Study Scheme for BS(CS)

Document technical information

Format pdf
Size 508.2 kB
First found May 22, 2018

Document content analysis

Language
English
Type
not defined
Concepts
no text concepts found

Persons

Peter Norvig
Peter Norvig

wikipedia, lookup

Jean-Jacques Rousseau
Jean-Jacques Rousseau

wikipedia, lookup

Andrew Appel
Andrew Appel

wikipedia, lookup

Ben Shneiderman
Ben Shneiderman

wikipedia, lookup

John Canny
John Canny

wikipedia, lookup

Organizations

Places

Transcript

20-01-2014
Scheme of Study for Bachelor of Science in
Computer Science BS (CS)
4-year programme (8 semesters)
#
1
2
3
Category
Computing Courses
Core Courses
(Comp-Core)
Supporting Areas (Comp-Supp)
General Education (Comp-Gen)
Computer Science Courses
CS Core Courses
(CS-Core)
CS Elective Courses
(CS-Elec)
CS Supporting Courses (CS-Supp)
University Electives (Univ-Elec)
# of Courses
21
12
4
5
16
6
7
3
6
Credit Hours
70
43
12
15
48
18
21
9
18
43
136
Total
Semester-I: (20 Credit Hours)
Category
Course Title
1
2
3
Course
Code
CS 101
CS 103
MT 105
Comp-Core
Comp-Core
Comp-Supp
4
5
6
EG 107
PK 109
* 111
Comp-Gen
Comp-Gen
Univ-Elec
Introduction to Computing
Programming Fundamentals
Calculus and Analytical
Geometry
Functional English (English-I)
Islamic and Pakistan Studies
Univ Elective-1
#
Credit
Hours
4 (3,1)
4 (3,1)
3 (3,0)
Prerequisites
3 (3,0)
3 (3,0)
3 (3,0)
Semester-II: (19 Credit Hours)
1
Course
Code
CS 102
Comp-Core
Discrete Structures
Credit
Hours
3 (3,0)
2
CS 104
Comp-Core
Object Oriented Programming
4 (3,1)
3
ST 106
CS-Supp
Multivariable Calculus
3 (3,0)
4
MT 108
Comp-Supp
3 (3,0)
5
EG 110
Comp-Gen
6
* 112
Univ-Elec
Probability and Statistics
Technical & Report Writing
(English-II)
Univ Elective-2
#
Category
Course Title
3 (3,0)
3 (3,0)
Prerequisites
Programming
Fundamentals
Calculus &
Analytical Geometry
Study Scheme BS(CS)
Semester-III: (19 Credit Hours)
1
Course
Code
CS 201
Comp-Core
Digital Logic Design
Credit
Hours
3 (3,0)
2
CS 203
Comp-Core
Data Structures and Algorithms
4 (3,1)
3
4
MT 205
EL 207
5
EG 209
6
* 211
Comp-Supp Linear Algebra
Comp-Supp Basic Electronics
Communication Skills
Comp-Gen
(English-III)
Univ-Elec Univ Elective-3
#
Category
Course Title
Prerequisites
Programming
Fundamentals
3 (3,0)
3 (2,1)
3 (3,0)
3 (3,0)
Semester-IV: (18 Credit Hours)
Category
Course Title
1
2
3
Course
Code
CS 202
CS 204
CS 206
Comp-Core
Comp-Core
Comp-Core
4
CS 208
CS-Core
Operating Systems
Intro. to Database Systems
Intro. to Software Engineering
Computer Organization &
Assembly Language
5
ST 210
CS-Supp
Differential Equations
6
* 212
Univ-Elec
Univ Elective-4
#
Credit
Hours
3 (3,0)
3 (2,1)
3 (3,0)
Prerequisites
3 (2,1)
Digital Logic Design
3 (3,0)
Calculus &
Analytical Geometry
3
Semester-V: (18 Credit Hours)
#
Course
Code
Category
1
CS 301
Comp-Core
2
CS 303
Comp-Core
3
CS 305
CS-Core
4
CS 307
CS-Core
5
6
CS 309
* 311
CS-Elec
Univ-Elec
Course Title
Computer Communications and
Networks
Human Computer Interaction
Theory of Automata and
Formal Languages
Computer Architecture
CS Elective-1
Univ Elective-5
Credit
Hours
3 (3,0)
3 (2,1)
3 (3,0)
Discrete Structures
3 (3,0)
Computer Org. &
Assembly Language
3
3
2
Prerequisites
Study Scheme BS(CS)
Semester-VI: (18 Credit Hours)
#
Course
Code
Category
1
CS 302
CS-Core
Compiler Construction
3 (2,1)
2
CS 304
CS-Core
Design and Analysis of
Algorithms
3 (3,0)
3
CS 306
CS-Supp
Numerical Computing
3 (2,1)
4
5
6
CS 308
CS 310
* 312
CS-Elec
CS-Elec
Univ-Elec
CS Elective-2
CS Elective-3
Univ Elective-6
Course Title
Credit
Hours
Prerequisites
Theory of Automata
& Formal Languages
Data Structures and
Algorithms
Calculus &
Analytical Geometry
3
3
3
Semester-VII: (15 Credit Hours)
#
1
2
3
4
5
Course
Code
CS 401
CS 403
CS 405
CS 407
CS 409
Category
Course Title
CS-Core
CS-Elec
CS-Elec
CS-Elec
CS-Elec
Artificial Intelligence
CS Elective-4
CS Elective-5
CS Elective-6
CS Elective-7
Credit
Hours
3 (2,1)
3
3
3
3
Prerequisites
Discrete Structures
Semester-VIII: (9 Credit Hours)
#
1
2
Course
Code
CS 402
CS 404
Category
Comp-Gen
Comp-Core
Course Title
Professional Practices
Final Year Project
Credit
Hours
3 (3,0)
6 (0,6)
Prerequisites
* Two alphabetic characters (MG or SS) to be used for the respective course from the university elective
course list.
3
Study Scheme BS(CS)
Electives for BS (CS)
CS Elective Courses:
#
Category
1
2
Course
Code
CS
CS
3
CS
CS-Elec
4
5
6
7
CS
CS
CS
CS
CS-Elec
CS-Elec
CS-Elec
CS-Elec
Software Engineering II
Data Communications
Principles of Programming
Languages
Computer Graphics
Digital Image Processing
Visual Programming
Distributed Computing
8
CS
CS-Elec
Network Security
3 (3,0)
9
10
11
12
13
14
15
16
CS
CS
CS
CS
CS
CS
CS
CS
CS-Elec
CS-Elec
CS-Elec
CS-Elec
CS-Elec
CS-Elec
CS-Elec
CS-Elec
Computer Vision
Systems Programming
Distributed Database Systems
Data Warehousing
Web Engineering
Artificial Neural Networks
Expert Systems
Operations Research
3 (3,0)
