Department of
COMPUTER SCIENCE






Syllabus for
Bachelor of Science (Computer Science, Mathematics)
Academic Year  (2023)

 
3 Semester - 2022 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
CSC333Y DESIGN AND ANALYSIS OF ALGORITHMS 4 3 100
CSC337Y INFERENTIAL STATISTICS 4 4 100
CSC371Y DATABASE MANAGEMENT SYSTEM 5 4 100
CSC372Y WEB TECHNOLOGY 5 4 100
MAT331 REAL ANALYSIS 4 4 100
MAT332Y COMPLEX ANALYSIS 4 2 50
4 Semester - 2022 - Batch
Paper Code
Paper
Hours Per
Week
Credits
Marks
CSC432Y SOFTWARE PROJECT DEVELOPMENT 3 3 100
CSC434Y USER INTERFACE DESIGN 3 2 100
CSC471Y PROGRAMMING IN JAVA 5 100 4
CSC473Y WEB STACK DEVELOPMENT 4 3 100
MAT431 ALGEBRA 4 4 100
MAT451Y DATA ANALYSIS USING PYTHON 2 2 50

CSC333Y - DESIGN AND ANALYSIS OF ALGORITHMS (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The main objective of this course is to inculcate fundamental knowledge and practical experience with, the principles of data structures. It includes the concepts and

terminologies which facilitate the construction of algorithms. The objective also includes indoctrinating the activities of implementation of algorithm analysis.

Learning Outcome

CO1: Understand the fundamentals of data structures.

CO2: Understand the design paradigms of algorithms.

CO3: To apply tree and graph-based algorithms.

CO4: Develop dynamic and greedy models and experiment with the algorithms using appropriate analysing methods.

Unit-1
Teaching Hours:9
Introduction to Data Structures
 

Introduction, Abstract Data Type (ADT), Arrays, Linked List, Stack, Queue, Graphs, Trees, Sets, and Dictionaries.

Unit-2
Teaching Hours:12
Algorithm Design Paradigm
 

Characteristics of the algorithm, Algorithm Specification, Analysis Framework Performance Analysis Space complexity, Time complexity; Asymptotic Notations: Big-

Oh notation (O), Omega notation (Ω), Theta notation (Θ), and Little-oh notation (o), Mathematical analysis of Non-Recursive and recursive Algorithms with Examples.

Unit-3
Teaching Hours:15
Tree Graph based Algorithms
 

Binary Tree, Self-Balancing Binary, Heap-Adjacency Matrix and Adjacency List, Shortest Path Algorithms: Dijkstra's algorithm, Bellman-Ford Algorithm, Johnson Algorithm.

Minimum Spanning Tree - Kruskal's Algorithm, Prim's Algorithm, Graph Coloring Algorithm. Divide-and-Conquer Algorithms: Mergesort, Quicksort, Binary Search,

Stressens Matrix Multiplication.

Unit-4
Teaching Hours:12
Dynamic Programming Greedy Algorithms
 

Dynamic Programming: Floyd Warshall Algorithm, 0-1 Knapsack Problem, Subset Sum Problem, Travelling Salesman Problem, Bellman–Ford Algorithm; Greedy

Algorithms: Activity Selection Problem, Job Sequencing Problem, Huffman Coding.

Unit-5
Teaching Hours:8
Analysis of Algorithms
 

Complexity Analysis techniques: Master theorem, Substitution Method, Iteration Method; Time Complexity Bound for Sorting: Comparison Sort, Non-comparison sort; Time

Complexity Bound for Searching - Linear Search, Binary Search, Interpolation Search; Complexity Classes: P class, NP-Complete, NP-Hard.

Text Books And Reference Books:

[1]. Thomas H. Cormen., Charles E. Leiserson., Ronald L . Rivest., Lifford Stein, “Introduction to Algorithms, Third Edition, PHI Learning Pvt. Ltd., 2010.

[2]. Anany Levitin, “Introduction to the Design and Analysis of Algorithms”. 3rd Edition, Pearson Education, 2017.

[3] S. Sridhar “Design and Analysis of Algorithms”, Oxford University Press, 2014.

Essential Reading / Recommended Reading

[1]. Steven S Skiena, “The Algorithm Design Manual”, 2nd Edition, 2008, Springer, 2008.

[2] Alfred V Aho, Jeffrey D. Ullman, and John E. Hopcroft, “Data Structures & Algorithms”, First Edition, 2002, Pearson Education India.

Evaluation Pattern

CIA 50%

ESE 50%

CSC337Y - INFERENTIAL STATISTICS (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Basic principles for statistical inference with practical applications of data. Point estimation, confidence intervals, hypothesis testing, ANOVA, and simple linear

regression are included. And includes the use of statistical software.

Learning Outcome

CO1: Demonstrate strong conceptual knowledge of probability and different distributions.

CO2: Represent and visualize data in different ways.

CO3: Perform statistical analysis based on sampled data.

