VII Semester Syllabus (PDF)




File information


Author: Aravind

This PDF 1.7 document has been generated by Microsoft® Word 2016, and has been sent on pdf-archive.com on 28/12/2017 at 08:36, from IP address 157.49.x.x. The current document download page has been viewed 700 times.
File size: 718.95 KB (14 pages).
Privacy: public file
















File preview


School of Engineering and Technology
Jain Global Campus

Jakkasandra Post, Kanakapura Taluk, Ramanagara District
Pin Code: 562 112

JAIN UNIVERSITY
Decl a red as D eemed -to -b e Un i ver s i ty u / s 3 o f th e UG C Act 19 56

Bachelor of Engineering
In
Department of Information Science and
Engineering
Course Matrix & Syllabus
For VII Semesters
Batch: 2014-2019

Date: __________

Head of the Department

1

School of Engineering and Technology
Jain Global Campus

Jakkasandra Post, Kanakapura Taluk, Ramanagara District
Pin Code: 562 112

JAIN UNIVERSIT

Declared as Deemed-to-be University u/s 3 of the UGC Ac

2014 - Onwards
Department of Information Science and Engineering
Course Matrix
B.Tech in Information Science and Engineering
VII Semester

ubject
Code

Name of the Subject

4IS 71

Credit

L–T–P

Engineering & Management Technology

3

4IS 72

Web Technologies

4IS 73

Data Mining

4IS 74

Internal
Assessment

End Semester
Examinations

Max.
Marks

Min.
Marks

Max.
Marks

Min.
Marks

3-0-0

30

-

70

28

4

4-0-0

30

70

28

4

4-0-0

30

70

28

Cloud Computing

4

4-0-0

30

70

28

70

28

70

28

Elective – 2

4

4-0-0

30

IS 76XX

Elective – 3 (open)

4

4-0-0

30

-

4ISL77

Technologies Web Lab

1

0-0-3

100*

-

-

-

4ISL78

Parallel Computing Lab

1

0-0-3

100*

-

-

-

4IS79

Project Work Phase – I

4

---

100*

-

-

-

IS 75X

Total

29

Elective – 2
Sl.
No.

480

420

Elective – 3 (OPEN)

Subject
Code

Name of the Subject

Sl.
No.

Subject
Code

Name of the Subject

1
2

14IS 751

Soft Computing

1

14IS7605

Bio Informatics

14IS752

Internet of Things

2

14IS7606

Storage Area
Networks

3

14IS753

Distributed Systems

* - Continuous Assessment (CA)

Date: ________________________

Head of the Department

2

ENGINEERING AND MANAGEMENT TECHNOLOGY
Course Code: 14CS/IS71
Credits: 3
L-T-P : 3-0-0

Total No of Hrs: 45
Hours per week: 03
Maximum Marks: 70

PREREQUISITES
• Student should have the knowledge of basic mathematics, probability, statistics and software
engineering
COURSE OBJECTIVES
• To analyze the characteristics and contributions of enterprising people, To assess their own
entrepreneurial and enterprising potential, To analyze the characteristics and contributions of Project
Manager.
• To develop an understanding of the general role of Small Business Enterprises, To develop skills to
start, run and manage SMEs, Manage projects, people, and resources effectively.
• Plan, design, analyze, implement, and improve cost-effective manufacturing/service systems.
• Build and use management tools to analyze and solve problems effectively and make decisions from a
systems perspective.
• Communicate effectively in verbal, written, and graphic forms, Pursue professional growth and interact
effectively in work environments.
________________________________________________________________________
COURSE CONTENT
PART-A
UNIT 1
6 Hours
Foundations of Information Systems in Business : Introduction to Information Systems in Business,
Why study Information Systems?: What you need to know, A global Information society, Success and
Failure with IT, Why Business need Information Technology.
Fundamentals of Information Systems : Fundamental of Information Systems concepts: System
concepts, Components of an Information System, Information System Resources, Information Systems
activities, Overview of Information Systems: The expanding role of Information Systems, Operations
support Systems, Management support Systems, Other classification of Information Systems.
UNIT 2
7 Hours
Planning and Forecasting: Preview, Nature of Planning, The foundations for planning, Some Planning
concepts, Forecasting, Strategies for Managing Technology.
Decision Making: Preview, Nature of Decision Making, Management Science, Tools for Decision Making,
Computer-Based Information Systems, Implementation.
UNIT 3
7 Hours
Organizing: Preview, Nature of Organizing, Traditional organization Theory, Technology and Modern
Organization Structures, Teams.
Some Human Aspects of Organizing: Preview, Staffing Technical Organizations, Authority and Power
Delegation, Committees and Meetings.
UNIT 4
5 Hours
Motivating and Leading Technical People: Preview, Motivation, Leadership, Motivating and Leading
Technical Professionals. Controlling preview, The Process of Control, Financial Controls, Non-financial
Controls
PART-B
UNIT 5
5 Hours
Managing Engineering Design: Preview, Nature of Engineering Design, Systems Engineering/ New
Product Development, Concurrent Engineering and CALs , Control System in Design, Product Liability and
Safety, Designing for Reliability, Other “Ilities” in Design.
3

