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119
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATION TEACHING AND EXAMINATION SCHEME
Programme Master of Computer Application
Branch/Spec. Computer Applications
Semester V
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject Code
Subject Name
Teaching scheme Examination scheme (Marks)
Credit Hours (per week) Theory Practical
Lecture(DT) Practical(Lab.) Lecture(DT) Practical(Lab.) CE SEE Total CE SEE Total
L TU Total P TW Total L TU Total P TW Total
P15A1SE SOFTWARE ENGINEERING
2 1 3 - - - 2 1 3 - - - 40 60 100 - - -
ELECTIVE-VIII 2 1 3 2 - 2 2 1 3 4 - 4 40 60 100 20 30 50
P15A3SEO SEO & DIGITAL MARKETING
3 0 3 2 - 2 3 0 3 4 - 4 40 60 100 20 30 50
ELECTIVE-IX 2 1 3 2 - 2 2 1 3 4 - 4 40 60 100 20 30 50 ELECTIVE-X 2 1 3 2 - 2 2 1 3 4 - 4 40 60 100 20 30 50 P15A6SDP1 SYSTEM
DEVELOPMENT PROJECT-I
0 0 0 5 - 5 0 0 0 10 - 10 - - - 60 40 100
Total 11 4 15 13 - 13 11 4 15 26 - 26 200 300 500 140 160 300
ELECTIVE – VIII
1. P15A2DBA DATABASE ADMINISTRATION 2. P15A2ADM ADVANCE DATABASE MANAGEMENT
SYSTEM
ELECTIVE – IX
1. P15A4AAD ANDROID APPLICATION DEVELOPMENT
2. P15A4IAD I-PHONE APPLICATION DEVELOPMENT
120
ELECTIVE – X
1. P15A5ML4 MACHINE LEARNING-II 2. P15A5BDA4 BIG DATA ANALYTICS-IV 3. P15A5CSF4 CYBER SECURITY AND
FORENSIC-III
4. P15A5CC4 MICROSOFT AZURE
121
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATON Programme MASTER OF COMPUTER
APPLICATION Branch/Spec.
Computer Application
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject code P15A1SE Subject Name SOFTWARE ENGINEERING
Teaching scheme Examination scheme (Marks)
(Per week) Lecture(DT) Practical(Lab.) Total CE SEE Total
L TU P TW
Credit 02 01 - - 03 Theory 40 60 100
Hours 02 01 - - 03 Practical - - -
Objective:
To teach the students the software engineering concepts.
Pre-requisites:
Student must have knowledge of Software Development Process and Object Oriented Concepts.
Learning Outcome:
Students will gain knowledge and Understanding of System Development Life cycle using software
engineering concepts and also they will come to know how to model the system by drawing various structural
and behavioural diagrams using UML.
Unit Content Hrs
SECTION-I
1 Introduction to Software Engineering: What is Software, Characteristics of Software, Applications of Software, Software Myths A Generic View of Software: Software Engineering : A layered Technology, A Process framework, The Capability Maturity Model Integration (CMMI), Process Patterns
06
2 Process Models: The Waterfall Model, Incremental Process Models: The Incremental Model, The RAD Model, Evolutionary Software Process Models: Prototyping, The Spiral Model, Concurrent Development Model, Specialized Process Models: Component-Based Development, Aspect oriented Software Development
06
3 Metrics for Process and Projects: Software process and project metrics, Software measurement: Size Oriented Metrics, Function Oriented Metrics
05
4 Risk analysis and Management: Reactive versus proactive risk strategies, Software risks, Risk identification, Risk projection, Risk refinement, Risk mitigation, monitoring, and management, The RMMM Plan.
05
SECTION-II
122
5 Introduction to UML Overview of UML, Conceptual Model of UML, Common Mechanisms in the UML, Architecture, Software Development Life Cycle, UML modelling with example
05
6 Basic Structural modeming Classes: Names, Attributes, Operations, Organizing Attributes and Operations, Responsibilities Advanced Classes: Classifiers, Visibility, Scope, Abstract Root Leaf and Polymorphic Elements, Multiplicity, Attributes, Operations, Relationships: Dependency, Generalization, Association Advanced Relationships: Dependency, Generalization, Association, Realizations.
06
7 Advanced Structural modeming Class Diagrams: Common Uses, Common modelling Techniques, Interface Types and Roles: Operations, Relationships, Understanding an Interface, Types and Roles, Packages: Names, Owned Elements, Visibility, Importing and Exporting, Generalization, and Standard Elements
06
8 Behavioural modelling Interactions: Object and Roles, Links and connectors, Messages, Sequencing, Use Cases: Names, Use Cases and Actors, Organizing Use Cases, Use Case Diagrams: Common Uses, Common modelling Techniques, Interaction Diagram: Sequence Diagram, Collaboration Diagram. Activity Diagram: Action and Activity States, Transactions, Branching, Forking and Joining, Swim lanes, Object Flow
06
Practical content N.A.
Text Books
1 The Unified Modeling Language User Guide by Grady Booch, James Rumbaugh, Ivar Jacobson, Pearson.
2 Software Engineering by Roger S. Pressman, Mc Graw Hill
Reference Books
MOOC/ Certification Courses 1 https://www.academiccourses.com/Certificate/Software-Engineering/ Question Paper Scheme: University Examination Duration: 3 Hours
Note for Examiner: - (I) Questions 1 and 4 are compulsory with no options. (II) Internal options should be given in questions 2, 3, 5 and 6. SECTION - I Q.1 –8 Marks Q.2 –11 Marks Q.3 – 11 Marks
SECTION - II Q.4 –8 Marks Q.5 –11 Marks Q.6 – 11 Marks
123
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATION Programme Master of Computer
Application
Branch/Spec. Master of Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject code P15A2DBA Subject Name ELECTIVE VIII DATABASE ADMINISTRATION
Teaching scheme Examination scheme (Marks)
(Per week) Lecture(DT) Practical(Lab.) Total CE SEE Total
L TU P TW
Credit 2 1 2 - 5 Theory 40 60 100
Hours 2 1 4 - 7 Practical 20 30 50
Objective:
To teach the database administration tasks.
