BSc. Computer Science (MECS, MPCS, MSCS)

Semester I

Course Title: Programming in C (Theory)

Course Code: CSC101

At the end of the course the student would be able to:

CO1: Acquire knowledge about fundamentals of Computer, Program fundamentals, Algorithms and understand the basics of C.

CO2: Understand and apply the concept of Control Statements, Arrays and program Structures

CO3: Define the syntax and semantics of Functions & Pointers.

CO4: Compare and analyze the approaches of Structures, Union, and Enumeration data types and devise to Files handling in C

Course Title: Programming in C (Practical)

Course Code: CSC111

CO1: Develop C programs using the fundamental programming concepts.

CO2: Design programming solutions to simple technical problems using C language

Semester II

Course Title: Programming in C++ (Theory)

Course Code: CSC202

At the end of the course the student would be able to:

CO1: Understand the basics of C++

CO2: Ability to develop programs with Object Oriented Programming concepts.

CO3: Develop in-depth knowledge about inheritance & C++ Streams

CO4: Define and apply the concepts of Exception & Templates in complex C++ programs.

Course Title: Programming in C++ (Practical)

Course Code: CSC202

CO1: Develop programs that demonstrate Object Oriented Concepts of C++

CO2: Implement solutions for various problems using Classes and Objects

Semester III

Course Title: Implementing Data Structures using C++ (Theory)

Course Code: CSC303

At the end of the course the student would be able to:

CO1: Develop Proficiency to apply core knowledge on implementing Data Structures using C++ programming language.

CO2: Define &Analyze Object Oriented Programming aims to implement real-world entities like Stacks & Queues in programming.

CO3: Acquire hands-on coding; computing abilities for the concepts of Data structures like Arrays, Linked list, Trees, Graphs to update to the demands from Industry.

CO4: Acquire skills on the creation of Binary Trees, Heaps and problem solving mind with Searching & Sorting techniques.

Course Title: Implementing Data Structures using C++ (Practical)

Course Code: CSC 313

CO1: Facilitate in working with Data Structures concepts involving Stacks, Queues, and Linked Lists etc.

CO2: Ability to solve problems related to Trees, Graphs, Minimum Spanning trees and its applications.

Semester IV

Course Title: Database Management System (DBMS – Theory)

Course Code: CSC404

At the end of the course the student would be able to:

CO1: Define Database concepts & roles in Database Environment to develop Knowledge.

CO2: Acquire employable skills through SQL commands, PL/SQL programs to update to the demands from Industry.

CO3: Develop strong foundation on construction of E- R E- R & E-E-R diagrams for different types of relationships and contemporary knowledge on Normalisation forms.

CO4: Inculcate ability to understand Transaction Management & Security issues.

Course Title: SQL& PL/SQL (Practical)

Course Code: CSC414

CO1: Understand and appreciate different commands towards Structured Query language

CO2: Attain knowledge of basic programs on PL/SQL concepts such as Cursors, Exceptions, Procedures, Packages, and Functions.

Semester V

Course Title: Programming in Java (Theory)

Course Code: CSC505

At the end of the course, the student would be able to:

CO1: Define the concepts of OOPs and fundamentals of the Java programming language.

CO2: Demonstrate various programming constructs like control structures, constructors, inheritance, polymorphism, interfaces and packages.

CO3: Develop efficient and error-free programs by applying the concepts of Multithreading and Exception handling.

CO4: Acquire employability skills through hands-on coding and developing interactive programs using applets, swings and JDBC.

Course Title: Programming in Java (Practical)

Course Code: CSC515

CO1: Apply the concepts of java to develop efficient and error-free codes.

CO2: Develop programs for solving real-world problems using swings.

Course Title: Operating Systems (Theory)

Course Code: CSC506

At the end of the course the student would be able to:

CO1: Gain understanding of the relevance, importance of Operating Systems and the various features and functions of Operating Systems.

CO2: Acquire knowledge about Process Management, Synchronization and CPU Scheduling. Demonstrate the various Scheduling Algorithms using C language and a comparative study.

CO3:Acquire knowledge relating to Deadlocks, various deadlock handling methods, Memory Management techniques and File systems.

CO4: Application as Case Study of the various features of any particular Operating System.

Course Title: Unix Programming (Practical)

Course Code: CSC516

CO1: Gain Knowledge of UNIX Operating System and hands-on experience of UNIX commands and apply in creating/ writing shell scripts.

CO2: Implementing the various Scheduling Algorithms using C language.

Semester VI

Course Title: Computer Networks (Theory)

Course Code: CSC607

At the end of the course, the student would be able to:

CO1: Understand and recognize the various components that makeup a Computer Network.

CO2: Acquire the knowledge about the various concepts related to network protocols.

CO3: Discuss the functionality of different layers of ISO Model and TCP/IP layers.

CO4: Gain knowledge about algorithms used at various layers in networks.

