Download Department of Information Technology MCA

Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
M.C.A.- 4th Semester
Sl.
No
1
Code
ITP1 2413
2
3
Theory
practical
Credits
Data Warehousing & Data
Mining
4
-
4
ITP1 2414
Mobile Computing
4
-
4
ITP1 2415
Unix Programming
4
-
4
4
-
4
4
Subject
Elective-1
ITP1 2416
Artificial Intelligence
ITP1 2417
Distributed Operating Systems
ITP1 2418
Embedded Systems
5
Elective-2
4
ITP1 2419
Bio Informatics
ITP1 2420
Cloud Computing
ITP1 2421
Open Source Software
6
ITP1 2207
Data Warehousing & Mining
Laboratory
-
7
ITP1 2208
Mini Project
-
Total Credits
4
3
2
2
24
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: DATA WAREHOUSING AND DATA MINING
Course Code: ITP1 2413
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Course objectives : Students undergoing this course are expected to:
• Differentiate OnLine Transaction Processing and OnLine Analytical processing
• Learn Multidimensional schemas suitable for data warehousing
• Understand various data mining functionalities
• Inculcate knowledge on data mining query languages.
• Know in detail about data mining algorithms
Course outcomes : After undergoing the course, Students will be able to understand
• Design a data mart or data warehouse for any organization
• Develop skills to write queries using DMQL
• Extract knowledge using data mining techniques
• Adapt to new data mining tools.
• Explore recent trends in data mining such as web mining, spatial-temporal mining
UNIT- I
15 Hrs
Introduction : Fundamentals of data mining, Data Mining Functionalities, Major issues in Data Mining
Data Preprocessing: Needs Preprocessing the Data, Data Cleaning, Data Integration andTransformation, Data
Reduction, Data Warehouse and OLAP Technology for Data Mining Data Warehouse, Multi-dimensionalData
Model, Data Warehouse Architecture, Data Warehouse Implementation.
UNIT-II
14 Hrs
Data Mining Primitives, Languages, and System Architectures : Data MiningPrimitives, Data Mining
Query Languages, Designing Graphical User Interfaces Based on a Data Mining Query Language,Architectures
of Data Mining Systems.
Concepts Description : Characterization and Comparison : Data Generalization andSummarization-Based
Characterization, Analytical Characterization: Analysis of AttributeRelevance, Mining Class Comparisons:
Discriminating between Different Classes
UNIT- III
16 Hrs
Mining Association Rules in Large Databases :Association Rule Mining, Mining Single-Dimensional
Boolean Association Rules from Transactional Databases, Mining MultilevelAssociation Rules
\
fromTransaction Databases, Mining Multidimensional Association Rulesfrom Relational Databases and Data
Warehouses
Classification and Prediction : Issues Regarding Classification and Prediction,Classification by Decision Tree
Induction, Bayesian Classification, Classification byBackpropagation, , OtherClassification Methods,
Prediction, Classifier Accuracy.
UNIT IV
15 Hrs
Cluster Analysis Introduction : Types of Data in Cluster Analysis, A Categorization ofMajor Clustering
Methods, Partitioning Methods, Density-Based Methods, Grid-BasedMethods, Model-Based Clustering
Methods, Outlier Analysis.
Mining Complex Types of Data :Multidimensional Analysis and Descriptive Mining ofComplex, Data
Objects, Mining Spatial Databases, Mining Multimedia Databases, MiningTime-Series and Sequence
Data,Mining Text Databases, Mining the World Wide Web.
Text Books:
1. Data Mining – Concepts and Techniques - JIAWEI HAN & MICHELINE KAMBER Harcourt
India.
Reference Books:
1. Data Mining Introductory and advanced topics –MARGARET H DUNHAM, PEARSON
EDUCATION
2. Data Mining Techniques – ARUN K PUJARI, University Press.
3. Data Warehousing in the Real World – SAM ANAHORY & DENNIS MURRAY. Pearson Edn .
4 Data Warehousing Fundamentals – PAULRAJ PONNAIAH WILEY STUDENT EDITION.
5. The Data Warehouse Life cycle Tool kit – RALPH KIMBALL WILEY STUDENT EDITION.
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: MOBILE COMPUTING
Course Code: ITP1 2414
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Course objectives :Students undergoing this course are expected to:
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The student learns about the mobile architecture
The subject makes student to understand about how to interact even on move as roaming.
