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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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

Course outcomes : On successful completion of the course, the students should be able to

CO1. Quote and understand the definition of a limit of a sequence or a function in its various forms.

CO2. Demonstrate the convergence or divergence of the geometric and harmonic series and other standard series.

CO3. Apply the basic tests for convergence of infinite series.

CO4. Prove the tests for convergence: Comparison Test, Ratio Test, Cauchy’s Root test, Raabe’s Test, alternating series test etc.

CO5. Understand the differences between convergence and absolute convergence

CO6. Understand and solve binomial , logarithmic and exponential series

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern

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.

Text Books And Reference Books:
Essential Reading / Recommended Reading
Evaluation Pattern