Computer Organization and Architecture

1. Basics of computer organization and architecture

   • Memory hierarchy

   • CPU organization

   • Input-output organization

Object-Oriented Programming and C++

• Object-oriented programming principles

• Classes and objects

• Inheritance and polymorphism

• Exception handling

Programming in C

• Fundamentals of C programming

• Control structures

• Functions and recursion

• Arrays and pointers

Data Communication and Networking

• Introduction to networking concepts

• Network protocols and architecture

• TCP/IP and OSI models

• Network security

Data Structures

• Introduction to data structures

• Arrays, linked lists, and stacks

• Queues and trees

• Searching and sorting algorithms

Database Management Systems

• Database concepts

• Relational database management systems

• SQL and query optimization

• Normalization and transactions

Computer and ‘C’ Programming Lab

• Practical exercises related to programming in C

• Implementing data structures in C

Data Structures Lab

• Practical exercises related to data structures and algorithms

Operating Systems

• Introduction to operating systems

• Process management

• Memory management

• File systems

Software Engineering

• Software development life cycle

• Requirement analysis and specification

• Software design and testing

• Software maintenance and quality assurance

Java Programming

• Introduction to Java

• Java fundamentals

• GUI programming with Swing

• Multithreading and exception handling

Mobile App Development

• Mobile app development platforms (e.g., Android, iOS)

• App development using IDEs (e.g., Android Studio, Xcode)

• Mobile app design principles

Web Technologies

• HTML, CSS, and JavaScript

• Server-side scripting (e.g., PHP)

• Web development frameworks (e.g., ASP.NET, JSP)

Computer Graphics

• Fundamentals of computer graphics

• 2D and 3D graphics programming

• Rendering techniques

• Animation

Operating Systems Lab

• Practical exercises related to operating systems

Software Engineering Lab

• Practical exercises related to software engineering principles

Data Analytics and Business Intelligence

• Data analytics tools and techniques

• Data visualization

• Business intelligence concepts

• Data mining and predictive modeling

Project Work

• Students typically undertake a substantial software project under the guidance of faculty.

Artificial Intelligence and Machine Learning

• Introduction to AI and ML

• Machine learning algorithms

• Neural networks and deep learning

• AI applications

Seminar and Presentation

• Presentation of project work and related topics

Cloud Computing

• Cloud computing models (IaaS, PaaS, SaaS)

• Cloud service providers (e.g., AWS, Azure)

• Virtualization and containerization

Viva Voce

• Oral examination related to the project and coursework.