Student understands blue tooth architecture and functionality.
Security implementation in wireless network communication is acknowledged by student.
Course outcomes : After undergoing the course, Students will be able to understand
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How to implement multiple access and overcome the problems of hidden, exposed, far and near.
Routing methods and handover process in mobile networks
How to transmit an IP packet and optimization of its transmission
How to implement blue tooth architecture.
UNIT – I
16 Hrs
Mobile Computing (MC) : Introduction to MC,, limitations, and architecture GSM : Mobile services, System
architecture, Radio interface, Protocols, Localization and calling, Handover, Security. Motivation for a
specialized MAC (Hidden and exposed terminals, Near and far terminals), SDMA, FDMA, TDMA, CDMA.
UNIT – II
14 Hrs
Mobile Network Layer : Mobile IP (Goals, assumptions, entities and terminology, IP packet delivery, agent
advertisement and discovery, registration, tunneling and encapsulation, optimizations), Dynamic Host
Configuration Protocol (DHCP).
UNIT – III
15 Hrs
Mobile Transport Layer : Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP, Fast retransmit/ fast
recovery, Transmission /time-out freezing, Selective retransmission, Transaction oriented TCP, Overview and
Properties of a MANET,
spectrum of MANET applications ,routing and various routing algorithms, security in MANETs.
UNIT – IV
15 Hrs
Wireless Application Protocol-WAP. (Introduction, protocol architecture, and treatment of protocols of all
layers), Bluetooth (User scenarios, physical layer, MAC layer, networking, security, link management) and
J2ME.
TEXT BOOKS :
1. Jochen Schiller,“Mobile Communications”,Addison-Wesley. (Chapters
4,7,9,10,11),second edition, 2004.
REFERENCES :
1. Reza Behravanfar, “Mobile Computing Principles: Designing and Developing Mobile Applications with
UML and XML”, ISBN: 0521817331, Cambridge University Press, October 2004,
2. Hansmann, Merk, Nicklous, Stober, “Principles of Mobile Computing”, Springer, second edition, 2003.
3. Martyn Mallick, “Mobile and Wireless Design Essentials”, Wiley DreamTech, 2003.
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: UNIX PROGRAMING
Course Code: ITP1 2415
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Course objectives :
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Students undergoing this course are expected to:
Know about UNIX operating system
know about important commands which are used in UNIX
Learn about shell programming in UNIX
Understand inter-process communication tools
Course outcomes :
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After undergoing the course, Students will be able to understand
UNIX/LINUX Operating System
UNIX commands
How to write shell programming
How to establish communication through IPC tools
UNIT- I UNIX Commands and Shell programming
15 Hrs
File-handling utilities, security by file permissions, process utilities, disk utilities, networking commands,
backup utilities, text processing utilities, Introduction about shell, working with bourn shell, shell
responsibilities shell variables, control structures, shell script examples
UNIT-II UNIX file Structure, System Calls, Standard I/O Formatted I/O
14 Hrs
Unix file structure, and type of files. File handling system (open, creat, read, write, close, lseek, stat, fstat, octl,
umask,dup,dup2). The standard I/O(fopen, fclose, fflush, fseek, fgetc, getc, getchar, fputc, putc, putchar,
fgets,gets), formatted-I/O, stream errors, streams and file descriptors, file and directory maintenance (chmod,
chown, unlink, link, symlink,mkdir, rmdir ,chdir, getcwd), Directory handling system calls (opendir, readdir,
closedir, rewinddir, seekdir, telldir).
UNIT- III: UNIX Process, Threads and Record Locking:
14 Hrs
Threads and Signals: What is process, process structure, system calls for process-management (fork, vfork, exit,
wait, waitpid, exec, and system) and zombie-process. Threads, Thread-creation, waiting for a thread to
terminate, threads vs. processes, Signals, Signal functions, unreliable signals, interrupted system-calls, kill and
raise functions, alarm, pause functions, abort, sleep functions. File and record locking (creating lock-files,
locking regions, use of read /write locking, competing locks, other commands, deadlocks).
UNIT IV
16 Hrs
Inter-Process Communication:
Inter-processCommunication: Introduction to IPC, IPC between processes on a single computer system, IPC
between processes on different systems, pipes, FIFO’s. Message-Queues: IPC, permission issues, Access
permission modes, message structure, working message queues, UNIX system V messages, UNIX kernel
support for messages, Unix APIs for messages, client/server example. Shared-Memory: UNIX system-V
API for Shared memory, working with shared memory segment. Semaphores: UNIX system V API for
semaphores, file-locking with semaphores. Semaphore and shared memory example using semaphores.