Pre-requisites:
Require the basic knowledge of DBMS and basic operational systems. Learning Outcome:
Students can apply this knowledge for Data Management and Data Administration and can performed
role as a DBA Theory syllabus
Unit Content Hrs
Section-I
1 Introduction of Oracle Database 10g and Database Configuration Assistant
Introduction (4): Oracle Database 10g: Overview of Grid Computing, Oracle
Database Architecture (1), Database Structures, Oracle Memory Structures, Process
Structures, Oracle Instance Management (1), Server Process and Database Buffer
Cache, Physical Database Structure, Tablespaces and Data Files (1), SYSTEM and
SYSAUX tablespaces, Segments, Extents and Blocks (1), Logical and Physical Database
Structures(1)
Creating an Oracle Database(3): Objectives, Planning the Database, Database
Configuration Assistant (DBCA)(1), Using DBCA to create a database, Password
Management(1), Creating a Database Design Template, Using the DBCA to Delete a
Database(1)
07
2 Managing Oracle Instance & Database Storage Structures
Managing the Oracle Instance(4) : Objectives, Management Framework, Starting and
Stopping Database Control, Oracle Enterprise Manager (1),Accessing Oracle Enterprise
Manager, Using SQL*Plus and iSQL*Plus to Access Your Database ,Setting Up
9
124
iSQL*Plus for SYSDBA and SYSOPER Access, Calling SQL*Plus from a Shell
Script(1), Calling a SQL Script from SQL*Plus, Initialization Parameter Files,
Simplified Initialization Parameters(1), Viewing and Modifying Initialization
Parameters , Database Startup and Shutdown, Viewing the Alert Log, Viewing the Alert
History, Dynamic Performance Views(1)
Managing Database Storage Structures (5) :Objectives, Storage Structures, How Table
Data Is Stored, Anatomy of a Database Block ,Tablespaces and Data Files(1),Oracle
Managed Files (OMF), Space Management in Tablespaces, Exploring the Storage
Structure, Creating a New Tablespace, Storage for Locally Managed Tablespaces(1) ,
Tablespaces in the Preconfigured Database, Altering a Tablespace , Actions with
Tablespaces, Dropping Tablespaces(1), Viewing Tablespace Information, Gathering
Storage Information, Viewing Tablespace Contents(1), Enlarging the Database, What
Is Automatic Storage Management? , ASM: Key Features and Benefits, ASM: Concepts
(1) 3 Managing Undo Data, Security in Database
Managing Undo Data (3) : Objectives, Data Manipulation, Undo Data , Transactions
and Undo Data, Storing Undo Information1(1), Undo Data Versus Redo Data,
Monitoring Undo, Administering Undo, Configuring Undo Retention(1), Guaranteeing
Undo Retention, Sizing the Undo Tablespace, Using the Undo Advisor(1)
Implementing Oracle Database Security (4) :Objectives, Industry Security
Requirements, Separation of Responsibilities, Database Security, Principle of Least
Privilege(1), Applying the Principle of Least Privilege, Monitoring for Suspicious
Activity, Standard Database Auditing, Enabling Auditing(1), Uniform Audit Trails,
Enterprise Manager Audit Page(1), Using and Maintaining Audit Information, Value-
Based Auditing, Fine-Grained Auditing, FGA Policy, Audited DML Statement:
Considerations, FGA Guidelines, DBA Auditing(1), Maintaining the Audit Trail,
Security Updates, Applying Security Patches(1)
7
Section-II
4 Performance Management (5)
Objectives, Performance Monitoring , Performance Monitoring: Top Sessions,
Performance Monitoring: Top Services(1) , SQL Tuning Advisor: Overview ,SQL
Tuning Advisor : Options and Recommendations(1), SQL Statistics, Identifying
05
125
Duplicate SQL, Using the SQL Access Advisor, Managing Memory Components,
Enabling Automatic Shared Memory Management (ASMM)(1),Manually Setting
Shared Memory Management, Using the Memory Advisor, Dynamic Performance
Statistics(1) , Troubleshooting and Tuning Views, Invalid and Unusable Objects(1)
5 Backup and Recovery in Database
Performing Database Backups (3) : Objectives, Backup Solutions: Overview, Oracle
Secure Backup, User- Managed Backup(1),Terminology, Recovery Manager (RMAN),
Configuring Backup Settings, Scheduling Backups: Strategy(1), Options, Settings,
Schedule, Review Backing Up the Control File to a Trace File, Managing Backups,
Flash Recovery Area (1)
Performing Database Recovery (4)
Objectives, opening a Database, Changing Instance Status, Keeping a
Database Open, Loss of a Control File, Loss of a Redo Log File(2), Loss of a Data File
in NOARCHIVELOG Mode, Loss of a Noncritical Data File in ARCHIVELOG Mode,
Loss of a System-Critical Data File in ARCHIVELOG Mode (2)
07
6 Performing Flashback & Moving Data
Performing Flashback (3) : Objectives, Flashback Technology: Benefits, When to Use
the Flashback Technology, Flashing Back Any Error(1),Flashback Database: Overview,
Reducing Restore Time, Considerations, Enabling Flashback
Database (1), Flashback Table, Flashback Drop: Overview, Flashback Time Navigation,
Flashback Query, Flashback Versions Query, Flashback Transaction Query (1)
Moving Data (7) :Objectives, Moving Data: General Architecture, Directory Object:
Overview, Creating Directory Objects(1),SQL*Loader: Overview, Loading Data with
SQL*Loader, SQL*Loader Control File, Loading Methods(1), Data Pump: Overview,
Data Pump: Benefits, Data Pump Export and Import: Overview, Data Pump Utility:
Interfaces and Modes(3), Fine-Grained Object Selection, Advanced Feature: Sampling,
Export Options: Files, Data Pump File Locations, Scheduling and Running a Job, Data
Pump File Naming and Size(2)
10
Practical content
List of programs specified by the subject teacher based on above mentioned topics
Text Books
1 Oracle Database 10G, The Complete reference by kevinloney- Tata Mcgraw Hill Education Pvt.
Ltd Publication
Reference Books
1 Oracle DBA Bible, by Janathan Gennick, Carol McCullough-Dieter and Gerrit- Jan Linker,
WILEY-Dreamtech Publication.