3 (2,1)
3 (2,1)
3 (3,0)
3 (2,1)
3 (2,1)
3 (2,1)
3 (3,0)
17
CS
CS-Elec
Network Programming
3 (2,1)
18
19
20
21
22
23
24
CS
CS
CS
CS
CS
CS
CS
CS-Elec
CS-Elec
CS-Elec
CS-Elec
CS-Elec
CS-Elec
CS-Elec
3 (3,0)
3 (2,1)
3 (2,1)
3(2,1)
3(2,1)
3(2,1)
3 (3,0)
25
CS
CS-Elec
26
CS
CS-Elec
Wireless Networks
Telecommunication Systems
Mobile Computing
Java Programming
Android Programming
Cloud Computing
Cyber Security
Object-Oriented Analysis &
Design
Ethical Hacking
CS-Elec
CS-Elec
Course Title
4
Credit
Hours
3 (3,0)
3 (3,0)
Prerequisites
Intro to Software Engg
3 (3,0)
3 (2,1)
3 (2,1)
3 (2,1)
3 (2,1)
3(3,0)
3(2,1)
Computer Comm. and
Networks
Data Struc. & Algo.
Operating Systems
Intro. to Database Sys.
Intro. to Database Sys.
Artificial Intelligence
Computer Comm. and
Networks
Java Programming
Distributed Computing
Intro to Software Engg
Study Scheme BS(CS)
University Electives Courses:
#
Category
Course Title
1
2
3
4
5
6
7
8
Course
Code
MG
MG
MG
MG
SS
SS
SS
SS
Univ-Elec
Univ-Elec
Univ-Elec
Univ-Elec
Univ-Elec
Univ-Elec
Univ-Elec
Univ-Elec
9
SS
Univ-Elec
Financial Accounting
Financial Management
Human Resource Management
Marketing
Economics
Philosophy
Psychology
International Relations
Foreign/Regional Languages (French, German, Chinese,
Japanese, Russian, Sindhi, Punjabi, Balochi, Pashto etc.)
5
Credit
Hours
3 (3,0)
3 (3,0)
3 (3,0)
3 (3,0)
3 (3,0)
3 (3,0)
3 (3,0)
3 (3,0)
3 (3,0)
Study Scheme BS(CS)
Detailed Courses Outline for BS (CS)
6
Study Scheme BS(CS)
Description of Computing-Core and CS-Core Courses
Course Name: Introduction to Computing
Course Structure: Lectures: 3, Labs: 1
Credit Hours: 4
Objectives: This course focuses on a breadth-first coverage of computer science discipline,
introducing computing environments, general application software, basic computing hardware,
operating systems, desktop publishing, Internet, software applications and tools and computer
usage concepts; Introducing Software engineering and Information technology within the
broader domain of computing, Social issues of computing.
Course Outline: Number Systems, Binary numbers, Boolean logic, History of computer system,
basic machine organization, Von Neumann Architecture, Algorithm definition, design, and
implementation, Programming paradigms and languages, GUI programming, Overview of
Software Engineering and Information Technology, Operating system, Compiler, Computer
networks and internet, Computer graphics, AI, Social and legal issues.
Reference Material:
1. “Computers: Information Technology in Perspective, 9/e”, Larry Long and Nancy Long,
Prentice Hall, 2002 / ISBN: 0130929891
2. “An Invitation to Computer Science”, Schneider and Gersting, Brooks/Cole Thomson
Learning, 2000
3. “ An overview of Computer Science”, Sherer
Course Name: Programming Fundamentals
Course Structure: Lectures: 3, Labs: 1
Credit Hours: 4
Objectives: The course is designed to familiarize students with the basic structured
programming skills. It emphasizes upon problem analysis, algorithm designing, and program
development and testing.
Course Outline: Overview of computers and programming. Overview of a computer
language, for example, C language. Basics of structured and Modular programming. Basic
algorithms and problem solving, development of basic algorithms, analyzing a problem,
designing solution, testing designed solution. Fundamental programming constructs,
translation of algorithms to programs, data types, control structures, functions, arrays, records,
files, testing programs.
Reference Material:
1. “Problem Solving and Program Design in C / 6th Ed.”, Hanly & Koffman Addison-Wesley
Publisher 2009. ISBN-10: 0321535421 | ISBN-13: 9780321535429
2. “C How to Program 5th Ed”, (Harvey & Paul) Deitel & Deitel, Publisher: Prentice-Hall
Course Name: Object Oriented Programming
Course Structure: Lectures: 3, Labs: 1
Credit Hours: 4
Prerequisites: Programming Fundamentals
Objectives: The course aims to focus on OO concepts, analysis and software development.
Course Outline: Evolution of Object Oriented (OO) programming, OO concepts and principles,
problem solving in OO paradigm, OO program design process, classes, methods, objects and
encapsulation; constructors and destructors, operator and function overloading, virtual functions,
7
Study Scheme BS(CS)
derived classes, inheritance and polymorphism. I/O and file processing, exception handling.
Reference Material:
1. “C++ How to Program, 6th Ed.”, (Harvey & Paul) Deitel & Deitel ISBN-10:
0136152503 ISBN-13: 9780136152507 Publisher: Prentice Hall
2. “Java How to Program, 7th Ed.”, (Harvey & Paul) Deitel & Deitel ISBN-10:
0132222205 ISBN-13: 9780132222204 Publisher: Prentice Hall.
Course Name: Discrete Structures
Course Structure: Lectures: 3, Labs: 0
Credit Hours: 3
Objectives: This course introduces the foundations of discrete mathematics as they apply to
Computer Science, focusing on providing a solid theoretical foundation of the subject matter.