Text Books:
1. Unix Concepts and Applications, 3/e, Sumitabha Das, TMH
2. Advanced UNIX Programming, Richard Stevens.
3. Advanced Programming in the UNIX Environment: Second Edition By W. Richard Stevens,
Stephen A. Rago
Reference Books:
1. Unix and shell Programming, Sumitabha Das, TMH
2. A Beginner’s Guide to Unix, N.P.Gopalan, B.Sivaselva, PHI
3. UnixShellProgramming,StephenG.Kochan,PatrickWood,3/e, Pearson
4. Unix and shell Programming, NB Venkateswarlu, Reem, NewDelhi
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
ELECTIVE -I
Course Title: ARTIFICIAL INTELLIGENCE
Course Code: ITP1 2416
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Course objectives:
Students undergoing this course are expected to:
• Understand the AI problems and techniques.
• Know the different heuristic search techniques.
• Represent the knowledge in different forms.
• Know the different ways of planning and natural language understanding.
• Realize the different methods of learning.
Course outcomes:
After undergoing the course, Students will be able to:
• Use the heuristic search techniques for AI related problems.
• Represent knowledge in suitable forms for computer processing.
• Apply the natural language processing techniques to computer.
• Can apply the learning techniques to computer.
UNIT- I
16 Hrs
Introduction: AI problems, AI techniques, defining problem as a state space search, production systems,
problem characteristics, production system characteristics
Heuristic search techniques: Generate-and-test, hill climbing, best-first-search, problem reduction, constraint
satisfaction, means-ends-analysis
UNIT-II
15 Hrs
Knowledge representation: Issues, predicate logic, resolution, representing, knowledge using rules, forward
versus backward reasoning, matching, control knowledge, weak slot and filler structure- semantic nets, frames,
strong slot and filler structures-conceptual dependency, scripts
UNIT- III
15 Hrs
Game playing: mini-max search, alpha-beta cutoffs, planning system, goal stack planning, hierarchical
planning, understanding, understanding as constraint satisfaction, waltz algorithm, natural language processing,
syntactic processing, semantic analysis, case grammars
UNIT- IV
14 Hrs
Learning: Rote learning, learning by taking advice, learning in problem solving, learning from examples,
Winston’s learning program, decision trees, perception, vision, speech recognition, navigation, manipulation,
robot architecture, expert systems, shell, explanation, knowledge acquisition.
Text Books:
1. Artificial Intelligence, 2nd edition, E.Rich and K.Knight, TMH
2. Artificial Intelligence A modern Approach, Russel Norvig, Pearson Education
Reference Books:
1. Artificial Intelligence, third edition, Patrick henry Winston, Pearson Education Asia
2. Introduction to Artificial intelligence and Expert Systems, Dan W. Patterson, PHI
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: EMBEDDED SYSTEMS
Course Code: ITP1 2417
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Course objectives : Students undergoing this course are expected to:
• Learn the design process methods for Microprocessors and Microcontrollers.
• Understand 8051 Microcontroller Architecture.
• Explore the concepts of Assembly Level Language.
• Learn about interfacing with devices like keyboard, VDU, converters and so on.
• Know the Concepts of Real-Time Operating Systems
Course outcomes : After undergoing the course, Students will be able to understand
• Assembly Language Programs using all types of arithmetic, logical and data transfer instructions.
• Design of Interfaces for different Applications such as Displays, Keyboards etc.
• Development of simple Embedded Systems
• Implementation of a microcontroller such as Elevator using advanced processor Concepts.
UNIT- I
14 Hrs
Embedded Computing : Introduction, Complex Systems and Microprocessor, The Embedded System Design
Process, Design Examples.
The 8051 Architecture : Introduction, 8051 Micro controller Hardware, Input/Output Ports and Circuits,
External Memory, Counter and Timers, Serial data Input/Output, Interrupts.