2 Using Oracle, by William G. Page - PHI Publication
MOOC/ Certification Courses
126
1 https://education.oracle.com/oracle-certification-path/pFamily_32 Question Paper Scheme:
University Examination Duration: 3 Hours Note for Examiner: - (I) Questions 1 and 4 are compulsory with no options. (II) Internal options should be given in questions 2, 3, 5 and 6. SECTION - I Q.1 –8 Marks Q.2 –11 Marks Q.3 –11 Marks SECTION - II
Q.4 –8 Marks Q.5 –11 Marks
Q.6 –11 Marks
127
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer
Applications
Branch/Spec. Master of Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject code P15A2ADM Subject Name ADVANCE DATABASE MANAGEMENT SYSTEM
Teaching scheme Examination scheme (Marks)
(Per week) Lecture(DT)
Practical(Lab.) Total CE SEE Total
L TU P TW
Credit 2 1 2 - 5 Theory 40 60 100
Hours 2 1 4 - 7 Practical 20 30 50
Objective:
To make students aware about the normal form, database design, parallel and distributed database and sql.
Pre-requisites:
Students must have knowledge of Database concepts, Transaction Management, Concurrency,
Recovery and Security. They also have PL\SQL blocks, SQL Statements, Subqueries, Joins, Locks,
Indexing, Sequencing and various inbuilt SQL functions. Learning Outcome:
After completing this course, students should be able to:
Understand Concepts of Normalization, Database design and Performance Tuning
Parallel and Distributed Database systems
Student will able to develop business application with the help of advanced objects like Stored
Procedure, Function, Trigger and Package.
Theory syllabus
Unit Content Hrs
SECTION - I
1 Schema Refinement and Normal Forms
Introduction to Schema Refinement, Examples
Functional Dependencies
Examples Motivating Schema Refinement
Reasoning about Functional Dependencies
Normal Forms
Decompositions
Normalization
Other kinds of Dependencies
6
2 Physical Database Design and Tuning
Introduction to Physical Database Design
Guidelines for Index Selection
Basic Examples of Index Selection
5
128
Clustering and Indexing
Indexes on Multiple-Attribute Search keys
Indexes that Enable Index-Only Plans
Overview of Database Tuning
Choices in Tuning the Conceptual Schema
Choices in Tuning Queries and Views
Impact of Concurrency
DBMS Benchmarking
3 Parallel and Distributed Databases:
Architectures for Parallel Databases
Parallel Query Evaluation
Parallelizing Individual Operations
Parallel Query Optimization
Introduction to Distributed Databases
Distributed DBMS Architectures
Storing Data in a Distributed DBMS
Distributed Catalog Management
Distributed Query Processing
Updating Distributed Data
Introduction to Distributed Transactions
Distributed Concurrency control
Distributed Recovery
12
SECTION - II
4 Working with PL/SQL
Generic PL/SQL Block,
SQL Transactions
Error Handling in PL/SQL (System and User Define)
Cursors: Types of Cursor, Cursor with Loops, Parameterized Cursor, Nested
Cursor
11
5 PL/SQL Database Objects
Stored Procedures and Functions: IN, OUT and INOUT parameters
Triggers: Types of Triggers (Raw Trigger, Statement Trigger, Before and After
Trigger, Combination trigger),Create and Delete Trigger
Package: Introduction, Create, Invoke, Alter, overloading Procedure and
Functions
11
Practical content List of programs specified by the subject teacher based on above mentioned topics
MOOC/ Certification Courses
1 https://www.w3schools.com/sql/
2 https://nptel.ac.in/courses/106/106/106106220/
3 https://www.tutorialspoint.com/plsql/index.htm
129
Text Books
1 Database Management System by Raghu Ramakrishnan/Johannes Gehrke – 2nd Edition,MC
Graw Hill
2 SQL,PL/SQL The Programming language of Oracle by Ivan Bayross – 4th Revised Edition ,
BPB Publication
Reference Books
1 Fundamentals of Database Systems by Ramez Elmasri and Shamkant B. Navathe
-4th Edition Pearson Education.
2 Database Systems:Concepts, Design and Applications by S. K. Singh., Pearson
Education
3 Database System Concepts by Abraham Silberschatz,Henry F. Lorth,S.Sudarshan – 5th Edition
,MC Graw Hill
4 Oracle Database 11g PL/SQL Programming by Michael Mclaughlin (Oracle Press)
Question Paper Scheme: University Examination Duration: 3 Hours Note for Examiner: - (I) Questions 1 and 4 are compulsory with no options. (II) Internal options should be given in questions 2, 3, 5 and 6. SECTION - I Q.1 –8 Marks Q.2 –11 Marks Q.3 –11 Marks SECTION - II
Q.4 –8 Marks Q.5 –11 Marks
Q.6 –11 Marks
130
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer Applications Branch/Spec. Master of Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject Code P15A3SEO Subject Name SEO & DIGITAL MARKETING
Teaching scheme Examination scheme (Marks)
(Per week) Lecture (DT) Practical (Lab.) Total CE SEE Total
L TU P TW
Credit 03 00 02 00 05 Theory 40 60 100
Hours 03 00 04 00 07 Practical 20 30 50
Objective:
To provide wide opportunities of Digital media marketing and SEO field in cutting edge technologies.