CO4: Perform hypothesis testing on sampled data.

CO5: Identify correlation between different variables characterizing the samples and perform different regression analysis.

Unit-1
Teaching Hours:12
INTRODUCTION
 

Population and Statistics –– Types of sampling - Sampling Distribution – Sampling Error - Standard Error – Test of significance –concept of hypothesis –testing – Critical region –

level of significance - Power of the test.

Unit-2
Teaching Hours:12
TESTING OF HYPOTHESIS I
 

Concept of large and small samples – Tests concerning a single population mean for known σ – equality of two means for known σ – Test for Single variance - Test for equality

of two variances for normal population – Tests for single proportion – Tests of equality of two proportions for the normal population.

Unit-3
Teaching Hours:12
TESTING OF HYPOTHESIS II
 

Students' t-distribution and its properties (without proofs) – Single sample mean test – Independent sample mean test – Paired sample mean test – Tests of proportion (based on t

distribution) – F distribution and its properties (without proofs) – Tests of equality of two variances using F-test – Chi-square distribution and its properties (without proofs) –

chi-square test for independence of attributes – Chi-square test for goodness of fit.

Unit-4
Teaching Hours:12
ANALYSIS OF VARIANCE
 

Meaning and assumptions - Fixed, random and mixed effect models - Analysis of variance of one-way and two-way classified data with and without interaction effects – Multiple

comparison tests: Tukey’s method - critical difference.

Unit-5
Teaching Hours:12
NONPARAMETRIC TESTS
 

Concept of Nonparametric tests - Run test for randomness - Sign test and Wilcoxon Signed Rank Test for one and paired samples - Run test - Median test and Mann-Whitney-

Wilcoxon tests for two samples.

Text Books And Reference Books:

1. Gupta S.C and Kapoor V.K, Fundamentals of Mathematical Statistics, 12th edition, Sultan Chand & Sons, New Delhi, 2020.

2. Brian Caffo, Statistical Inference for Data Science, Learnpub, 2016.

Essential Reading / Recommended Reading

1. Walpole R.E, Myers R.H and Myers S.L, Probability and Statistics for Engineers and Scientists, 9th edition, Pearson, New Delhi, 2017.

2. John V, Using R for Introductory Statistics, 2nd edition, CRC Press, Boca Raton, 2014.

3. Rajagopalan M and Dhanavanthan P, Statistical Inference, PHI Learning (P) Ltd, New Delhi, 2012.

4. Rohatgi V.K and Saleh E, An Introduction to Probability and Statistics, 3rd edition, JohnWiley & Sons Inc, New Jersey, 2015.

Evaluation Pattern

CIA 50%

ESE 50%

CSC371Y - DATABASE MANAGEMENT SYSTEM (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

The main objective of this course is to impart fundamental knowledge and practical experience with database concepts. It also introduces the concepts and SQL structures towards the construction of relational databases, writing effective queries, comprehending data processing, and writing queries on databases.

Learning Outcome

CO1: Understand the fundamentals of database system, architecture and Relational Model

CO2: Understand and apply the design principles of E-R model and Relational model

CO3: Learn and apply data modelling concepts and design database systems.

CO4: Develop database-dependent application programs with ethical coding standards.

Unit-1
Teaching Hours:15
Introduction to Database System and Relational Model
 

Database-System Applications - Purpose of Database Systems - View of Data - Database Languages - Database Design - Database Engine - Database and Application Architecture -

Database Users and Administrators - History of Database Systems. Overview of the Design Process - The Entity-Relationship Model - Complex Attributes - Mapping Cardinalities - Primary Key - Removing Redundant Attributes in Entity Sets - Reducing E-R Diagrams to Relational Schemas - Entity-Relationship Design Issues.

Lab Exercises:

1. Creation of E-R model with attributes

2. Defining relationships among entities

3. Converting E-R model into the Relational model

Unit-2
Teaching Hours:15
Database Design: Relational Model
 

Structure of Relational Databases - Database Schema - Keys - Schema Diagrams - Relational Query Languages - The Relational Algebra

Features of Good Relational Designs - Decomposition Using Functional Dependencies - Normal Forms.

Lab Exercises:

1. Creation of Tables with Keys (Unique, Not-null, Primary and Foreign keys)

2. Altering Tables and Dropping Tables

3. Practicing DML commands- Insert, Select, Update, Delete

Unit-3
Teaching Hours:20
Structured Query Language
 

Overview of the SQL Query Language - SQL Data Definition - Basic Structure of SQL Queries - Additional Basic Operations - Set Operations - Null Values - Aggregate Functions -

Nested Sub-queries. Join Expressions - Views - Transactions - Integrity Constraints - SQL Data Types and Schemas - Index Definition in SQL - Authorization.

Lab Exercises:

1. Practicing Sub-queries (Nested, Correlated)

2. Working with types of Joins (Left, Right, Inner, Outer, Equi)

3. Creation and working with Views

Unit-4
Teaching Hours:15
Indexing and Transaction Management
 

Indexing: Basic Concepts - Ordered Indices - B+ Tree Index Files - B+ Tree Extensions -Hash Indices - Multiple-Key Access - Creation of Indices.