UNIT 6
6 Hours
Planning Production Activity: Preview, Introduction, Planning Manufacturing Facilities, Quantitative
Tools in Production Planning, Production Planning and Control, Flexible Manufacturing Systems. Managing
Production Operations Preview, Assuring Product Quality, Productivity, Work Measurement, Maintenance
and Facilities (Plant) engineering, Other manufacturing Functions.
UNIT 7
5 Hours
Engineers in Marketing and Service Activities: Preview, Marketing and the Engineer, Engineers in
Service Organizations.
Project Planning and Acquisition: Preview, Characteristics of a Project, The Project Proposal Process,
Project Performance Tools, Types of Contracts.
UNIT 8
4 Hours
Project Organization, Leadership, and Control: Preview, Project Organization, The Project Manager,
Motivating Project Performance, Controlling Cost and Schedule.
TEXT BOOKS
1. Lucy C. Morse, “Managing Engineering and Technology”, 6/E, Dan L. Babcock, Prentice-Hall,
2014.
REFERENCES
1. James A O’ Brien, “Management Information Systems”, 4th edition, Tata McGraw Hill 1999
2. Laudon and Laudon,” Management Information System”, Organization and Technology, 4th
edition Pearson Education/Prentice hall India 1999
Course Learning Outcome
• After successful completion of the course the students will acquire the following
competencies:
• Ability to plan, select, recruit, motivate, lead and retain technical professionals
• Ability to plan technical projects and forecast outputs or future situations and devise strategies for
effective management of projects
• Ability to design organization structure, communication and control mechanisms.
• Organizational Management; Project Management; Project/Organizational Management; Quality
Management; Technical Innovation Management, management of new-product development and
entrepreneurship
• Integration of engineering, computer science, information technology, and business management
• Become proficient in the following areas: strategy, planning, innovation, entrepreneurship,
information technology, software design, product development, and supply-chain management.
• Ability to solve business problems, and the management of technology.
Scheme of Continuous Internal Evaluation (CIE):CIE consists of three tests each for a maximum of 50 marks. The performance of two best out of three
tests is considered and is scaled for a maximum of 30 marks.
Scheme of Semester End Examination (SEE):The question paper consists of 8 questions each for a maximum of 14 marks with two to three
subdivisions under each question.
The students are required to answer any five questions for a total maximum of 70 marks.
Note:

1. Question Paper consist of Part - A and Part – B.
2. Any 5 questions to be answered of which 2 questions should be chosen compulsorily from
each part.
_________________________________________________________________________

4

WEB TECHNOLOGIES
Course Code: 14CS/IS72
Credits: 4
L-T-P : 4-0-0

Total No of Hrs: 60
Hours per week: 04
Maximum Marks: 70

PREREQUISITES
• Basics of Web, Internet, Markup Languages.
COURSE OBJECTIVES
• To implement different navigation strategies for Websites.
• To Learn and implement the use of client-side technologies (XHTML, CSS, forms, JavaScript, and
HTML5), and server-side technologies (PHP, Servlets, JSP, Python, AJAX) for Websites.
________________________________________________________________________
COURSE CONTENT
PART-A
UNIT 1
8 Hours
FUNDAMENTALS of Web –I: Differentiation between HTML and HTML5; Additional Tags in HTML5 like
<!DOCTYPE>, <article>, <aside>, <audio>, <source>, <datalist>, <figcaption>, <header>, <footer>,
<video>, <wbr>; XHTML; CSS.
UNIT 2
7 Hours
Basics of JavaScript: Why do we need JavaScript. Overview of JavaScript; Object Orientation and
JavaScript; General Syntactic Characteristics; Primitives, Operations, and Expressions; Screen Output and
Keyboard Input, Control Statements, Object Creation and Modification, Arrays, Functions, Constructors,
Pattern Matching using Regular Expressions; Overview of Ajax, The Basics of Ajax.
UNIT 3
7 Hours
Programming in Python-1: Beginning Python, Interactive Python, Lexical Matters, Builtin Data types.
UNIT 4
7 Hours
Programming in Python-2: Classes and instances, modules, packages, Regular Expressions, Parsing
PART-B
UNIT 5
Programming in Python-3: GUI Applications, Guidance on Package and Modules.