Pre-requisites:
Basic knowledge to access internet and social media.
Learning Outcome:
After completing this course, students should be able to:
Students gain an overall understanding of Digital Marketing.
Develop insight on Current Trends – Digital and Social Statistics.
Introduction to Social Marketing Platforms like Facebook, YouTube, etc.
To gain and implement of Search Engine Optimization (SEO) in Digital Media.
To acquire web analytics skills for business analysis, tracking, monitoring and controlling.
Content:
Unit Hrs
SECTION – I
1 Introduction to Digital Media Marketing:
Overview of Digital Marketing, Types of Digital Marketing, Need of Digital Marketing,
How to Create a Digital Marketing Strategy, Future digital marketing, Digital Marketing
models
Email, Video and Mobile Marketing
Overview of Email & Mobile Marketing, Email & Mobile marketing strategy, Mail
Chimp, Email scheduling & automation, Mobile Commerce, Mobile Integration and
Mobile Analytics, Video Marketing, Virtual Reality marketing
14
131
2 Social media Marketing Media Marketing
Social Media advertising (PPC), Blog Optimization, Business Listing, Facebook paid
marketing Strategy, Multi-Channel Social Media Strategy, LinkedIn Lead generation &
Personal Branding, ROI of Social Media marketing, SMS marketing
8
SECTION – II
3 Introduction to Search Engine Optimization:
Definition, SEO Vs SEM, Components of Search Engine, Phases of SEO, SEO Tactics
Methods – White Hat Vs. Black Hat, Types of SEO methods - On Page, Off Page and
Local SEO, SEO audit, Link building
SEO Tools & Techniques
Webmaster Tools, Trend Analysis Tools, Keyword Planner Tool, Competitor Analysis,
Google Ads (adword), ahrefs, longtailpro, Woorank, CanlRank, SEMrush, SEObility,
DareBoost, LSIGraph, Moz, LinkMiner, pitchbox, seedkeywords, seoptimer, backlinko,
authoritylabs, Small SEO tool.
16
4 Web Analytics:
Introduction of Web Analytics, Importance of Google Analytics, When Analytics
actually need, on Site vs. Off-Site Web analytics, Major Web Analytics Tools, Google
Analytics - Setting up website with web analytics, Set Goals, Funnels, Filters,
Segmentation, Monitor Website Traffic, Traffic Source, Visitors, Event Tracking,
Tracking Conversions, Analytics Monitoring.
07
Practical Content:
List of programs specified by the subject teacher based on above mentioned topics
Text Book:
1 The art of Digital Marketing by Ian Dodson, John Wiley & sons publication.
Reference Books:
1 Digital Marketing using Google Services by Balu and Latha, LocSea Software Development
Private Limited.
2 eMarketing - the essential guide to marketing in a Digital World by Rob Stokes and the Minds of
Quirk, 5th Edition, Quirk eMarketing (Pty) Ltd.
3 Digital Marketing Analytics by Chuck Hemann & Ken Burbary, Que publishing.
4 Mastering Search Analytics by Brent Chaters, O'reilly publication.
5 Marketing 4.0 Moving from Traditional to Digital by Philip Kotler, Hermawan Kartajaya, Iwan
Setiawan, Wiley publication, 2017
6 Search Engine Optimization With Wordpress Website and SEO Free tools Knowledge.
7 Social Media Marketing by Dave Evants with Jake McKee, Wiley Publishing.
8 Fundamentals of Digital Marketing by Puneet Singh Bhatia, Person, 1st Edition, 2017.
9 Digital Marketing by Seema Gupta, Mc-Graw Hill, 1st Edition, 2017.
MOOC/Certification Courses:
1 https://moz.com/
132
2 https://seositecheckup.com/
3 https://www.semrush.com/
4 https://yoast.com/what-is-local-seo/
5 https://www.seoptimer.com/
6 https://ahrefs.com/blog/seo-audit/
7 https://www.yourprimer.com/in
Question Paper Scheme:
University Examination Duration: 3 Hours
Note for Examiner: -
(I) Questions 1 and 4 are compulsory with no options.
(II) Internal options should be given in questions 2, 3, 5 and 6.
SECTION - I
Q.1 –8 Marks
Q.2 –11 Marks
Q.3 –11 Marks
SECTION - II
Q.4 –8 Marks
Q.5 –11 Marks
Q.6 –11 Marks
133
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer Applications Branch/Spec. Master of Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject Code P15A4AAD Subject Name ANDROID APPLICATION DEVELOPMENT
Teaching scheme Examination scheme (Marks)
(Per week) Lecture (DT) Practical (Lab.) Total CE SEE Total
L TU P TW
Credit 02 01 02 00 05 Theory 40 60 100
Hours 02 01 04 00 07 Practical 20 30 50
Objective:
To explore and quickly to learn the skeleton of Mobile platform using Android Programming.
Pre-requisites:
Java programming and Object-oriented programming, Knowledge of RDBMS
Learning Outcome:
After completing this course, students should be able to:
To understand and develop Android application using Java.
To be capable to learn the process of developing software for the mobile.
To be able to implement mobile applications on the Android Platform.
To be able to create mobile applications involving data storage in SQLite database.
