Department of Master of Computer Applications
Overview
MCA Department is started during the academic year 1993-94 with the intake of 30 Students and affiliated by Madurai Kamaraj University and approved by AICTE, New Delhi. Now the Intake is 60 students and affiliated by Anna University, Chennai. In Our Department we are having experienced faculties with different specialization, and well equipped Laboratories with latest computer systems. We are maintaining Cent percentage of results constantly.
We motivate Staff and Students to promote Industry Institute Interaction and R&D activities. In addition to regular curriculum the department organizes technical seminars, symposia, workshops, industrial visits, in-plant training to expose the students to the real world environments and to enable them to gain practical knowledge. The department has excellent modern (Advanced) computing facilities with latest Software and Hardware. The students of this department are highly placed in the industrial segments and in trade / commercial / corporate organizations while many of them pursue higher education in India and overseas.
Programme
Duration:
2 years (Regular)
No. of Semesters:
4 (Regular)
Intake / No. of Seats:
Total - 60 (Government - 18, Management - 42)
Eligibility:
A pass in a recognized Bachelor’s degree of minimum 3 years duration with mathematics at 10+2 level or at Graduate level and obtained atleast 50 % in the qualifying degree examination.
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VISION
The Department of Master of Computer Applications strives to groom students with diverse backgrounds into competitive software professionals and pioneering leaders in offering innovative solutions to dynamic global challenges in tune with the needs of the society
MISSION
i. To offer high-grade, value-based Post-graduate programmes in the field of Computer Applications.
ii. To impart value-added technical education to the students and enrich their knowledge.
iii. To endeavour for continuous upgradation of technical expertise of students.
iv. Develop intellectual curiosity and a commitment to lifelong learning in students, with societal and environmental concerns
Programme Educational Objectives (PEOs)
| PEO1. | Apply their computing skills to analyse, design and develop innovative software products to meet the industry needs and excel as software professionals. |
| PEO2. | Pursue lifelong learning and do research in the computing field based on solid technical foundations to contribute technical solutions for the sustainable development of society. |
| PEO3. | Communicate and function effectively in teams in multidisciplinary fields within the global, societal and environmental context. |
| PEO4. | Exhibit professional integrity, ethics and an understanding of responsibility. |
Program Specific Outcomes (PSOs)
| PSO1. | Understand and apply the computing techniques with mathematics and industrial concepts for solving the problems. |
| PSO2. | Analyze, design, develop, test and maintain the software applications with latest computing tools and technologies. |
| PSO3. | Enable the students to select the suitable data model, appropriate architecture and platform to implement a system with good performance for real time environments. |
Programme Outcomes (PO)
| PO1. | Computational Knowledge: | Apply knowledge of computing fundamentals, computing specialisation, mathematics, and domain knowledge appropriate for the computing specialisation to the abstraction and conceptualisation of computing models from defined problems and requirements. |
| PO2. | Problem analysis: | Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines. |
| PO3. | Design/development of solutions: | Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations. |
| PO4. | Conduct Investigations of Complex Computing Problems: | Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions. |
| PO5. | Modern tool usage: | Create, select, adapt and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations. |
| PO6. | Professional Ethics: | Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practice. |
| PO7. | Life-long Learning: | Recognise the need, and have the ability, to engage in independent learning for continual development as a computing professional. |
| PO8. | Project Management and Finance: | Demonstrate knowledge and understanding of the computing and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments. |
| PO9. | Communication Efficacy: | Communicate effectively with the computing community, and with society at large, about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions. |
| PO10. | Societal and Environmental Concern: | Understand and assess societal, environmental, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice. |
| PO11. | Individual and Team Work: | Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary environments. |
| PO12. | Innovation and Entrepreneurship: | Identify a timely opportunity and using innovation to pursue that opportunity to create value and wealth for the betterment of the individual and society at large. |
Department Facilities
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Description
No of Rooms
Total Area (m2)
Class Rooms I-MCA Class Room(LH-55)
II-MCA Class Room(LH-57)33*30 Sq.m
33*30 Sq.mFaculty Rooms HOD - 1
Faculty - 111*10 Sq.m
22.5*20 Sq.mDepartment Library 1 20*11 Sq.m Laboratories 1 32*28 Sq.m MCA Laboratory
LENOVA
DELL
ACER
No of Terminal : 13
No of Terminal : 14
No of Terminal : 4
PROCESSOR INTEL CORE I3 PROCESSOR INTEL CORE I5 PROCESSOR INTEL CORE I3 PROCESSOR SPEED 6.4 GHz PROCESSOR SPEED 3.10 GHz PROCESSOR SPEED 3.70 GHz RAM 8 GB RAM 4 GB RAM 4 GB HARD DISK 1 TB HARD DISK 500 GB HARD DISK 1 TB MOTHER BOARD INTEL MOTHER BOARD INTEL MOTHER BOARD INTEL
Faculty
| Name | Qualification | Designation | Date of Joining | Nature of Association (Regular / Contract / Adjunct) |
Mr. M. MOHAMED RAFI |
M.C.A.,(Ph.D) | Professor & Head | 01/02/1995 | Regular |
Mr. N. BALASUBRAMANIAN |
M.E.,(Ph.D) | Associate Professor | 25/06/2000 | Regular |
Dr. S. SAJITHABANU |
M.Tech., Ph.D., | Associate Professor | 21/06/2011 | Regular |
Mr. M. SABARI RAMACHANDRAN |
M.E., | Assistant Professor | 01/03/2010 | Regular |
Mr. G. BALAMURUGAN |
M.C.A | Assistant Professor | 20/06/2012 | Regular |
Mrs. S. SHANMUGA PRIYA |
M.C.A | Assistant Professor | 24/06/2024 | Regular |
Mrs. N. SRUTHILAYA |
M.C.A | Assistant Professor | 24/06/2024 | Regular |
Academics
| Subject Code | Subject Name | Lesson Plan | Question Bank | Lecture Notes | ICT Tools |
| Applied Probability and Statistics for Computer Science Engineers | |||||
| Research Methodology and IPR | |||||
| Advanced Data Structures and Algorithms | |||||
| Object Oriented Software Engineering | |||||
| Python Programming | |||||
| Fundamentals of Accounting | |||||
| Machine Learning | |||||
| Internet of Things | |||||
| Crypto currency and Block chain Technologies | |||||
| Data Mining and Data Warehousing Techniques | |||||
| Software Quality and Testing | |||||
| Environmental Sustainability |
Innovation in Teaching
| Subject Code | Subject Name | ITM Tool |
| Applied Probability and Statistics for Computer Science Engineers | ||
| Research Methodology and IPR | ||
| Advanced Data Structures and Algorithms | ||
| Object Oriented Software Engineering | ||
| Python Programming | ||
| Fundamentals of Accounting | ||
| Machine Learning | ||
| Internet of Things | ||
| Cryptocurrency and Blockchain Technologies | ||
| Data Mining and Data Warehousing Techniques | ||
| Software Quality and Testing | ||
| Environmental Sustainability |
infrastructures
