Master of Computer Applications (MCA)
A comprehensive program designed to provide a strong foundation in computer applications with a focus on practical, work-linked experience.
About the Program
The MCA Work-Linked Program (WLP) is an advanced postgraduate degree that combines rigorous academic coursework with practical industry experience. This program is designed for students seeking to build a robust career in the IT sector, equipping them with the skills needed to excel in roles like software development, system analysis, and data management.
Key Information
Program Objectives
To provide a comprehensive understanding of modern programming languages and software development methodologies.
To equip students with skills in database management, computer networks, and operating systems.
To offer specialized knowledge in emerging areas like Artificial Intelligence, Machine Learning, and Big Data.
To bridge the gap between academia and industry through project-based learning and practical labs.
Career Prospects
Software Developer
System Analyst
Data Scientist
Machine Learning Engineer
Database Administrator
Web Developer
IT Consultant
Program Structure
Semester I
Object Oriented Programming Using Java
Data Structures and Algorithms
Operating Systems using Linux
Computer Networks
Mathematical Foundation for Computer Applications
Computer Architecture
Object –Oriented Programming using Java Lab
Data Structures and Algorithms Lab
Operating Systems and Computer Networks Lab
Semester II
Project - I
Database Management Systems
Software Engineering
Web Technology
Artificial Intelligence
Introduction to Big Data
Database Management Systems Lab
Software Engineering Lab
Web Technology Lab
Semester III
NO SQL databases
Python Programming
Machine Learning
Data Warehousing and Data Mining
Introduction to IOT / Service Oriented Architecture /Advanced Computer Architecture
Organizational Behaviour/ Psychology and Life Skills
NO SQL databases Lab
Python Programming Lab
Machine Learning Lab
Semester IV
Software Testing / Introduction to Data Science/Agile Methodology
Research Methodology
Project - II