411)

Credit Hours:              3 (2+1)

Prerequisites:             Discrete Structures

 

Course Outline:

Artificial Intelligence: Introduction, AI Paradigms and Hypothesis, Intelligent Agents. Difference between Cybernetic Intelligence and Artificial Intelligence, Objectives and Scope of Weak AI and Strong AI, Problem-solving: Solving Problems by Searching, Informed Search and Exploration, Constraint Satisfaction Problems, Adversarial Search. Knowledge and reasoning: Logical Agents, First-Order Logic, Inference in First-Order Logic, Knowledge Representation. Planning and Acting in the Real World. Uncertain knowledge and reasoning: Uncertainty, Probabilistic Reasoning, Probabilistic Reasoning over Time, Making Simple Decisions, Making Complex Decisions. Learning: Learning from Observations, Knowledge in Learning; Learning Methods, Reinforcement Learning. Communicating, perceiving, and acting: Communication, Probabilistic Language Processing, Perception and Robotics. Introduction to LISP/PROLOG and Expert Systems (ES) and Applications; Artificial General Intelligence, Issues in Safe AI, Introduction to Cognitive and Conscious Systems.

Reference Materials:

  1. Artificial Intelligence: Structures and Strategies for Complex Problem Solving: International Edition by George F. Luger, 6th edition: Pearson Education, 2008.
  2. Artificial Intelligence: A Modern Approach, by Stuart Jonathan Russell, Peter Norvig, John F. Canny, 3nd Edition, Prentice Hall

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