Transaction: Transaction Concept - Simple Transaction Model – ACID Properties - Transaction Atomicity and Durability - Transaction Isolation - Serializability - Transaction

Isolation Levels. Concurrency Control: Lock-Based Protocols - Deadlock Handling - Timestamp-Based Protocols - Validation-Based Protocols

Lab Exercises:

1. Basic programing with PL/SQL Block

2. Cursors – Declaring, Opening & closing Cursor, Fetching the data

Unit-5
Teaching Hours:10
Advanced Concepts
 

Big Data: Motivation - Big Data Storage Systems - The MapReduce Paradigm - Beyond MapReduce: Algebraic Operations - Streaming Data - Graph Databases.

Blockchain Databases: Overview - Blockchain Properties - Achieving Blockchain Properties via Cryptographic Hash Functions - Consensus - Data Management in a

Blockchain - Smart Contracts - Performance Enhancement - Emerging Applications 

Lab Exercises:

1. Database triggers - the creation of trigger

2. Data Manipulation (Insertion, Deletion, Updation) and alerts using triggers.

Text Books And Reference Books:

[1] Silberschatz A, Korth HF, Sudarshan S., “Database system concepts”. 7 th Edition McGraw-Hill; 2021.

Essential Reading / Recommended Reading

[1]. Thomas Connolly, Carolyn Begg, “Database Systems | A Practical Approach to Design, Implementation, and Management”, 6 th Edition, Pearson, 2019

[2]. Elmasri Ramez, Navathe Shamkant, “Fundamentals of Database Systems”, 7 th Edition, Pearson Education, 2017.

Evaluation Pattern

ESE 50%

CIA 50%

CSC372Y - WEB TECHNOLOGY (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

The main objective of this course is to:

1. Able to understand the fundamental concepts of Internet, WWW, HTML, CSS,

JavaScript, JQuery.

2. Enable the students to make their webpages and host the website on the Internet

Learning Outcome

CO1: Students will acquire the skills necessary to create and host a website on the Internet

CO2: Comprehensive understanding of the various technologies utilized in the

CO3: Knowledgeable in the principles of Internet connectivity.

Unit-1
Teaching Hours:5
Introduction
 

Introduction to the Internet: Electronic mail - Remote Login - WWW - Browsers - Introduction to static, dynamic, and active web pages - Client-server model, Protocols: IP,

HTTP, and HTTPs protocols.

Unit-2
Teaching Hours:20
HTML
 

Structuring documents for web: A web of Structured documents Introducing HTML5 - Attribute Groups - Core Elements - Basic Text Formatting - Working with Lists - Fine

Tuning your Text: Elements that describe Text Level Semantics - Links and Navigation: Basic Links - Creating in-page links with <a> tag - Images, Audio, and Video: Adding

elements using <img> element - Adding video and audio to your web pages. HTML Tables: Introducing Tables - Basic Table Elements and Attributes - Adding caption to a Table -

Grouping sections of a table - Nested Tables - Forms: Introducing Forms - creating a form with form elements - Form controls - Semantic Elements - Input elements.

Lab Exercises:

● Develop a webpage using the basic elements and list

● Include a navigation elements to develop a webpage

● Develop a webpage with images, videos, and audio elements

● Design a web page with tables

● Design a web page - Registration page with all form elements

● Link all the webpages to create a website

Unit-3
Teaching Hours:20
CSS
 

Introduction to CSS- Inline styles - Embedded Style Sheets - Conflicting Styles - Linking External Style Sheets - Transform , Transition, Positioning elements - Box Model and Text

Flow - Building a CSS drop-down menu - User-defined styles. 

Lab Exercises:

● Demonstrate the Inline, Embedded/Internal, and External style sheets

● Demonstrate User-defined styles in CSS

● Div Based design and CSS based design comparison

● Design webpage that uses the Box Model CSS

Unit-4
Teaching Hours:20
JavaScript
 

Learning How to add a script to your pages - create an external JavaScript - The Document Object Model - Starting to program with JavaScript - Variables - Operators -

Functions - Conditional Statements - Looping - Events - Built-in Objects: String - Window.

Lab Exercises:

● Demonstrate the JavaScript variables, operators, and control structures

● Demonstrate JavaScript functions

● Demonstrate the Window and String objects of JavaScript

Unit-5
Teaching Hours:10
Responsive Web Apps
 

Introduction to the responsive web application: Benefits of a responsive design - Technology stack - measuring responsiveness - Responsive frameworks - Creating a responsive

framework for a web application: required software and tools - setting up a Java-based web project - creating a wireframe for a web application - Responsive layouts - creating a layout for large and small devices - Developing the layout - Verifying the layout. Working with

JQuery: Adding JQuery to your page - JQuery basics - JQuery and the DOM.