Content:
Unit Hrs
SECTION – I
1 Introducing Android:
The Android Platform, Exploring Android SDK, Testing Your Development
Environment, Important Android Terminology, Application Context, Application Tasks
with Activities
Android Manifest File and Application Resources:
Configuring Android Manifest File, Managing Application’s Identity, Enforcing
Application System Requirements, Registering Activities and other Application
Components, Working with Permissions, Working with Resources
09
2 Exploring User Interface Screen Elements:
Introducing Android Views and Layouts, Displaying Text with Text View, Retrieving
Data From Users, Using Buttons, Check Boxes and Radio Groups, Getting Dates and
14
134
Times From Users, Using Indicators to Display Data to Users, Adjusting Progress with
Seek Bar, Providing Users with Options and Context Menus, Handling User Events,
Working with Dialogs, Working with Styles, Working with Themes
Layouts and Animation:
Creating User Interfaces in Android, Organizing User Interface, Using Built-in Layout
Classes, Using Built-in View Container Classes, Drawing on the Screen, Working with
Text, Working with Bitmaps, Working with Shapes, Working with Animations
SECTION – II
3 Using Android Data and Storage APIs:
Working with Application Preferences, Working with Files and Directories, Storing
Structured Data using SQLite Databases
Sharing Data Between Applications with Content Providers:
Exploring Android’s Content Providers, Modifying Content Providers Data, Acting as a
Content Provider, Working with Live Folders
11
4 Advance Layout:
Recycler View, Card Layout, Drawer Layout, Floating Button, Custom Adapters, Custom
List View
Using Android Networking, Web and Telephony APIs:
Understanding Mobile Networking Fundamentals, Accessing the Internet (HTTP),
Browsing the Web with Web View, Building Web Extensions using Web Kit, Working
with Flash, Working with Telephony Utilities, Using SMS, Making and Receiving Phone
Calls
11
Practical Content:
List of programs specified by the subject teacher based on above mentioned topics
Text Book:
1 Android Wireless Application Development By Lauren Darcey and Shane Conder,
Pearson Education, 3rd Edition
Reference Books:
1 Beginning Android Application Development By Wei-Meng Lee, Wrox Publication
2 Professional ANDROID 4 Application Development, By Reto Meier, Wrox Publication, Latest Edition
3 Unlocking Android Developer’s Guide By Frank Ableson and Charlie Collins and Robi Sen, Manning Publication Co.
MOOC/ Certification Courses:
1 https://developer.android.com/
2 https://www.udemy.com/learn-android-application-development-y/
Question Paper Scheme:
University Examination Duration: 3 Hours
Note for Examiner: -
(I) Questions 1 and 4 are compulsory with no options.
(II) Internal options should be given in questions 2, 3, 5 and 6.
SECTION - I
135
Q.1 –8 Marks
Q.2 –11 Marks
Q.3 –11 Marks
SECTION - II
Q.4 –8 Marks
Q.5 –11 Marks
Q.6 –11 Marks
136
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATION Programme Master of Computer
Application
Branch/Spec. Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject code P15A2IAD Subject Name ELECTIVE-VIII I-PHONE APPLICATION DEVELOPMENT
Teaching scheme Examination scheme (Marks)
(Per week) Lecture(DT) Practical(Lab.) Total CE SEE Total
L TU P TW
Credit 02 01 02 00 05 Theory 40 60 100
Hours 02 01 04 00 07 Practical 20 30 50
Objective:
To explore and quickly to learn the skeleton of Mobile platform using I-Phone Programming. Pre-requisites:
Student must have knowledge of Programing language like C,VB, C# and concepts of OOPS.
Learning Outcome:
Student can create IPhone based mobile application. Student can also upload their apps on Apple Store. The main objectives to give the subject Mobile Application Development in iOS are:
To introduce basic concepts of IOS Application Programming.
To introduce iOS
To introduce Building Mobile Application with iOS
Theory syllabus
Unit Content Hrs
Section - I
1 Introduction to IOS Application Programing Introduction to Objective C and Swift The Development Tools, the Learning Approach and the App Idea Your First Taste of Swift with Playgrounds Introduction to Auto Layout Designing UI Using Stack Views
04
2 Introduction to Prototyping Creating a Simple Table-based App, Working with Static Table Views, Customize Table Views Using Prototype Cell, Interacting with Table View, edition of row, Table Row Deletion, Swipe for Action, Activity Controller and MVC
06
137
3 Outlets, Action, Segue View Controller to Outlet and Actions, Using alert View, Introduction to Navigation Controller and Segue Object Oriented Programming, Project Organization and Code Documentation Detail View Enhancement
04
4 Navigation, animations and MAP: Navigation on multiple pages, Navigation Bar Customization Extensions and Dynamic Type Working with Maps, Device Rotation Basic Animations
06
SECTION II
1 Camera and Gesture reorganization Camera and Library Access, types of screen rotation, All external libraries and bundle resources. Pinch and drag Gesture.
06
2 Explore Interface with Input and screen Using keyboard, customizing the types of input, set keypad with number pad, Exploring Tab Bars and Storyboard References Exploring CloudKit, Keychain
05
3 Deploying and Testing Localizing Your App to Reach More Users Deploying and Testing Your App on a Real iOS Device
04
4 Working with DATABASE Working with Core Data and SQLite Database, Developing User Notifications in iOS Beta Testing with TestFlight and CloudKit Production Deployment Submitting Your App to App Store
10
Practical content
List of programs specified by the subject teacher based on above mentioned topics
Text Books
1 Beginning IOS Programing with Swift –by AppCoda
Reference Books
1 Beginning Swift Programming (WROX) by Wei-Meng Lee 2 The Swift Developer's Cookbook by Packt Publishing Limited
3 https://www.appcoda.com/learnswift/
MOOC/ Certification Courses
1 https://www.appcoda.com/learnswift/
2 https://www.appcoda.com/category/swift-2/
University Examination Duration: 3 Hours
Note for Examiner: -
(I) Questions 1 and 4 are compulsory with no options.
(II) Internal options should be given in questions 2, 3, 5 and 6.