8 Hours

UNIT 6
8 Hours
Programming in Python-4: Python workbook: Introduction, Lexical Structures, Execution model,
Statements, functions, Applications and Recipes.
UNIT 7
7 Hours
Introduction to PHP: Origins and Uses of PHP, Overview of PHP, General Syntactic Characteristics,
Primitives, Operations, and Expressions, Output, Control Statements, Arrays, Functions, Pattern Matching,
Form Handling, Files, Cookies, Session Tracking.
UNIT 8
8 Hours
Servlets, Java Server Pages: Overview of Servlets, Servlet details, a survey example, storing
information on clients, Java Server Pages, Examples to illustrate the applications of Servlets and JSP

5

TEXT BOOKS
1. Robert. W. Sebesta, "Programming the World Wide Web", Fourth Edition, Pearson
Education,2007.
2. Dave Kuhlman , “A Python Book: Beginning Python, Advanced Python, and Python
Exercises”, Revision 1.1a, dkuhlman@rexx.com http://www.rexx.com/~dkuhlman, April 22,
2012.
REFERENCES
1. Allen Downey, “Think Python: How to think like a Computer Scientist”, Version 2.0.13,
http://www.greenteapress.com/thinkpython/thinkpython.pdf, Green Tea Press, June 2014.
COURSE LEARNING OUTCOME
• Students will be able to design and implement basic websites.
Scheme of Continuous Internal Evaluation (CIE):CIE consists of three tests each for a maximum of 50 marks. The performance of two best out of three
tests is considered and is scaled for a maximum of 30 marks.
Scheme of Semester End Examination (SEE):The question paper consists of 8 questions each for a maximum of 14 marks with two to three
subdivisions under each question.
The students are required to answer any five questions for a total maximum of 70 marks.
Note:

1. Question Paper consist of Part - A and Part – B.
2. Any 5 questions to be answered of which 2 questions should be chosen compulsorily from
each part.

6

DATA MINING
Course Code: 14IS73
Credits: 4
L-T-P : 4-0-0

Total No of Hrs: 60
Hours per week: 04
Maximum Marks: 70

PREREQUISITES
• Data Base Management System
COURSE OBJECTIVES
• This course introduces the fundamental principles, algorithms and applications of intelligent data
processing and analysis. It will provide an in depth understanding of various concepts and popular
techniques used in the field of data mining.
________________________________________________________________________
COURSE CONTENT
PART-A
UNIT 1
7 Hours
Introduction: Introduction to Data Mining: what is data mining, Motivation challenges. Origins and data
mining tasks. Types of data, data quality, Data preprocessing
UNIT 2
Data Visualization: Motivations for visualization, general concept, techniques,
dimensional data, OLAP and Multi dimensional data analysis

7 Hours
visualization of higher

UNIT 3
7 Hours
Classification-I: Classification - Basic Methods, general approach to solving a classification problem,
Decision Trees induction, rule based classifiers, nearest neighbor classifiers.
UNIT 4
8 Hours
Classification-II: Bayesian classifiers, artificial neural network, ensemble methods: rationale for
Ensemble method, methods for constructing an Ensemble Classifier- Bagging and Boosting.
PART-B
UNIT 5
8 Hours
Association Analysis: Basic Concepts and Algorithms: Problem Definition, Frequent Itemset
Generation, Rule Generation, Compact Representation of Frequent Itemsets, Alternative Methods
for Generating Frequent Itemsets.
UNIT 6
8 Hours
Cluster Analysis: Basic Concepts and Algorithms-I: Overview, k-mean, agglomerative Hierarchical
clustering.
UNIT 7
8 Hours
Cluster Analysis: Basic Concepts and Algorithms-II: DBSCAN: traditional density-center based
approach, the DBSCAN algorithm, strengths and weakness, cluster evaluation.
UNIT 8
7 Hours
Anomaly Detection: Preliminaries, statically approaches, proximity based outlier detection, density
based detection, clustering based techniques, PCA, Linear Regression.