Further, this course aims to develop understanding and appreciation of the finite nature inherent
in most Computer Science problems and structures through study of combinatorial reasoning,
abstract algebra, iterative procedures, predicate calculus, tree and graph structures. In this course
emphasis is given to statistical and probabilistic formulation with respect to computing aspects.
Course Outline: Introduction to logic and proofs: Direct proofs; proof by contradiction, Sets,
Combinatorics, Sequences, Formal logic, Prepositional and predicate calculus, Methods of
Proof, Mathematical Induction and Recursion, loop invariants, Relations and functions,
Pigeonhole principle, Trees and Graphs, Elementary number theory, Optimization and matching.
Fundamental structures: Functions; relations (more specifically recursions); pigeonhole
principle; cardinality and countability, probabilistic methods.
Reference Material:
1. “Discrete Mathematics and Its Applications, 6TH edition”, Kenneth H. Rosen, McGraw
Hill Book Co. 2006
2. “Discrete Mathematics, 7TH edition”, Richard Johnsonbaugh, Prentice-Hall, 2008.
3. “Discrete Mathematical Structures, 4th edition”, Kolman, Busby & Ross, Prentice-Hall
Publishers 2000.
4. “Discrete and Combinatorial Mathematics: An Applied Introduction”, Ralph P.
Grimaldi, Addison-Wesley Pub. Co., 1985.
Course Name: Operating Systems
Course Structure: Lectures: 3, Labs: 0
Credit Hours: 3
Objectives: To help students gain a general understanding of the principles and concepts
governing the functions of operating systems and acquaint students with the layered approach
that makes design, implementation and operation of the complex OS possible.
Course Outline: History and Goals, Evolution of multi-user systems, Process and CPU
management, Multithreading, Kernel and User Modes, Protection, Problems of cooperative
processes, Synchronization, Deadlocks, Memory management and virtual memory, Relocation,
External Fragmentation, Paging and Demand Paging, Secondary storage, Security and
Protection, File systems, I/O systems, Introduction to distributed operating systems. Scheduling
and dispatch, Introduction to concurrency. Assignments involving different single and
multithreaded OS algorithms.
8
Study Scheme BS(CS)
Reference Material:
1. “Operating Systems Concepts, 7th Edition”, Silberschatz A., Peterson, J.L., & Galvin
P.C. 2004.
2. “Modern Operating Systems, 3rd Edition”, Tanenbaum A.S., 2008.
Course Name: Introduction to Database Systems
Course Structure: Lectures: 2, Labs: 1
Credit Hours: 3
Objectives: The course aims to introduce basic database concepts, different data models, data
storage and retrieval techniques and database design methods. The course primarily focuses on
relational data model and DBMS concepts.
Course Outline: Basic database concepts; Entity-Relationship modeling, Relational data model
and algebra, Structured Query language; RDBMS; Database design, functional dependencies and
normal forms; Physical database design: Storage and file structure; indexed files; b-trees; files
with dense index; files with variable length records; database efficiency and tuning. Transaction
processing and optimization concepts; concurrency control and recovery techniques; Database
security and authorization. Small Group Project implementing a database.
Reference Material:
1. “Introduction to Database Systems”, C.J. Date, Addison Wesley Pub. Co. 2004.
2. “Database Systems: A Practical Approach to Design, Implementation and
Management”, T. Connolly and C. Begg, Addison-Wesley Pub. Co. 2009.
3. “Fundamentals of Database Systems”, Elmasri and Navathe, Addison-Wesley, ISBN:
0-201-74153-9.
Course Name: Introduction to Software Engineering
Course Structure: Lectures: 3, Lab: 0
Credit Hours: 3
Objective: To study various software development models and phases of software development
life cycle (SDLC). The concepts of project management, change control, process management,
software development and testing are introduced through hands-on Team Projects. The students
will study techniques for software verification, validation and testing. They would also study
reliability and performance issues in software design and development. Upon successful
completion of this course the student will be to understand the importance of software
engineering to computer science and the most important general approaches to structuring the
software production process, analyze the requirements for a software system and produce a
software design from requirements, assess software productivity using metrics, use different
testing techniques used in software engineering to test software systems, manage the important
issues for planning a project.
Course Outlines:
Introduction to Software Engineering, Software Process Framework, Process Models, Agile