138
SECTION - I
Q.1 –8 Marks
Q.2 –11 Marks
Q.3 –11 Marks
SECTION - II
Q.4 –8 Marks
Q.5 –11 Marks
Q.6 –11 Marks
139
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer Applications Branch/Spec. Master of Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject Code P15A5ML4 Subject Name MACHINE LEARNING-II
Teaching scheme Examination scheme (Marks)
(Per week) Lecture (DT) Practical (Lab.) Total CE SEE Total
L TU P TW
Credit 2 1 2 - 5 Theory 40 60 100
Hours 2 1 4 - 7 Practical 20 30 50
Objective:
To Understand the students, the role of unsupervised learning in Analytics
To Understand how to apply ensemble techniques in solving problem
To Understand recommender systems and their business applications
To learn various pre-processing steps to prepare text data for modelling
Pre-requisites:
Basic Knowledge of Statistics and Programming Language
Learning Outcome:
After completing this course, students should be able to:
Apply different types of clustering techniques
Build and measure ensemble models by setting different hyper parameters
Build and evaluate recommendation systems
Learn to develop model for sentiment classification
Content:
Unit SECTION – I Hrs
1 Introduction to Unsupervised Learning Algorithms
Introduction to unsupervised learning, Introduction to Clustering, Distance and Dissimilarity
measures used in Clustering, Euclidean distance, Standardized Euclidean distance, Manhattan
distance, Minkowski distance, Jaccard Similarity Coefficient, Cosine similarity, Gower’s Similarity
coefficient, Quality and Optimal number of clusters, clustering algorithms, K-Means clustering
and Hierarchical clustering.
10
140
2 Advanced Machine Learning
How Machines Learn?, Gradient Decent Algorithm, Developing a Gradient Descent algorithm for
Linear Regression Model, Scikit-Learn library for Machine Learning, Steps for building Machine
learning models, Bias-variance Trade-off, K-fold cross validation, advanced Regression Models,
Advanced Machine Learning Algorithms, dealing with Imbalanced datasets, K-Nearest
Neighbours(KNN) algorithm, Introduction to ensemble methods, Introduction to Ensemble
methods, Random Forest algorithm, Building and evaluating Random Forest algorithm, Boosting
algorithm, Model building using Adaboost and Gradient Boosting algorithm.
13
SECTION – II
3 Recommender Systems
Introduction to Recommender system, Application of Recommender system, Basic Models for
Recommender system, Association rule mining, Association rules metrics, support, confidence,
lift, applying association rules, Loading the dataset, Encoding the transactions, generating
association rules, Introduction to collaborative filtering, how to find similarity between users,
User based and item based similarity, Matrix factorization
11
4 Text Analytics
Introduction to text analytics, Sentiment classification, Loading the dataset, Exploring the
dataset, text pre-processing, Bag-of-words model, creating count vectors for sentiment train
dataset, displaying document vectors, removing low frequency words, removing stop words,
creating count vectors, distribution of words across different sentiment, Naïve-Bayes Model for
sentiment classification, using TF-IDF vectorizer, challenges of Text Analytics
11
Practical Content:
List of programs specified by the subject teacher based on above mentioned topics
Reference Books:
1 Kumar, U. D. (2017). Business Analytics: The Science of Data-driven Decision Making. Wiley India.
2 Kumar, U.D et al. machine Learning Using Python. Wiley India.
MOOC/ certification Courses:
1 Machine Learning A To Z || Complete Course by Andrew Ng || Beginner to Advance ML
https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN
2 Machine Learning NPTEL course
https://www.youtube.com/watch?v=BRMS3T11Cdw&list=PLYihddLF-CgYuWNL55Wg8ALkm6u8U7gps
Question Paper Scheme:
University Examination Duration: 3 Hours
Note for Examiner: -
(I) Questions 1 and 4 are compulsory with no options.
(II) Internal options should be given in questions 2, 3, 5 and 6.
SECTION - I
141
Q.1 –8 Marks
Q.2 –11 Marks
Q.3 –11 Marks
SECTION - II
Q.4 –8 Marks
Q.5 –11 Marks
Q.6 –11 Marks
142
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer Applications Branch/Spec. Master of Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject Code P15A5BDA4 Subject Name BIG DATA ANALYTICS-IV
Teaching scheme Examination scheme (Marks)
(Per week) Lecture (DT) Practical (Lab.) Total CE SEE Total
L TU P TW
Credit 2 1 2 - 5 Theory 40 60 100
Hours 2 1 4 - 7 Practical 20 30 50
Objective:
To understand the concepts of Scala and learn their implementation. To understand the Apache Spark. To understand Spark Resilient Distributed Datasets – Transformation, Action.
Pre-requisites:
Basic knowledge of Object Oriented programming concepts, Java, Python concepts and any of the Linux operating system flavors.
Learning Outcome:
After completing this course, students should be able to:
Concepts of Scala and its implementation. Concepts of Spark and how it is used along with Spark.
Content:
Unit Hrs
SECTION – I
1 Scala Programming:
Introduction: Introduction to Scala, History of Scala, Features Basic Syntax, Scala
Comments, Data types, Scala Basic Literals, Variables Concept and Operators.
Conditional Expressions: If-Statement, If-else, While, do-while, for, Pattern matching,
break statement.
Scala Function: Function declaration, function definition, Function calling, Functions-
Call by name, Functions with named arguments, Functions with variable arguments,
Default parameter values, Nested functions, Recursion, Scala Closures.
11
2 Scala Classes and Objects: Object, Class, Extending a Class, Singleton Object, Access
Modifiers: Private Members, Protected Members, Public Member, Scope of Protection ,
Constructors, Method overloading, Inheritance.
Scala String Concept: Introduction, String Length, Concatenating String, Format String,
12
143
String Interpolation: The ‘s’ String Interpolator, The ‘f’ Interpolator, raw’ Interpolator;
type of String Methods.