7

TEXT BOOKS
1. Tan, Steinbach, Kumar, “Introduction to Data Mining”, Addison Wesley, 2006.
REFERENCES
1. D.J. Hand, H. Mannila, and P. Smyth,” Principle of Data Mining”, MIT Press, 2001.
2. M. J. A. Berry, and G. Linoff, “Data Mining Techniques: For Marketing, Sales, and Customer
Relationship Management”, 2nd. ed., Wiley Computer Publishing, 2004.
3. Jiawei Han , Micheline Kamber , Jian Pei , “Data Mining: Concepts and Techniques” , The
Morgan Kaufmann Series in Data Management Systems, 2011.
COURSE LEARNING OUTCOME
Students participating this course will learn about:
• The principle algorithms and techniques used in data mining, such as clustering, association
mining, classification and prediction;
• The various application and current research areas in data mining, such as Web and text mining,
stream data mining;
• Ethical and social impacts of data mining.
• Practical lab sessions using a state-of-the-art open source data mining tool will allow students to
gain expertise in 'hands on data' mining, while tutorial sessions covering overview research
papers will highlight important data mining issues in more depth.
Scheme of Continuous Internal Evaluation (CIE):CIE consists of three tests each for a maximum of 50 marks. The performance of two best out of three
tests is considered and is scaled for a maximum of 30 marks.
Scheme of Semester End Examination (SEE):The question paper consists of 8 questions each for a maximum of 14 marks with two to three
subdivisions under each question.
The students are required to answer any five questions for a total maximum of 70 marks.
Note:

1. Question Paper consist of Part - A and Part – B.
2. Any 5 questions to be answered of which 2 questions should be chosen compulsorily from
each part.

8

CLOUD COMPUTING
Course Code: 14CS/IS74
Credits: 4
L-T-P : 4-0-0

Total No of Hrs: 60
Hours per week: 04
Maximum Marks: 70

PREREQUISITES: Computer networks.

COURSE OBJECTIVES
• To articulate the main concepts, key technologies, strengths, and limitations of cloud computing
and the possible applications for state-of-the-art cloud computing.
• To identify the architecture and infrastructure of cloud computing, including SaaS, PaaS, IaaS,
public cloud, private cloud and hybrid cloud.
• To explain the core issues of cloud computing such as security, privacy, and interoperability.
_______________________________________________________________________
COURSE CONTENT
PART-A
UNIT 1
7 Hours
Introduction: Overview of Cloud Computing, Applications, Intranets and the Cloud, When can cloud
computing be used? Benefits and limitations, Security concerns, Regulatory issues
UNIT 2
8 Hours
Business Case for Cloud and Cloud Computing Technology: Cloud computing services, Cloud
Deployment Models, Help to the business, Deleting the data center, Hardware & Infrastructure: Clients,
Security, Network, Services
UNIT 3
7 Hours
Cloud Computing Technology: Accessing the Cloud: Platforms, Web applications, Web APIs, Standards:
Application, Infrastructure, Service
UNIT 4
8 Hours
Cloud Computing at Work: Software as a Service: Overview, Driving Forces; Software plus Services:
Overview, Mobile Device Integration; Migrating to the Cloud: Migration; Best Practices.
PART-B
UNIT 5
8 Hours
Using Cloud Patforms: Understanding Abstraction & Virtualization: Using Virtualization Technologies,
Load Balancing and Virtualization, Understanding Hypervisors, Understanding Machine Imaging, Capacity
Planning: Capacity Planning, Defining Baseline and Metrics, Network Capacity, Scaling
UNIT 6
7 Hours
Exploring Cloud Infrastructures: Managing the Cloud: Administrating the Clouds, Emerging Cloud
Management Standards, Understanding Cloud Security: Securing the Cloud, Securing Data, Establishing
Identity and Presence.
UNIT 7
7 Hours
Working with Cloud-Based Storage: Measuring the Digital Universe, Cloud storage in the Digital
Universe, Cloud storage definition, Provisioning Cloud Storage, Unmanaged cloud storage, Managed cloud
storage, Creating cloud storage systems, Virtual storage containers, Exploring Cloud Backup Solutions,
Backup types, Cloud backup features, Cloud attached backup, Cloud Storage Interoperability

9






Download VII Semester Syllabus



VII_Semester_Syllabus.pdf (PDF, 718.95 KB)


Download PDF







Share this file on social networks



     





Link to this page



Permanent link

Use the permanent link to the download page to share your document on Facebook, Twitter, LinkedIn, or directly with a contact by e-Mail, Messenger, Whatsapp, Line..




Short link

Use the short link to share your document on Twitter or by text message (SMS)




HTML Code

Copy the following HTML code to share your document on a Website or Blog




QR Code to this page


QR Code link to PDF file VII_Semester_Syllabus.pdf






This file has been shared publicly by a user of PDF Archive.
Document ID: 0000713777.
Report illicit content