UNIT-II
16 Hrs
Basic Assembly Language Programming Concepts : Programming the 8051. Data Transfer and Logical
Instructions, Arithmetic Operations, Decimal Arithmetic. Jump and Call Instructions
Applications : Interfacing with Keyboards, Displays, D/A and A/D Conversions
UNIT- III
14 Hrs
Introduction to Real – Time Operating Systems : Tasks and Task States, Tasks and Data, Semaphores, and
Shared Data; Message Queues, Mailboxes and Pipes, Timer Functions, Events, Memory Management, Interrupt
Routines in an RTOS Environment. Introduction to ARM and SHARC, Processor
UNIT IV
16 Hrs
Basic Design Using a Real-Time Operating System : Principles, Semaphores and Queues, Hard Real-Time
Scheduling Considerations, Saving Memory and Power, An example RTOS like uC-OS (Open Source);
Embedded Software Development Tools: Host and Target machines, Linker/Locators for Embedded Software,
Getting Embedded Software into the Target System; Debugging Techniques: Testing on Host Machine.
Text Books:
1. Computers as Components-principles of Embedded computer system design, Wayne Wolf, Elseveir.
2. The 8051 Microcontroller, Third Edition, Kenneth J.Ayala, Thomson.
Reference Books:
1. Embedding system building blocks, Labrosse, via CMP publishers.
2. Embedded Systems, Raj Kamal, TMH.
3. Embedded System Design, Frank Vahid, Tony Givargis, John Wiley.
4. An Embedded Software Primer, David E. Simon, Pearson Education.
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: DISTRIBUTED OPERATING SYSTEMS
Course Code: ITP1 2418
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Course objectives : Students undergoing this course are expected to:
• Learn the basic concepts upon which distributed systems at large and distributed operating systems
• Create awareness about overall architecture of distributed systems
• Focus on design issues, design problems, solutions and performance issues of distributed systems
Course outcomes :After undergoing the course, Students will be able to understand
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About effective distribution of data in a network.
To choose suitable operating system for distribution of data.
Learn about different data consistency models.
UNIT- I :
14 Hrs
Processes: Introduction to Threads, Threads in Distributed Systems; CODE MIGRATION: Approaches to
Code Migration, Migration and Local Resources, Migration in Heterogeneous Systems, Example: D'Agents ,
Introduction to Software Agents in Distributed Systems, Agent Technology.
Naming Systems: Naming Entities: Names, Identifiers, and Addresses, Name Resolution, The Implementation
of a Name Space, Example: DNS, X.500
UNIT-II :
16 Hrs
Synchronization:Clock synchronization, logical clocks, global state, election algorithms, mutual exclusion,
distributed transactions.
Consistency and Replication:Introduction, Data-Centric Consistency Models, Client-Centric Consistency
Models, Distribution Protocols, Consistency Protocols.
UNIT- III:
14 Hrs
Fault Tolerance: Introduction to Fault Tolerance, Process Resilience, Reliable Client-Server Communication,
Reliable Group Communication, Distributed Commit, Recovery.
Distributed Object-Based Systems:CORBA, Distributed Com, Globe and Comparison of CORBA, DCOM,
and Globe.
UNIT IV:
16 Hrs
Distributed File Systems:Sun Network File System, Coda File System, XFS and SFS, Scalable Security.
Distributed Document-Based Systems and Coordination-Based Systems:Distributed Document-Based
Systems: The World Wide Web, Lotus Notes.Distributed Coordination-Based Systems: Introduction to
Coordination Models, TIB/Rendezvous, JINI, Comparison of TIB/Rendezvous and JINI.
Text Books:
1. Distributed Systems , Principles and Paradigms, 2/e, Tanenbaum, Maarten Van Steen, PHI.
2. Advanced concepts in Operating Systems, MukeshSinghal, Niranjan G. Shivaratri, TMH, 2005.
Reference Books:
1. Distributed Operating Systems and Algorithm Analysis, Chow, Johnson, PEA
2. Operating Systems, Internals & Design Principles, 6/e, William Stallings, PEA.
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
ELECTIVE -II
Course Title: BIOINFORMATICS
Course Code: ITP1 2419
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Course objectives : Students undergoing this course are expected to:
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Understand the basic concepts and techniques of Bioinformatics.
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Develop an awareness of the computational problems that arise in the modeling and analysis of living
systems.
Understand basic abstractions and computational approaches used to formulate and address
these problems.
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Course outcomes : After undergoing the course, Students will be able to understand
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Sequencing Alignment and Dynamic Programming
Sequence Databases
UNIT- I
14 Hrs
Introduction to Bioinformatics: Scope of Bioinformatics, Elementary commands and protocols, ftp, telnet, http.