Software Process, Software Engineering Practices, System Engineering, Requirements
Engineering, Analysis Modelling, Design Engineering, Architectural Design, Component
Design, User Interface Design, Testing Strategies, Testing Tactics, Product and Process, Metrics,
Project Management, Project Estimation, Project Scheduling, Risk Management, Quality
Management, Change Management.
Reference Material:
9
Study Scheme BS(CS)
1. “Software Engineering: A Practitioner's Approach”, Roger Pressman, McGraw-Hill
2. “Software Engineering”, Ian Sommerville. Addison-Wesley, 2001 (7th edition).
3. “UML Distilled”.
Course Name: Computer Communication and Networks
Course Structure: Lectures: 3, Labs: 0
Credit Hours: 3
Objectives: To introduce students to the concept of computer communications. Analog and
digital transmission. Network Layers, Network models (OSI, TCP/IP) and Protocol Standards.
Emphasis is given on the understanding of modern network concepts.
Course Outline: Analog and digital Transmission, Noise, Media, Encoding, Asynchronous and
Synchronous transmission, Protocol design issues. Network system architectures (OSI, TCP/IP),
Error Control, Flow Control, Data Link Protocols (HDLC, PPP). Local Area Networks and
MAC Layer protocols (Ethernet, Token ring), Multiplexing, Switched and IP Networks, Internetworking, Routing, Bridging, Transport layer protocols TCP/IP, UDP. Network security
issues. Programming exercises, labs or projects involving implementation of protocols at
different layers.
Reference Material:
1. “Introduction to Computer Networks”, A. S. Tanenbaum, Prentice Hall 2003
2. “Computer Networks and Internets”, Douglas E. Comer, Purdue University ISBN-10:
0136061273 ISBN-13: 9780136061274 Publisher: Prentice Hall 2008
3. “Data and Computer Communications”, W. Stallings, Macmillan Pub. , 8th Ed., 2006
4. “Data Communications and Networking” (4th edition), Behrouz A. Forouzan,
McGraw-Hill, 2006. ISBN-13: 978-0073250328
Course Name: Human Computer Interaction
Course Structure: Lectures: 2, Labs:1
Credit Hours: 3
Objectives: This course introduces the human issues of usability and its importance. It considers
the implications of human understanding on the usability of computer systems and the
importance of understanding the context of use. It describes guidelines for use of different media
and interface styles. Topics include Usability Design principals, standards and models,
evaluation techniques. Groupware, pervasive and ubiquitous applications.
Course Outlines: The Human, Computer and Interaction, Usability paradigm and principles,
Introduction to design basics, HCI in software process, Design rules, prototyping, evaluation
techniques, task analysis, Universal design and User support and Computer Supported
Cooperative Work. Introduction to specialized topics such as Groupware, pervasive and
ubiquitous applications.
Reference Material:
1. “Human-Computer Interaction, 3/E”, Alan Dix, Janet E. Finlay, Gregory D. Abowd,
Russell Beale, ISBN-10: 0130461091 ISBN-13: 9780130461094 Prentice Hall
2. “Designing the User Interface: Strategies for Effective Human-Computer Interaction”,
4/E Ben Shneiderman, Catherine Plaisant, ISBN-10: 0321197860 ISBN-13:
9780321197863 Publisher: Addison-Wesley
3. “Designing Interfaces: Patterns for Effective Interaction Design”, (2nd Ed.) Jennifer
Tidwell. Publisher: O'Reilly Media, 2011
10
Study Scheme BS(CS)
Course Name: Computer Organization and Assembly Language
Course Structure: Lectures: 2, Labs: 1
Credit Hours: 3
Prerequisites: Digital Logic Design
Objectives: The main objective of this course is to introduce the organization of computer
systems and usage of assembly language for optimization and control. Emphasis is given to
expose the low-level logic employed for problem solving while using assembly language as a
tool. At the end of the course the students should be capable of writing moderately complex
assembly language subroutines and interfacing them to any high level language.
Course Outline: Microprocessor Bus Structure: Addressing, Data and Control, Memory
Organization and Structure (Segmented and Linear Models), Introduction to Registers and Flags,
Data Movement, Arithmetic and Logic, Program Control, Subroutines, Stack and its operation,
Peripheral Control Interrupts, Interfacing with high level languages, Real-time application.
Objectives and Perspectives of Assembly Language, Addressing Modes, Introduction to the
Assembler and Debugger, Manipulate and translate machine and assembly code, Describe
actions inside the processing chip, Discuss operations performed by an instruction set, Write a
fully documented program, Using an assembler of choice.
Reference Material:
1. "Computer Organization & Architecture", 7th ed, W. Stallings, Prentice Hall, 2006.
2. “Assembly Language for Intel-based Computers”, 5th ed, Irvine, Prentice Hall, 2007.
3. “Computer Organization and Design, The Hardware/Software Interface”, 4th ed,