Lab Exercises:

● Demonstrate on how to develop and verify the layout for responsive web applications

● Demonstrate how to add JQuery to a webpage

Text Books And Reference Books:

1. Rob Larsen, Beginning HTML and CSS, Wiley Publishing Inc, 2013.

2. Sandeep Kumar Patel, Developing Responsive Web Applications with AJAX and JQuery, Packt Publications, 2014.

3. Thomas A Powell, The Complete Reference: HTML & CSS, Tata McGraw Hill, Fitfh edition, 2003.

Essential Reading / Recommended Reading

1. Paul Deitel, Harvey Deitel, Abbey Deitel, Internet & World Wide Web - How to Program, 5th edition, Pearson Education, 2012.

2. Kogent Learning Solutions Inc, Web Technologies Black Book, Dream Tech press, 2013.

3. Richard York, Web Development with JQuery, Wrox publisher, 2015.

Evaluation Pattern

CIA 50%

ESE 50%

MAT331 - REAL ANALYSIS (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course description : This course enables the students to understand the basic techniques and theories of real Analysis.

 

Course objectives : This course will help the learner to

COBJ1. examine the convergence or divergence of sequences and series.

COBJ2. understand the different types of convergence and their properties.

 

Learning Outcome

CO1: understand the concepts of limits, infimum, supremum, and boundedness of sequences.

CO2: examine the convergence of series using various tests.

CO3: distinguish between different types of convergence of sequence and series.

CO4: identify the region of convergence for sequence and series of functions.

Unit-1
Teaching Hours:20
Sets and Sequences
 

Open sets, closed sets, closure of a set, countable and uncountable sets, topology of real line. Sequences: Definition of Sequences, limit of a sequence, algebra of limits of a sequence, convergent, divergent, and oscillatory sequences, problems thereon. Bounded sequences, Monotonic sequences and their properties, Cauchy sequence.

Unit-2
Teaching Hours:20
Infinite Series
 

Infinite series, Cauchy convergence criterion for series, geometric series, comparison test, convergence of p-series, D'Alembert's Ratio test, Raabe's test, Cauchy's Root test, alternating series, Leibnitz’s test. Definition and examples of absolute and conditional convergence.

Unit-3
Teaching Hours:20
Sequence and Series of functions
 

Sequences and series of functions, Pointwise and uniform convergence. Mn - test, M-test, Statements of the results about uniform convergence. Power series and radius of convergence.

Text Books And Reference Books:

S.C.Malik and Savita Arora, Mathematical Analysis , Second Edition, New Delhi, India: New Age international (P) Ltd., 2005.

Essential Reading / Recommended Reading
  1. R.G. Bartle and D. R Sherbert, Introduction to Real Analysis, John Wiley and Sons (Asia) P. Ltd., 2000.
  2. E. Fischer, Intermediate Real Analysis ,1 st ed.(Reprint), Springer Verlag, 2012.
  3. K.A. Ross, Elementary Analysis- The Theory of Calculus Series- Undergraduate Texts in Mathematics, Springer Verlag, 2003.
  4. S Narayana and M.D. Raisinghania, Elements of Real Analysis, Revised ed., S. Chand & Company Ltd, 2011.
  5. T. M. Apostol, Calculus (Vol. I), John Wiley and Sons (Asia) P. Ltd., 2002.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT332Y - COMPLEX ANALYSIS (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description: This course enables the students to understand the basic theory and principles of complex analysis.

Course Objectives​: This course will help the learner to

COBJ1. Understand the theory and geometry of complex numbers.

COBJ2. Evaluate derivatives and integrals of functions of complex variables.

COBJ3. Examine the transformation of functions of complex variables. 

Learning Outcome

CO1: Understand the concepts of limit, continuity, differentiability of complex functions

CO2: Evaluate the integrals of complex functions using Cauchy?s Integral Theorem/Formula and related results

CO3: Examine various types of transformation of functions of complex variables.

CO4: Apply the concepts of complex analysis to analyze and address real world problems.

Unit-1
Teaching Hours:15
Analytic Functions
 

Properties of complex numbers, regions in the complex plane, functions of complex variable, limits, limits involving the point at infinity, continuity and differentiability of functions of complex variable. Analytic functions, necessary and sufficient conditions for a function to be analytic. 

Unit-2
Teaching Hours:15
Complex Integration and Conformal Mappings
 

Definite integrals of functions, contour integrals and its examples, Cauchy’s integral theorem, Cauchy integral formula, Liouville’s theorem and the fundamental theorem of algebra, elementary transformations, conformal mappings, bilinear transformations.

Text Books And Reference Books:

Dennis G. Zill and Patrick D. Shanahan, A first course in Complex Analysis with Applications, 2nd Ed, Jones & Barlett Publishers, 2011. 

Essential Reading / Recommended Reading

1.  J. W. Brown and R. V. Churchill, Complex Variables and Applications, 8th ed., McGraw – Hill International Edition, 2009.