Primer on information theory.
Introduction to Homology : Introduction to Homology (with special mention to Charles Darwin, Sir Richard
Owen, Willie Henning, Alfred Russel Wallace).
UNIT-II
16 Hrs
Special Topics In Bioinformatics : DNA mapping and sequencing, Map alignment, Large scale sequencing
methods Shotgun and Sanger method.
Sequencing Alignment and Dynamic Programming : Heuristic Alignment algorithms. Global sequence
alignments-Neddleman-Wunsch Algorithm Smith-Waterman Algorithm-Local sequence alignments (Amino
acid substitution Matrices (PAM, BLOSUM).
UNIT- III
16 Hrs
Primary Database and their Use : Introduction to Biological databases, Organization and management of
databases. Searching and retrieval of information from the World Wide Web. Structure databases-PDB (Protein
Data Bank), Molecular Modeling Databases (MMDB). Primary Databases NCBL,EMBL, DDBJ.
Secondary Databases : Introduction to Secondary Databases Organization and management of databases
Swissprot, PIR,KEGG
UNIT IV
14 Hrs
Bio Chemical Data Bases : Introduction to BioChemical databases-organization and Management of databases.
KEGG, EXGESCY, BRENDA, WIT.
Introduction to Multiple sequence alignment.
TEXT BOOKS :
1. Bioinformatics Basics. Applications in Biological Science and Medicine by Hooman H. Rashidi and Lukas
K.Buehler CAC Press 2000.
2. Algorithms on Strings Trees and Sequences Dan Gusfiled. Cambridge University Press 1997.
REFERENCES :
1. Bioinformatics: A Machine Learning Approach P. Baldi. S. Brunak, MIT Press 1988.
2. Bioinformatics. David Mount, 2000. CSH Publications
3. Developing Bioinformatics Skills. Cynthia Gibbas & Per Jamberk
4. Genomics and Proteomics-Functional and Computational aspects. Springer Publications. Editior-Sandor
Suhai.
5. Bioinformatics- Methods and Protocols-Human Press. Stephen Misener, Stephen A. Krawetz.
6. Computational Biochemistry - C.Stan ,TSAI WILEY Publications.
7. Bioinformatics - A Practical guide to the Analysis of Genes and Proteins Andreas D.Baxevanis, B.F. Francis Ouellette.
8. Bioinformatics - Principles and Applications - Harshawardhan P.Bal Tata Megraw Hill.
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: CLOUD COMPUTING
Course Code: ITP1 2420
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Course objectives : Students undergoing this course are expected to:
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Inculcate knowledge on Centralized and Distributed Computing.
Understand Transparency and Fragmentation in Distributed Computing
Learn about transaction management, concurrency control, and reliability in Distributed
Computing
Create awareness on the major technical challenges in distributed systems design and
implementation.
Course outcomes : After undergoing the course, Students will be able to understand
• Decomposition of global relations into fragments.
• Concepts of transaction management, concurrency control in Distributed Computing, Resource
finding, Resource Utilization etc.
• principles applied in contemporary distributed database systems
• Proper Utilization of Resources available in the cloud
UNIT- I
16 Hrs
Introduction to Virtualization and Virtual machine – SOA- Cloud Computing: Introduction, Cloud Application
Architectures, Value of Cloud Computing, Cloud Infrastructure models, Scaling a Cloud Infrastructure,
Capacity Planning, Cloud Scale
UNIT-II
16 Hrs
Security: Disaster Recovery, Web Application Design, Machine Image Design, Privacy Design, Database
Management, Data Security, Network Security, Host Security, Compromise Response.
UNIT- III
16 Hrs
Defining Clouds for the Enterprise – Storage-as-a-Service, Database-as-a-Service, Information-as-a-Service,
Process-as-a-Service, Application-as-a-Service, Platform-as-a-Service, Integration-as-a-Service, and Securityas-a-Service.
UNIT IV
12 Hrs
Disaster Recovery, Disaster Recovery, Planning, Cloud Disaster Management, Case Study: Types of Clouds –
Eucalyptus, Amazon
Text Books:
1) Cloud Computing – Web Based Applications that change the way you work and collaborate onlineMichael Miller, Pearson Education.
2) Cloud Application Architectures, 1st Edition by George Reese O’Reilly Media.