David A. Patterson and John L. Hennessy, 2008. Elsevier Publishers.
Course Name: Theory of Automata and Formal languages
Course Structure: Lectures: 3 Labs: 0
Credit Hours: 3
Prerequisites: Discrete Structures
Objectives: The course aims to develop an appreciation of the theoretical foundations of
computer science through study of mathematical & abstract models of computers and the theory
of formal languages. Theory of formal languages and use of various abstract machines as
‘recognizers’ and parsing will be studied for identifying/validating the synthetic characteristics
of programming languages. Some of the abstract machines shall also study as ‘Transducers’.
Course Outline: Finite State Models: Language definitions preliminaries, Regular
expressions/Regular languages, Finite automata (FAs), Transition graphs (TGs), NFAs, Kleene’s
theorem, Transducers (automata with output), Pumping lemma and non-regular language.
Grammars and PDA: Context free grammars, Derivations, derivation trees and ambiguity,
Simplifying CFLs , Normal form grammars and parsing, Decidability, Chomsky’s hierarchy of
grammars Turing Machines Theory: Turing machines, Post machine, Variations on TM, TM
encoding, Universal Turing Machine, Context sensitive Grammars, Defining Computers by
TMs.
Reference Material:
1. “An Introduction to Formal Languages and Automata”, 4th ed., Peter Linz, Jones &
Bartlett Publishers, 2006
2. “Theory of Automata, Formal Languages and Computation”, S. P. Eugene, Kavier,
2005, New Age Publishers, ISBN-10: 81-224-2334-5, ISBN-13: 978-81-224-2334-1.
3. “Introduction to Automata Theory, Languages, and Computation”, 2nd ed., John
11
Study Scheme BS(CS)
Hopcroft and Jeffrey Ullman, 2001, Addison-Wesley.
4. “Introduction to Languages and the Theory of Computation”, 3rd ed., John C. Martin
2002, McGraw-Hill Professional.
Course Name: Design and Analysis of Algorithms
Course Structure: Lectures: 3, Labs: 0
Credit Hours: 3
Prerequisites: Data Structures and Algorithms
Objectives: Detailed study of the basic notions of the design of algorithms and the underlying
data structures. Several measures of complexity are introduced. Emphasis to be on the structure,
complexity, and efficiency of algorithms.
Course Outline: Introduction; Asymptotic notations; Recursion and recurrence relations;
Divide-and-conquer approach; Sorting; Search trees; Heaps; Hashing; Greedy approach;
Dynamic programming; Graph algorithms; Shortest paths; Network flow; Disjoint Sets;
Polynomial and matrix calculations; String matching; NP complete problems; Approximation
algorithms.
Reference Material:
1. “Introduction to Algorithms”, T. H. Cormen, C. E. Leiserson, and R. L. Rivest, MIT
Press, McGraw-Hill, New York, NY, 2001.
2. “Algorithms in C++”, Robert Sedgewick
Course Name: Artificial Intelligence
Course Structure: Lectures: 2, Labs: 1
Credit Hours: 3
Prerequisites: Discrete Structures
Objectives: This course studies four main objectives of AI. Modeling the environment by
constructing computer representations of the real world. Perception and reasoning - obtaining
and creating information/knowledge to populate a computational representation. Taking actions
by using the knowledge of the environment and desired goals to plan and execute actions.
Learning from past experience.
Course Outline: Artificial Intelligence: Introduction, Intelligent Agents. 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, Statistical 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.
Reference Material:
1. “Artificial Intelligence: Structures and Strategies for Complex Problem Solving”,
George F. Luger, 6th edition: Pearson Education, 2008.
2. “Artificial Intelligence: A Modern Approach”, Stuart Jonathan Russell, Peter Norvig,
John F. Canny, 2nd Edition, Prentice Hall, 2003.
12
Study Scheme BS(CS)
Course Name: Computer Architecture
Course Structure: Lectures: 3, Labs: 0
Credit Hours: 3
Prerequisites: Computer Organization and Assembly Language
Objectives: To get a deeper understanding of how computers work, working knowledge of
various subsystems and the general principles that affect their performance, analyze the
performance of systems and quantify the performance measurements, fundamentals of all
technologies, and advanced architectural features that boost the performance of computers.
Course Outlines: Fundamentals of Computer Design including performance measurements &
quantitative principles, principles of Instruction Set Design, Operands, addressing modes and
encoding, pipelining of Processors: Issues and Hurdles, exception handling features, InstructionLevel Parallelism and Dynamic handling of Exceptions, Memory Hierarchy Design, Cache
Design, Performance Issues and improvements, Main Memory Performance Issues, Storage
Systems, Multiprocessors and Thread Level Parallelism. Case Studies.
Reference Material:
1. “Computer Architecture: A Quantitative Approach”, Hennessy & Patterson, Morgan
& Kauffman Series (2006) Fourth Edition.
2. “Computer Organization and Design: The Hardware/Software Interface”, Patterson &
Hennessy, Morgan & Kauffman Series 2008.
Course Name: Compiler Construction
Course Structure: Lectures: 2, Labs: 1
Credit Hours: 3
Prerequisites: Theory of Automata and Formal Languages
Objectives: To understand the overall structure of compilers and to know significant details of a
number of important techniques commonly used in parsing. The students will get awareness of
the way in which language features raise challenges for compiler builders.
Course Outline: Contrast between compilers and interpreters. Organization of compilers.
Compiler techniques and methodology. Lexical and syntax analysis. Parsing techniques. Object
code generation and optimization, detection and recovery from errors.
Reference Material:
1. “Compilers: Principles, Techniques, and Tools”, Alfred V. Aho, Ravi Sethi, Jeffrey D.
Ullman, Addison-Wesley Pub. Co., 2nd edition,1987
2. “Modern Compiler Implementation in C”, Andrew W. Appel, Maia Ginsburg,
Cambridge University Press, 2004.
3. “Modern Compiler Design”, Dick Grune, Henri E. Bal, Ceriel J. H. Jacobs, Koen G.
Langendoen, 2003, John Wiley & Sons.
Course Name: Software Project
Course Structure: Lectures: 0, Labs: 6
Credit Hours: 6
Objectives: The software project involves research, conceive, plan and develop a real and
substantial project related to computer science. It provides an opportunity to the students to
crystallize their acquired professional competence in the form of a demonstrable software
product. Includes oral and written project presentations.
Reference Material:
1. “Software Project Management in Practice”, Pankaj Jalote. Addison-Wesley 2002.
13
Study Scheme BS(CS)
Description of Elective Courses
Course Name: Computer Graphics
Course Structure: Lectures: 2, Labs: 1
Credit Hours: 3
Objectives: Study of various algorithms in computer graphics and their implementation in
any programming language.
Course Outline: Graphics hardware. Fundamental algorithms. Applications of graphics.
Interactive graphics programming — graph plotting, windows and clipping, and
segmentation. Programming raster display systems, Differential Line Algorithm, panning and
zooming. Raster algorithms and software — Scan-Converting lines, characters and circles.
Scaling, Rotation, Translation, Region filling and clipping. Two and three dimensional
imaging geometry (Perspective projection and Orthogonal projection) and transformations.
Curve and surface design, rendering, shading, colour and animation.
Reference Material:
1. “Computer Graphics, Principles and Practice,” J. D. Foley, A. van Dam, S. K.
Feiner and J. F. Hughes, Addison-Wesley ISBN: 0-201-12110-7.
2. “Computer Graphics”, F.S.Hill, Maxwell MacMillan ISBN: 0-02-354860-6.
3. “Interactive Computer Graphics: Functional, Procedural and Device-level
methods”, Peter Burger and Duncan. F. Gillies; Addison-Wesley, (2003)
Course Name: Digital Image Processing
Course Structure: Lectures: 2 Labs: 1
Credit Hours: 3
Objective: The aim of this course is to understand the main terms & concepts of image
processing systems & their techniques.
Course Outline: Digital Imaging. Image analysis and filtering. Restoration in the Presence
of Noise Only–Spatial Filtering, Mean Filters, Order-Statistics Filters, Adaptive Filters,
Periodic Noise Reduction by Frequency Domain Filtering, Bandreject Filters, Bandpass
Filters, Notch Filters. Estimating the Degradation Function, Estimation by Image
Observation, Estimation by Experimentation, Estimation by Modeling, Inverse Filtering,
Minimum Mean Square Error (Wiener) Filtering. Image Segmentation, Detection of
Discontinuities, Point Detection, Line Detection, Edge Detection, Edge Linking and
Boundary Detection, Local Processing, Global Processing via the Hough Transform.
Thresholding, The Role of Illumination, Basic Global Thresholding, Basic Adaptive
Thresholding, Local Thresholding, Thresholds Based on Several Variables. Region-Based
Segmentation, Region Growing, Region Splitting and Merging.
Course Name: Computer Vision
Course Structure: Lectures: 3 Labs: 0
Credit Hours: 3
Prerequisites: Data Structures and Algorithms
Objectives: By the end of this course Students will be able to explain the concepts behind
computer based recognition and the extraction of features from raster images. Students will
also be able to illustrate some successful applications of vision systems and will be able to
identify the vision systems limitations.
14
Study Scheme BS(CS)
Course Outlines: Concepts behind computer-based recognition and extraction of features
from raster images. Applications of vision systems and their limitations. Overview of early,
intermediate and high level vision, Segmentation: region splitting and merging; quadtree