2.  J. Bak and D. J. Newman, Complex analysis, 2nd ed., Undergraduate Texts in Mathematics, Springer-Verlag New York, Inc., New York, 2000.

3.  A. Jeffrey, Complex Analysis and Applications, 2nd ed., CRC Press, Boca Raton 2013.

4.  L. V. Ahlfors, Complex Analysis, 3rd ed., McGraw-Hill Education, 2017.

5. S. Ponnusamy, Foundations of Complex Analysis, 2nd ed., Narosa Publishing House, Reprint 2021.

Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

Written assignment and Test

Mastery of the core concepts and Problem solving skills

5

CIA II

Mid-Semester Examination

Basic, Conceptual and analytical knowledge of the subject

10

CIA III

Problem solving assignment and Test

Problem solving skills

5

 

Attendance

Regularity and Punctuality

5

ESE

 

Basic, Conceptual and analytical knowledge of the subject

25

Total

50

CSC432Y - SOFTWARE PROJECT DEVELOPMENT (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

The aim of the course is to provide an understanding of the working knowledge of the techniques for estimation, design, testing and quality management of large software

development projects. Topics include process models, software requirements, software design, software testing, software process/product metrics, project management, risk

management, quality management, and UML diagrams.

Learning Outcome

CO1: Ability to translate end-user requirements into system and software requirements, using UML, and structure the requirements in a Software Requirements Document (SRD).

CO2: Identify and apply appropriate software architectures and patterns to carry out high level design of a system and be able to critically compare alternative choices.

CO3: Will have experience and/or awareness of testing problems and will be able to develop a simple testing report.

CO4: Develop and Manage dynamic models and experiment with the SDLC using appropriate methods.

Unit-1
Teaching Hours:9
Introduction to Software Engineering
 

Introduction: The evolving role of software, changing nature of software, software myths. A Generic view of process: Software engineering- a layered technology, a process

framework, the capability maturity model integration (CMMI), process patterns, process assessment, personal and team process models. Process models: The waterfall model,

incremental process models, evolutionary process models, the unified process.

Unit-2
Teaching Hours:9
The Requirements Engineering
 

Software Requirements: Functional and non-functional requirements, user requirements, system requirements, interface specification, the software requirements document.

Requirements engineering process: Feasibility studies, requirements elicitation and analysis, requirements validation, and requirements management. System models: Context

models, behavioural models, data models, object models, structured methods

Unit-3
Teaching Hours:9
The Design Engineering
 

Design Engineering: Design process and design quality, design concepts, the design model.  Creating an architectural design: software architecture, data design, architectural styles

and patterns, architectural design, conceptual model of UML, basic structural modelling, class diagrams, sequence diagrams, collaboration diagrams, use case diagrams, component

diagrams.

Unit-4
Teaching Hours:9
Software Testing and Metrics
 

Testing Strategies: A strategic approach to software testing, test strategies for conventional software, black-box and white-box testing, validation testing, system testing, the art of debugging. Product metrics: Software quality, metrics for analysis model, metrics for design model, metrics for source code, metrics for testing, metrics for maintenance. : Software measurement, metrics for software quality.

Unit-5
Teaching Hours:9
Project Management and Control
 

Framework for Management and control – Visualizing progress – Cost monitoring – Earned Value Analysis– Project tracking –Software Configuration Management–

Contract Management. Project schedules – Activities, Sequencing and scheduling – Network Planning models – Formulating Network Model – Critical path (CRM) method –

PERT technique – Risk identification –Risk Planning –Risk Management.

Text Books And Reference Books:

[1]. Software Engineering, A practitioner’s Approach- Roger S. Pressman, 6th edition, Mc Graw Hill International Edition, 2019.

[2]. Bob Hughes, Mike Cotterell and Rajib Mall: Software Project Management – Fifth Edition, Tata McGraw Hill, New Delhi, 2012.

Essential Reading / Recommended Reading

[1]. Software Engineering- Sommerville, 7th edition, Pearson Education, 2017.

[2]. Robert K. Wysocki ―Effective Software Project Management – Wiley Publication, 2011.

[3]. The unified modelling language user guide Grady Booch, James Rambaugh, Ivar Jacobson, Pearson Education, 2015.

Evaluation Pattern

CIA 50%

ESE 50%

CSC434Y - USER INTERFACE DESIGN (2022 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:2

Course Objectives/Course Description

 

The main objectives of this course are to

1. create user-centred interfaces that are intuitive, efficient, and aesthetically pleasing.

2. well-designed UI that makes it easy for users to accomplish their goals and tasks, whether that's filling out a form, making a purchase, or finding information.

Learning Outcome

CO1: Understanding principles of user-centred design and how to apply them in practice

CO2: Developing skills in designing and prototyping user interfaces using relevant software tools.

CO3: Creating user interfaces that are accessible to diverse audiences, including people with disabilities.

CO4: Applying design thinking and iterative design methodologies to create effective user interfaces.