Reference Books:
1) Cloud Computing and SOA Convergence in Your Enterprise: A Step-by-Step Guide David S Linthicum
Addison-Wesley Professional.
2) Distributed & Cloud Computing from Parallel Processing to the Internet of Things by Kai Hwang.
Geoffrey C Fox.Jack J.Dongarra.
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: OPEN SOURCE SOFTWARE
Course Code: ITP1 2421
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Course objectives :
Students undergoing this course are expected to:
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Choose appropriate programming language for the given problem definitions.
Use imperative (or procedural), an object-oriented, a functional, and a logical programming language.
Expose programming concepts and choose best way to express things that simulate useful features
Design new open source software.
Make good use of debuggers and related tools.
Course outcomes :
After undergoing the course, Students will be able to understand
• Understand the significance of an implementation of a programming language in system software
• Usage of imperative, an object-oriented, a functional, and a logical programming language approaches.
• The purpose of Open Source Software.
• The implementation of Programming Language.
• Download and learn open source databases.
• Design of new programming language.
UNIT- I
14 Hrs
INTRODUCTION: Introduction Open Sources – Need of Open Sources – Advantages of Open Sources –
Application of Open Sources. Open Source Operating Systems: LINUX: Introduction – General Overview –
Kernel Mode and User Mode - Signals.
UNIT-II
16 Hrs
Open Source DataBase: MySQL: Introduction – Setting up Account – Starting, terminating and writing you
own SQL programs – Record selection Technology – Working with strings – Date and Time – Sorting Query
Results – Generating Summary – Working with Metadata – Usings equences – MySQL and Web.
UNIT- III
14 Hrs
PYTHON: Syntax and Style – Python Objects – Numbers – Sequences – Strings – Lists and Tuples –
Dictionaries – Conditional and Loops – Files – Input & Output – Errors and Exceptions.
UNIT IV
16 Hrs
PERL: PERL Background – PERL Overview – PERL parsing rules – Variables and Data – Statement and
Control Structures – Subroutines, Packages and Modules – Working with Files – Data Manipulation.
Text Books:
1) Remy Card, Eric Dumas and Frank Mevel, “The Linux Kernel Book”, Wiley Publications, 2003.
2) Steve Suchring, “MySQL Bible”, John Wiley, 2002
3) Wesley J Chun, “Core Phython Programming”, Prentice Hall, 2001
4) Martin C Brown, “PERL: The Complete Reference”, 2nd Edition, Tata McGraw-Hill Publishing
Company Limited, Indian Reprint 2009.
Reference Books:
1) Vikram Vaswani,”MySQL: The Complete Reference”, 2nd Edition, Tata McGraw-Hill Publishing
Company Limited, Indian Reprint, 2009.
Department of Information Technology
M.C.A.- 4th Semester
COURSE STRUCTURE
(Applicable for 2012-13 admitted batch)
Course Title: DATA WAREHOUSING AND DATA MINING LAB
Course code: ITP1 2207
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Course Objectives: This lab course is intended to
Introduce data mining techniques including predictive, descriptive and visualization modeling and their
effective use in discovering interesting hidden patterns in large volume of data generated by businesses,
science, web, and other sources. Focus is on the main process of data mining such as data preparation,
classification, clustering, association analysis, and pattern evaluation
Course outcomes: After undergoing the course students will be able to:
• Synthesize the data mining fundamental concepts and techniques from multiple perspectives.
• Develop skills and apply data mining tools for solving practical problems
• Advance relevant programming skills.
• Gain experience and develop research skills by reading the data mining literature.
List of Experiments
1. Study of WEKA tool and applying data mining techniques on following data sets in ARFF file Format
i.e customer’s data, weather forecasting data, agricultural data etc.
2. Implementation / Usage of WEKA for classification of above mentioned data set.
3. Implementation / Usage of WEKA for prediction of above mentioned data set.
4. Study of Meta edits tool and drawing diagram for the problem statement: Any Hotel management
system and employer management in pharmaceutical company.
5. Usage of METAEDIT tool for making E-R diagrams for the above problem statement.
6. Usage of METAEDIT tool for state transaction for the above problem statement.
7. Study of AR miner Tool.
8. Usage of AR miner for data warehouse.
9. Study of DB miner Tool.
10. Implementation of various classification algorithms like decision tree, neural networks.
11. Comparison of various databases such as Oracle, Sybase.
12. Comparison of various data mining tools.