structures for segmentation; mean and variance pyramids; computing the first and second
derivatives of images using the isotropic, Sobel and Laplacian operators; grouping edge
points into straight lines by means of the Hough transform; limitations of the Hough
transform; parameterization of conic sections. Perceptual grouping: failure of the Hough
transform; perceptual criteria; improved Hough transform with perceptual features; grouping
line segments into curves. Overview of mammalian vision: experimental results of Hubel and
Weisel; analogy to edge point detection and Hough transform; Relaxation labeling of
images: detection of image features; Grouping of contours and straight lines into higher order
features such as vertices and facets. Depth measurement in images.
Reference Material:
1. “Computer Vision: A Modern Approach”, David Forsyth, Jean Ponce, Prentice Hall,
2003.
2. “Computer Vision”, Linda G. Shapiro, George C. Stockman, Prentice Hall, 2001.
3. “Handbook of Mathematical Models in Computer Vision”, Nikos Paragios, Yunmei
Chen, Olivier Faugeras, Birkhäuser, 2006.
Course Name: Data Communications
Course Structure: Lectures: 3
Credit Hours: 3
Objectives: To provide knowledge of Data Communication and its different mechanisms.
Course Outlines: Introduction, Data and Network, Layers, OSI Model, Introduction to
Signals, Transmission Media, Digital Transmission, PAM, PCM, ASK, FSK, PSK, QAM,
Data Communication Techniques and technologies, Modulation, Multiplexing, Types of
errors, Data Communication Protocols, Current technologies being used for data
communication.
Reference Material:
1. “Data Communication and Networking”, 4th Ed, Behrouz A. Forouzan. McGraw-Hill
2. “Business Data Communication”, William Stallings.
Course Name: Distributed Computing
Course Structure: Lectures: 3 Labs: 0
Credit Hours: 3
Course Outlines: Why use parallel and distributed systems? Why not use them? Speedup
and Amdahl's Law, Hardware architectures: multiprocessors (shared memory), networks of
workstations (distributed memory), clusters (latest variation). Software architectures: threads
and shared memory, processes and message passing, distributed shared memory (DSM),
distributed shared data (DSD). Parallel Algorithms, Concurrency and synchronization, Data
and work partitioning, Common parallelization strategies, Granularity, Load balancing,
Examples: parallel search, parallel sorting, etc. Shared-Memory Programming: Threads,
Pthreads, Locks and semaphores, Distributed-Memory Programming: Message Passing,
MPI, PVM. Other Parallel Programming Systems, Distributed shared memory, Aurora:
Scoped behavior and abstract data types, Enterprise: Process templates. Research Topics.
15
Study Scheme BS(CS)
Reference Material:
1. “Parallel Programming: Techniques and Applications Using Networked Workstations
and Parallel Computers, 1/e”, B. Wilkinson and M. Allen. Prentice Hall, 1999.
2. “Advanced Programming in the Unix Environment”, W. Stevens, Addison Wesley,
1993.
Credit Hours: 3
Course Title: Network Security
Course Structure: Lectures: 3 Labs: 0
Course Outlines: Introduction; Cryptology and simple cryptosystems; Conventional
encryption techniques; Stream and block ciphers; DES; More on Block Ciphers; The
Advanced Encryption Standard. Confidentiality & Message authentication: Hash functions;
Number theory and algorithm complexity; Public key Encryption. RSA and Discrete
Logarithms; Elliptic curves; Digital signatures. Key management schemes; Identification
schemes; Dial-up security. E-mail security, PGP, S-MIME; Kerberos and directory
authentication. Emerging Internet security standards; SET; SSL and IPsec; VPNs; Firewalls;
Viruses; Miscellaneous topics.
Reference Material:
1. “Cryptography and Network Security”, W. Stallings, Prentice Hall PTR, Upper Saddle
River, NJ, 2003.
2. “Network Security: Private Communication in a Public World”, Kaufman, R. Perlman,
M. Speciner, Prentice Hall PTR, Upper Saddle River, NJ, 2002.
3. “Computer Security: Art and Science”, M. Bishop, Addison-Wesley, 2003.
4. “Cryptography: Theory and Practice”, Stinson, CRC Press, Boca Raton, FL, 1995.
5. “An Introduction to Cryptography”, Richard A. Mollin, Chapman and Hall/CRC, 2001.
6. “Applied Cryptography”, B. Schneier, John Wiley and Sons, NY, 1996.
7. “Handbook of Applied Cryptography”, A. Menezes, P. Oorshcot, and S. Vanstone, CRC
Press, Boca Raton, FL, 1997.
8. “Cryptography and Network Security”, Behrouz A. Forouzan. McGraw-Hill
Credit Hours: 3
Course Name: Wireless Networks
Course Structure: Lectures: 3 Labs: 0
Course Outlines: This course covers fundamental techniques in design and operation of
first, second, and third generation wireless networks: cellular systems, medium access
techniques, radio propagation models, error control techniques, handoff, power control,
common air protocols (AMPS, IS-95, IS-136, GSM, GPRS, EDGE, WCDMA, cdma2000,