Scala Arrays: Declaring Array Variables, Processing Arrays, Multi-Dimensional Arrays,
Array Methods.
SECTION – II
3 Advance Scala Programming :
Scala Collections: Scala Lists, Scala Sets, Scala Maps, Scala Tuples, Scala Options,
Scala Iterators.
Scala Expressions: Pattern Matching, Matching using Case Classes, Regular Expressions,
the Forming Regular Expressions, Exception Handling
File Input-Output: Reading and Writing of files
10
4 Apache Spark :
Introduction to Apache Spark: Features of Apache Spark, Apache Spark Architecture,
Apache Spark Ecosystem Components, Spark Applications, Install Spark, Spark Shell
Commands to Interact with Spark-Scala.
Resilient Distributed Dataset (RDD): Introduction of RDD, Spark RDD vs DSM,
Features of RDD in Spark.
Spark RDD operations: Create RDDs in Apache Spark, RDD Transformation Function:
Map, Flat Map, Filter, Map Partitions, Map Partition With Index, Union, Intersection,
Distinct, Group By Key, Reduce By Key, Sort By Key, Join; RDD Action: Count,
Collect, Take ,Top, Reduce, Aggregate;
12
Practical Content:
List of programs specified by the subject teacher based on above mentioned topics
Text Book:
1 Scala Cookbook by Alvin Alexander-Oreilly Publisher
2 Programming in Scala by Martin Odersky, Lex Spoon, Bill Venners, 3rd Edition, ARTIMA PRESS
3 Beginning Apache Spark 2 by Hien Luu, Apress publication
MOOC/ Certification Courses:
1 Programming Scala by Dean Wampler, Alex Payne , O'Reilly Publisher
2 Scala for the Impatient by Cay S. Horstmann , Wesley Professional Publisher
3 Apache Spark Graph Processing by Rindra Ramamonjison, Packt Publishing
Web Reference:
1 https://data-flair.training/blogs/scala-environment-setup/
2 https://www.tutorialspoint.com/scala/index.htm
Question Paper Scheme:
University Examination Duration: 3 Hours
Note for Examiner: -
(I) Questions 1 and 4 are compulsory with no options.
(II) Internal options should be given in questions 2, 3, 5 and 6.
SECTION - I
Q.1 –8 Marks
144
Q.2 –11 Marks
Q.3 –11 Marks
SECTION - II
Q.4 –8 Marks
Q.5 –11 Marks
Q.6 –11 Marks
144
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer Applications Branch/Spec. Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject Code P15A5CSF4 Subject Name CYBER SECURITY AND FORENSIC-III
Teaching scheme Examination scheme (Marks)
(Per week) Lecture (DT) Practical (Lab.) Total CE SEE Total
L TU P TW
Credit 2 1 2 - 5 Theory 40 60 100
Hours 2 1 4 - 7 Practical 20 30 50
Objective:
To emphasize the fundamental and importance of digital forensic and incident response. The students will
learn different techniques and procedure that enable them to conduct a digital investigation systematically.
This course majorly focuses on network and host based digital evidence collection.
Pre-requisites:
Fundamental knowledge of cyber security , cyber-attacks and cyber law
Learning Outcome:
After completing this course, students should be able to:
Describe incident response process
Define digital forensic, the role of digital forensic and its process
Examine and collect several sources of network based and host-based evidence in the event of
incident
Prepare, document and report digital evidence whenever required
Content:
SECTION-I
Unit Hrs
1 Incident Response
Incident response process, the role of digital forensic, incident response process,
incident response framework, incident response plan, incident classification, incident
response playbook, escalation procedure, maintaining the incident response
capability, Cyber Security Vs. Cyber Forensic
07
2 Forensic Fundamentals
Introduction, Laws and regulations, rules of evidence, digital forensic fundamentals,
digital forensic process, Digital forensic lab, Physical security, Tools, Hardware,
08
145
Software, Jump kit,
3 Network Evidence Collection
Classification of Network Forensic Systems, Challenges in Network Forensic
Analysis, Network Forensic Process Models, configuration: Logs and log
management, network device evidence, Security information and event management
system, Security onion, packet Capture, tcpdump, winpcap and rawcap, wireshark,
Evidence collection
08
SECTION-II
4 Acquiring Host-Based Evidence Collection
Preparation, Evidence volatility, Evidence acquisition, Evidence collection
procedures, Memory acquisition, Non-volatile data,
07
5 Understanding Forensic Imaging
Overview of forensic imaging, Preparing a stage drive, Imaging : Dead Imaging, Live
Imaging, Imaging with linux
07
6 Forensic Reporting
Documentation overview, What to document, Types of documentation, Sources,
Audience, Incident tracking, Fast incident response, Written reports, Executive summary,
Forensic report
08
Practical Content:
List of programs specified by the subject teacher based on above mentioned topics
Text Book:
1 Digital Forensics and Incident Response - An intelligent way to respond to attacks 1st edition by
Gerard Johansen Published by Packt Publishing Ltd.
Reference Books:
1 Real Digital Forensics 1st edition by Keith J. Jones, Richard Bejtiich, Curtis W. Rose, Published by
Addison Wesley Pearson Education
2 Computer Evidence Collection & Presentation 1st edition by Christopher L.T. Brown Published by
Firewall Media
3 Digital Forensic with Open Source Tools, 1st Edition by Cory Altheide, Harlan Carvery by syngress
Question Paper Scheme:
University Examination Duration: 3 Hours
Note for Examiner: -
(I) Questions 1 and 4 are compulsory with no options.
(II) Internal options should be given in questions 2, 3, 5 and 6.