Unit-1
Teaching Hours:9
Introduction to UI Design
 

Definition and importance of UI design , Overview of the UI design process, Understanding user needs and expectations. User Research and Analysis User research methods,

Analyzing user data, Personas and scenarios

Unit-2
Teaching Hours:9
UI Design Principles and Guidelines
 

Principles of effective UI design, Usability and accessibility guidelines, Designing for different devices and platforms

Unit-3
Teaching Hours:9
Visual Design for UI
 

Color theory and typography, Layout and composition, Iconography and imagery

Unit-4
Teaching Hours:9
Interaction Design
 

Defining user interactions, Designing interaction patterns, Animations and transitions Prototyping and Testing - Prototyping tools and methods, Usability testing and feedback,

Iterative design process

Unit-5
Teaching Hours:9
UI Design Tools and Technologies
 

Overview of popular UI design tools , Integrating design with front-end development, Trends in UI design and emerging technologies Project and Portfolio Hands on project to apply UI

design skills, Creating a professional portfolio, Presenting and pitching design solutions. 

Tools for hands on practice – Sketch, Adobe XD, Figma, InVision Studio ,Axure RP ,Balsamiq, Moqups, Marvel, Zeplin, UXPin, Canva, Gravit Designer, Proto.io, Webflow, Affinity Designer

Text Books And Reference Books:

1. Make Me Think" by Steve Krug, Third Edition, Publisher Pearson Education, Publication date 1 January 2015

2. The Design of Everyday Things" by Don Norman revised and expanded edition (The MIT Press) Paperback – 20 Dec. 2013.

3. About Face: The Essentials of Interaction Design" by Alan Cooper, Robert Reimann,and Dave Cronin, Wiley Publishing, Inc., 2007

4. Seductive Interaction Design" by Stephen Anderson, Publisher New Riders, Edition 1 st , Publication date 15 June 2011

5. Designing Interfaces" by Jennifer Tidwell, Released January 2020 , Publisher(s): ;Reilly Media, Inc.

Essential Reading / Recommended Reading

1 A Practical Guide to Designing for the Web" by Mark Boulton, Publisher Mark Boulton Design Ltd, Publication date 14 April 2009

2 Universal Principles of Design by William Lidwell, Kritina Holden, and Jill Butler, Released January 2010, Publisher(s): Rockport Publishers

3 Designing for Interaction" by Dan Saffer, Publisher: Peachpit Press Publication date: July 2006

4 The Elements of User Experience" by Jesse James Garrett, Publisher New Riders, Publication date 16 December 2010

5. “100 Things Every Designer Needs to Know About People" by Susan Weinschenk, Released April 2011, Publisher(s): New Riders

Evaluation Pattern

CIA 50%

ESE 50%

CSC471Y - PROGRAMMING IN JAVA (2022 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:4
Credits:100

Course Objectives/Course Description

 

This course teaches students how to develop java applications. The course gives an overview of the difference between C++ and Java. Students will be developing and testing java

application as a practical course work. The course introduces the concept of GUI design in java

Learning Outcome

CO1: Understand the OOPS programming concepts.

CO2: Identify the classes and objects.

CO3: Design and create Java packages , interfaces and threads

CO4: Construct GUI application Using Java

Unit-1
Teaching Hours:12
UNIT 1
 

Introduction-Object Oriented paradigm-Basic concepts of object-oriented programming- Benefits of OOP-Applications of OOP- Java Features- How Java differs from C and C++ –

Java and Internet – Java and www – simple Java program –Structure – Java Tokens – Statements.

Unit-2
Teaching Hours:15
UNIT 2
 

Constants, Variables, Data Types - Operators and Expressions – Decision Making and Branching: if, if...else, nested if, switch, ? operator - Decision Making and Looping: while,

do, for –Jumps in Loops - Labeled Loops – Classes, Objects and Methods.

1. Define all types of variables and display it

2. Demonstrate types of operators in Java

3. Demonstrate looping structure in Java

4. Implement the objects and methods using JAVA

Unit-3
Teaching Hours:15
UNIT 3
 

Arrays- Introduction-One dimensional arrays –Two dimensional arrays-Strings-Vectors-

Enumerated types-Interfaces- Defining, Extending and implementing interfaces- Packages

–JAVA API packages- creating packages-Accessing packages-Adding a class to a package-

Hiding classes.

1. Write a program to create array and display the elements

2. Write a program to demonstrate String handling in Java

3. Write a program to demonstrate User Defined Packages.

4. Write a program to demonstrate -Defining Interfaces, Implementing Interfaces.

Unit-4
Teaching Hours:15
UNIT 4
 

Multithreaded Programming-creating threads- extending thread class- stopping and blocking a thread-life cycle of a thread-synchronization- Implementing a Runnable interface- Inter

thread communication-Managing Errors and Exceptions.