etc), radio resource and network management. As an example for the third generation air
interfaces, WCDMA is discussed in detail since it is expected to have a large impact on
future wireless networks. This course is intended for graduate students who have some
background on computer networks.
Reference Material:
1. “Wireless Communications”, Theodore S Rappaport.
2. “Fundamentals of Wireless Communications”, David Tse.
3. “Wireless Communications and Networks”, W. Stallings, Prentice Hall, 2002.
16
Study Scheme BS(CS)
4.
5.
6.
7.
8.
“Wireless Communications: Principles & Practice”, T.S. Rappaport, Second Edition,
Prentice Hall, 2002.
“Mobile Communications”, J. Schiller, Addison Wesley, 2000.
“IS-95 CDMA and cdma 2000”, V.K. Garg, Prentice Hall PTR, 2000.
“The UMTS Network and Radio Access Technology - Air Interface Techniques for
Future Mobile Systems”, J.P. Castro, Wiley, 2001.
“WCDMA for UMTS Radio Access for Third Generation Mobile Communications”,
H. Holma and A. Toskala, John Wiley & Sons, 2001.
Course Name: Software Engineering II
Course Structure: Lectures: 3, Labs: 0
Credit Hours: 3
Objectives: To study various software development models and phases of software
development life cycle. The concepts of project management, change control, process
management, software development and testing are introduced through hands-on Team
Projects.
Course Outline: Introduction to Computer-based System Engineering; Project Management;
Software Specification; Requirements Engineering, System Modeling; Requirements
Specifications; Software Prototyping; Software Design: Architectural Design, ObjectOriented Design, UML modeling, Function-Oriented Design, User Interface Design; Quality
Assurance; Processes & Configuration Management; Introduction to advanced issues:
Reusability, Patterns; Assignments and projects on various stages and deliverables of SDLC.
Reference Material:
1. “Software Engineering”, Sommerville, Addison-Wesley, 2006
2. “Software Engineering: A Practitioner's Approach”, Roger Pressman, McGraw-Hill,
2009
Course Name: Systems Programming
Course Structure: Lectures: 2 Labs: 1
Credit Hours: 3
Prerequisites: Operating Systems
Objectives: Demonstrate mastery of the internal operation of Unix system software
including assemblers, loaders, macro-processors, interpreters, inter-process communication.
Course Outline: System Programming overview: Application Vs. System Programming,
System Software, Operating System, Device Drivers, OS Calls. Window System
Programming for Intel386 Architecture: 16 bit Vs 32 bit, Programming, 32 bit Flat memory
model, Windows Architecture. Virtual Machine(VM), System Virtual Machine, Portable
Executable Format, Ring O Computer, Linear Executable format, Virtual Device Driver (V +
D), New Executable format, Module Management, COFF obj format 16 bit. (Unix) other 32bit O.S Programming for I 386; Unix Binaryble format (ELF), Dynamic shared objects, Unix
Kernel Programming (Ring O), Unix Device Architecture (Character & Block Devices),
Device Driver Development, Enhancing Unix Kernel.
Reference Material:
1. “The UNIX Programming Environment”, B. Kernighan & R. Pike Prentice-Hall.
2. “System Software”, Leland L. Beck, Addison-Wesley Longman, 1990, ISBN: 0-20150945-8.
17
Study Scheme BS(CS)
Course Name: Distributed Database System
Course Structure: Lectures: 2, Lab:1
Credit Hours: 3
Prerequisites: Introduction to Database Systems
Objectives: To understand difference of Centralized database and Distributed database and
to enable the students to design/model a distributed database.
Course Outline: Introduction, Overview of relational DBMS and Normalization, Distributed
DBMS architecture, Distributed database design and Data Distribution Strategies,
Replication/Fragmentation, Distributed Transaction Management, Distributed Query
Processing, Distributed Concurrency Control, Distributed Data Security, Distributed
Database Recovery.
Reference Material:
1. “Principals of Distributed Database Systems”, Ozsu Tamer.
2. “Database Systems”, Thomas Connolly.
Course Name: Data Warehousing
Course Structure: Lecture: 3
Credit Hours: 3
Prerequisite: Introduction to Database Systems
Objective: Introduction of Data warehouse and its purpose; to enable students to understand
different features / issues in data warehousing and its designing.
Course Outline: Introduction to Data Warehouse and Data Marts, Comparison of OLTP
Systems & Data Warehousing, Data Warehouse Architecture, Dimensional Modeling,
Comparison Of DM & ER Models, Extraction, Cleansing and Loading process and
techniques, Designing a Data warehouse, End user tools, OLAP.
Reference Material:
1. “Data Warehouses and OLAP Concepts, Architecture and Solutions”, Wrembel
2. “Data Warehousing: Architecture and Implementation”, Humphries
3. “Data Warehousing: Design, Development & Best Practices”, Mohanty
18
×

Report this document