Course Title: Computer Networks (Practical)

Course Code: CSC617

CO1: Gain working knowledge of socket programming

CO2: Implement client-server communication through TCP and UDP protocols

Course Title: Web Technologies (Theory)

Course Code: CSC608

At the end of the course, the student would be able to:

CO1: Gain knowledge and proficiency HTML/XHTML and be able to develop structure for web pages.

CO2: Gain proficiency in usage of style sheets in fine tuning structure and design.

CO3: Acquire knowledge and skills relating to JavaScript and apply this to create interactive web pages.

CO4: Acquire knowledge of various aspects and models of designing web pages, maintenance and apply the same in building websites.

Course Title: Web Technologies (Practical)

Course Code: CSC618

CO1: Create web pages using XHTML and Cascading Style Sheets.

CO2: Build dynamic web pages using JavaScript (Client side programming).

Data Science (MSDS)

Semester: I

Course Title: Fundamentals of Information Technology (Theory)

Course Code: DSC101

At the end of the course the student would be able to:

CO1: Explain the notion of problem-solving using computer programming

CO2: Remember and identify the components of a computer and their functions

CO3: Familiar with  the concepts of networking, LAN, Internet and working of www

CO4: Acquire the knowledge of Software Project and the Process of software development

Course Title: Fundamentals of Information Technology (Practical)

Course Code: DSC111

CO1: Understand the components of a Motherboard and allied parts of a System

CO2: Perform various tasks related to installing /uninstalling devices and programs

Semester: II

Course Title: Problem Solving and Python Programming (Theory)

Course Code: DSC202

At the end of the course the student would be able to:

CO1: Recognize how to read and write data from/to files in python programs

CO2: Acquire knowledge on various python concepts of data types, control statements, list, tuples, functions, strings and OOPS

CO3: Develop algorithmic solutions to simple computational problems

CO4: Develop simple Python programs for solving problems.

Course Title: Problem Solving and Python Programming (Practical)

Course Code: DSC212

CO1: Write Python programs using fundamental python concepts

CO2: Develop Programming solutions with appropriate data structures and logic

Semester: III

Course Title: Data Engineering with Python (Theory)

Course Code: DSC303

At the end of the course the student would be able to:

CO1: Acquire different types of files and work with text data

CO2: Implement regular expression operations in real time examples

CO3: Learn some of the relational databases concepts via SQL

CO4: Attain knowledge on tabular numeric data, data structures, data series & frames, and PyPlot for visualization

Course Title: Data Engineering with Python (Practical)

Course Code: DSC313

CO1: Write programs that can read and write to files and use various packages for visualization purposes

CO2: Create simple databases and perform different queries on them.

Semester IV

Course Title: Machine Learning (Theory)

Course Code: 404

At the end of the course the student would be able to:

CO1: Acquire basics of Machine Learning and its limitations

CO2: Implement the Machine Learning Algorithms- supervised, unsupervised, reinforcement into the real time problems.

CO3: Learn the Probabilistic Modelling and Association Rule Mining

CO4: Attain knowledge on linear modeling

Course Title: Machine Learning (Practical)

Course Code: 414

CO1: Implement Machine Learning Algorithms on datasets

CO2: Design appropriate Machine learning solutions for real world problems

Semester V

Course Title: Natural Language Processing

Course Code: DSC505

At the end of the course the student would be able to:

CO1: Acquire key concepts of NLP and linguistics to describe and analyze language

CO2: Understand the data structures and algorithms that are used in NLP

CO3: Classify texts using machine learning and deep learning

CO4: Build models to carry out Natural Language Processing techniques on various corpora

Course Code: DSC515

Course Title: Natural Language Processing Practical

CO1: Write programs that manipulate and analyze language data using Python

CO2: Perform high level tasks like sentiment analysis using NLP techniques

Course Title: Data Structures and Algorithms

Course Code: DSC506

At the end of the course the student would be able to:

CO1: Acquire strong foundation from fundamental concepts to analyze and design algorithms with various complexities

CO2: Inculcate a spirit of learning ability to understand and implement linear, non-linear data structures

CO3: Build capacities for professional development imbibing knowledge on various kinds of searching and sorting techniques.

CO4: Acquire employable skills through problem solving to update to the demands from Industry

Semester VI

Course Code: DSC607B

Course Title: Deep Learning

At the end of the course the student would be able to:

CO1: Understand the basics of deep learning

CO2: Gain familiarity with the usage of tensors in deep learning

CO3: Utilize Python deep-learning framework Keras, with Tensor-Flow as a backend engine

CO4: Develop multi layered neural networks to perform classification and prediction tasks

Course Code: DSC617B

Course Title: Deep Learning Practical

CO1: Develop deep learning models using Keras

CO2: Implement Deep neural networks based on CNN’s and RNN’s

Course Code: DSC608 / PRJT608

Course Title: Major Project ( Data Science)

On successful completion of the project, a student will be able to:

CO1: Demonstrate a sound technical knowledge of their selected project topic.

CO2: Design relevant Machine Learning/ Deep Learning based solution for respective problem domain

CO3: Acquire necessary datasets and Implement chosen models.

CO4: Demonstrate the knowledge, skills and attitudes of a Data Science Professional