SECTION - I
Q.1 –8 Marks
Q.2 –11 Marks
Q.3 –11 Marks
SECTION - II
Q.4 –8 Marks
Q.5 –11 Marks
Q.6 –11 Marks
146
147
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer
Applications
Branch/Spec. Master of Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject code P15A5CC4 Subject Name Microsoft Azure
Teaching scheme Examination scheme (Marks)
(Per week) Lecture(DT) Practical(Lab.) Total CE SEE Total
L TU P TW
Credit 2 1 2 ------ 5 Theory 40 60 100
Hours 2 1 4 ------ 7 Practical 20 30 50
Objective
Students can understand and hands on different types of concepts and services for cloud computing using Microsoft Azure.
Pre-requisites
Operating System Concepts, Computer Network Concepts, Programming concepts, Cloud Computing Concepts
Learning Outcome
Students successfully completing this course will be able to understand terminology, concepts and services of Microsoft Azure platform like Microsoft Azure Management Portal and its services
Theory syllabus
Unit Content Hrs
SECTION – I
1 Introduction to Microsoft Azure, Components, Compute Module, Fabric Controller, Storage, Blobs, Queues, Tables, CDN, Applications, Security, Datacentres
7
2 Azure Management Portal, Azure - Create Virtual Network, Azure - Deploying Virtual Machines, Azure - Endpoint Configuration, Azure - Point-to-Site Connectivity, Azure - Site-to-Site Connectivity
8
3 Microsoft Azure - Traffic Manager, Microsoft Azure - PowerShell, Azure - Monitoring Virtual Machines, Azure - Setting Up Alert Rules, Azure - Application Deployment Microsoft Azure - Backup & Recovery
7
SECTION – II
4 Azure - Self-Service Capabilities, Azure - Multi-Factor Authentication, Azure - Forefront Identity Manager, Azure - Data Import & Export Job, Microsoft Azure - Websites
7
5 Microsoft Azure - Scalability, Microsoft Azure - Disk Configuration, Microsoft Azure - Disk Caching, Microsoft Azure - Personalize Access, Azure - Personalize Company Brand
8
6 Azure - Self-Service Password Reset, Microsoft Azure - Self-Service Group, Microsoft Azure - Create a Group, Azure - Security Reports & Alerts, Azure - Orchestrated Recovery, Microsoft Azure - Health Monitoring, Microsoft Azure - Upgrades the services
8
148
Text Book:
1 Fundamentals of Azure Second Edition Microsoft Azure Essentials, Michael Collier Robin
Shahan, Microsoft Reference Books
1 Learn Azure in a Month of Lunches, Book by Iain Foulds, Manning Publications
2 Building Cloud Apps with Microsoft Azure: Best Practices for DevOps, Data Storage, High
Availability, and More (Developer Reference) Kindle Edition
by Scott Guthrie (Author), Mark Simms (Author), Tom Dykstra (Author), Rick
Anderson (Author), & 1 more
3 Microsoft Azure Essentials Azure Web Apps for Developers Kindle Edition
by Rick Rainey (Author)
4 Introducing Windows Azure for IT Professionals 1st Edition, Kindle Edition
by Mitch Tulloch (Author)
5 Microsoft Azure Essentials Azure Machine Learning Kindle Edition
by Jeff Barnes (Author)
MOOC/ Certification Courses
1 https://azure.microsoft.com/en-us/
2 https://docs.microsoft.com/en-us/azure/
3 https://www.tutorialspoint.com/microsoft_azure/
Question Paper Scheme:
University Examination Duration: 3 Hours
Note for Examiner: -
(I) Questions 1 and 4 are compulsory with no options.
(II) Internal options should be given in questions 2, 3, 5 and 6.
SECTION - I
Q.1 –8 Marks
Q.2 –11 Marks
Q.3 –11 Marks
SECTION - II
Q.4 –8 Marks
Q.5 –11 Marks
Q.6 –11 Marks
149
GANPAT UNIVERSITY
FACULTY OF COMPUTER APPLICATIONS Programme Master of Computer Application Branch/Spec. Computer Applications
Semester V Version 1.0.0.0
Effective from Academic Year 2020-21 Effective for the batch Admitted in June 2019
Subject Code P15A6SDP1 Subject Name SYSTEM DEVELOPMENT PROJECT - I
Teaching scheme Examination scheme (Marks)
(Per week) Lecture (DT) Practical (Lab.) Total CE SEE Total
L TU P TW
Credit - - 5 - 5 Theory - - -
Hours - - 10 - 10 Practical 60 40 100
Pre-requisites:
Students have basic knowledge of system analysis and design with the implementation ability in any one
technology.
Learning Outcome:
Student can study, analyse, design, implement and evaluate the information system.
Theory Syllabus : NA
Rules for the Project:
The students can develop their project individually or in a group of two is preferable.
The project can be developed in any language or platform but it is required to get it
approved by the head of the department. For the purpose of approval, they have to
submit their project titles and proposals with the name of internal and external
guides to the Head of Institution or Project Coordinator within 7 days of the
commencement of the semester. In case, if the student proposal is rejected, the
revised proposal in the same or other area, is required to submit and get it sanctioned
within next 7 days. Failing to do this, he/she will not be qualified for this subject.
The students have to report to the internal guide for at least 3 times during the
project lifespan with the progress report duly signed by guide. Moreover, they have
to bring these reports with the final report at the time of external examination.
The Internal Guide/Project Coordinator of Department will give the internal marks.
These marks may be given on the bases of regular reporting of the student to the
internal guide, quality of project work and a report obtained from the external guide.
150
The external examiners appointed by the University will give the external marks on
the basis of the heads like Presentation, Demonstration, Viva Voice, and
Documentation etc. The distribution of the marks to different heads may be decided
at the time of evaluation of the project but it is expected to have the same
distribution.
Text Books:
N.A.
Practical content:
N.A.
Web Reference:
N.A.