1. Write a program to demonstrate creation of thread using runnable interface.

2. Write a program to demonstrate life cycle of a Thread.

3. Write a program to demonstrate exception handling using try catch block

Unit-5
Teaching Hours:18
UNIT 5
 

Introduction to Event Handling and GUI: Event Classes – Event Listener Interfaces. Event types, Mouse and key events, GUI Basics, Panels, Frames, Layout Managers: Flow Layout,

Border Layout, Grid Layout, GUI components like Buttons, Check Boxes, Radio Buttons, Labels, Text Fields, Text Areas, Combo Boxes, Lists, Scroll Bars, Sliders, Windows,

Menus and Dialog Box

1. Write a program to demonstrate Label and Text box controls

2. Write a program to demonstrate Button, combo box, check box, and radio button controls

3. Write a program to demonstrate Menu and dialog box controls

Text Books And Reference Books:

E. Balagurusamy Programming with JAVA – A PRIMER - Tata McGraw-Hill - 2019 (6th Edition).

Essential Reading / Recommended Reading

1. Patrick Naughton & Hebert Schildt - The Complete Reference Java 2 - TMH publications (9th edition). 2014

2. John R. Hubbard - Programming With Java - TMH publications - (2nd Edition). 2020

Evaluation Pattern

ESE 50%

CIA 50%

CSC473Y - WEB STACK DEVELOPMENT (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:3

Course Objectives/Course Description

 

On completion of this course, a student will be familiar with full stack and able to develop a web application using advanced technologies and cultivate good web programming style and

discipline by solving the real world scenarios.

Learning Outcome

CO1: To develop front end application using PHP

CO2: To become proficient in Bootstrap concepts

CO3: To develop front end applications using along with jQuery, and AngularJS framework

CO4: To building Strong expertise in ReactJS and Nodejs

Unit-1
Teaching Hours:8
UNIT 1
 

Using PHP-Embedding PHP in HTML- Adding Dynamic Content-Accessing Form Variables - Server-side programming using - PHP - Storing and retrieving data - Using Arrays - String

Manipulation and Regular Expressions - Reusing Code and Writing Functions - Object — Oriented PHP.

Unit-2
Teaching Hours:12
UNIT2
 

Introduction to Bootstrap - Basics-Grids-Themes-CSS-JS, Introduction to jQuery- Syntax - Selectors -Events-Effects-HTML-Traversing-AJAX & Misc

Unit-3
Teaching Hours:15
UNIT 3
 

Introduction to Angular - Application Architecture- What is NgModule- Components - Templates - Data Binding - Types of Data Binding - Modules Component Working -

Directives - Structure Directives - Template Routing - Theme Implementation in Angular Framework - Angular Forms - Services - Inject Services - Angular Server Communication

With Backend Server - Working of API's(GET,POST,PUT,DELETE) - Complete Web application In Angular Framework

Unit-4
Teaching Hours:15
UNIT 4
 

ReactJS - Introduction to ReactJS -Understand ReactJSLibrary & directory- React Components-Types of Components-Build a simple React component- Component

composition-Component styling- Add styles to your components- Component inter communication.

Unit-5
Teaching Hours:10
UNIT 5
 

Nodejs : Introduction to Nodejs - Architecture of Nodejs Application - Synchronous and Asynchronous Programming - Call back Function in nodejs - Promises in Nodejs - Mongodb

with Nodejs - Design the Schema in Nodejs

Text Books And Reference Books:

1. Bootstrap Reference Guide Bootstrap 4 and 3 Cheat Sheets Collection By Jacob Lett · 2018

2. Modern PHP New Features and Good Practices By Josh Lockhart · 2015

Essential Reading / Recommended Reading

1. Node.js, MongoDB and Angular Web Development By Brad Dayley, Brendan Dayley, Caleb Dayley · 2017

2. React Js for Beginners A Comprehensive Beginner's Guide to ReactJS By Emma William 2021, ISBN: 9798700131568, Publisher: Independently Published.

3. React and React Native A Complete Hands-on Guide to Modern Web and Mobile Development with React.js, By Adam Boduch, Roy Derks · 2020, Publisher: Packt Publishing

Evaluation Pattern

CIA 50%

ESE 50%

MAT431 - ALGEBRA (2022 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course description : This course aims at developing the ability to write the mathematical proofs.  It helps the students to understand and appreciate the beauty of the abstract nature of mathematics and also to develop a solid foundation of theoretical mathematics.

Course objectives : This course will help the learner to

COBJ1. Understand the fundamentals of groups and its theories.

COBJ2. Relate abstract algebraic constructs to more familiar sets and operators

COBJ3. Know about the subgroups and group homomorphisms

COBJ4. Get familiar with the theories on rings, integral domains and fields.

Learning Outcome

CO1: Describe and generate groups, rings and fields.

CO2: Identify and differentiate different structures and understand how changing properties give rise to new structures.

CO3: Demonstrate the knowledge of concepts of rings and fields.

Unit-1
Teaching Hours:15
Groups
 

Definition and examples of groups, examples of abelian and non-abelian groups, the group Zn of integers under addition modulo n and the group U(n) of units under multiplication modulo n, complex roots of unity, groups of symmetries: Equilateral triangle.

Unit-2
Teaching Hours:25
Subgroups and Group Homomorphisms
 

Subgroups, the concept of a subgroup generated by a subset and the commutator subgroup of group, examples of subgroups including the center of a group. order of an element, cyclic subgroups, Cosets, Index of subgroup, Lagrange’s theorem, consequences of Lagrange’s theorem, Normal subgroups: their definition, examples, and characterizations, Quotient groups, permutation groups and Symmetric groups – Homomorphism of groups – Kernel of group homomorphisms and theorems thereon – Fundamental theorem of homomorphism of group.

Unit-3
Teaching Hours:20
Rings, Integral Domain and Fields
 

Definition and examples of rings, examples of commutative and non-commutative rings: rings from number systems, Zn the ring of integers modulo n, ring of real quaternions, rings of matrices, polynomial rings, and rings of continuous functions. Subrings and ideals, Integral domains and fields, examples of fields: Zp, Q, R, and C. Field of rational functions.

Text Books And Reference Books:
  1. I. N. Herstein, Topics in Algebra, Second Edition. Wiley India (P) Ltd. New Delhi, India Vikas Publishing House Pvt. Ltd, 2006.
Essential Reading / Recommended Reading
  1. M. Artin, Abstract Algebra, 2nd Ed., Pearson, 2011.
  2. S. R. Nagpaul and S.K.Jain, Topics in Applied Abstract Algebra, Universities Press, 2010.
  3. Joseph A Gallian, Contemporary Abstract Algebra, 4th Ed., Narosa, 2000.
  4. Pinter, Charles C. A Book of Abstract Algebra, New York: McGraw-Hill, 1990.
  5. J. B. Fraleigh, A First Course in Abstract Algebra, 7th Ed., Pearson, 2002.
Evaluation Pattern

 

Component

Mode of Assessment

Parameters

Points

CIA I

MCQ,

Written Assignment,

Reference work, etc.,

Mastery of the core concepts

Problem solving skills

 

10

CIA II

Mid-semester Examination

Basic, conceptual and analytical knowledge of the subject

25

CIA III

Written Assignment, Project

Problem solving skills

10

Attendance

Attendance

Regularity and Punctuality

05

ESE

 

Basic, conceptual and analytical knowledge of the subject

50

Total

100

MAT451Y - DATA ANALYSIS USING PYTHON (2022 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

Course Description:

This course is aimed at enabling the students to appreciate and understand the concepts of mathematics and statistics with the help of Python programming language. Students will learn to use the tools, libraries and packages useful for data analysis.

Course Objectives:

This course will help the learner to:

  • gain proficiency in using Python for programming. 
  • acquire skills in usage of suitable functions/packages of Python for data analysis.
  • acquaint with Numpy and Pandas packages for data manipulating and visualization.
  • illustrates use statistics methods to handle data effectively.

Learning Outcome

CO1: The students will acquire proficiency in using tools, libraries, packages of Python for data analysis.

CO2: The students shall demonstrate the use of Python tools for visualizing data.

CO3: The students will be familiar with the statistical methods for describing data.

Unit-1
Teaching Hours:10
Analysing data with NumPy and Pandas
 

Arrays in NumPy, Creating, Indexing, Slicing, Algebraic operations on array, Python Data structures: List, Tuple, Dictionaries. Data series and Data frames, Using Pandas library to read and write data from a CSV file and Excel file.

Unit-2
Teaching Hours:10
Data Visualization
 

Plotting data in Python using Matplotlib: 2D plots, bar graph, histogram, box plot, pie chart. Plotting data using Seaborn: Line Plot, Scatter Plot, Box plot, Point plot, Count plot, Violin plot, Swarm plot, Bar plot.

Unit-3
Teaching Hours:10
Describing Data with Statistics
 

Mean, Median, Mode, Creating a frequency table, Dispersion, Variance, and standard deviation, Correlation between two data sets- Correlation Coefficient, Regression, GroupBy in Python, foundations of predictive analysis.

Text Books And Reference Books:

Stefanie Molin and Ken Jee, Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and data analysis, 2nd Edition.

Essential Reading / Recommended Reading

Wes McKinney, Python for Data Analysis

Jake VanderPlas, Python Data Science Handbook: Essential Tools for Working with Data, 2nd Edition.

 

Evaluation Pattern

Component

Parameter

Mode of Assessment

Maximum

Points

CIA I

Mastery of the concepts

Lab Assignments

20

CIA II

Conceptual clarity and analytical skills

Lab Exam - I

10

Lab Record

Systematic documentation of the lab sessions.

e-Record work

07

Attendance

Regularity and Punctuality

Lab attendance

03

95-100% : 3

90-94%   : 2

85-89%   : 1

CIA III

Proficiency in executing the commands appropriately.

Lab Exam - II

10

Total

50