Master of Computer Applications
with Curriculum Aligned to NVIDIA Deep Learning Institute (DLI)
Duration2 Years
Master of Computer Applications is a two-year post-graduate programme with curriculum primarily based on the development of application software in diverse areas.
The programme provides the latest elective courses and with emphasis on project work. The programme is inclined towards application development and lays emphasis on the latest programming languages like Python etc. This programme equips students with the knowledge of the development of application software for diverse fields to solve specific problems for the end users or clients. In addition, the programme also emphasizes upon planning, designing, and building of complex commercial application software and system software.
Program Specific Outcomes (PSO)
PSO 01
To develop the technological planning and development of software applications in the usage of the modern era.
PSO 02
To demonstrate the ability to simulate, analyse, design, and deploy the software systems in advanced level for the industry and adcademic research.
Programme Outcomes (PO)
To apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
To identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
o design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
To 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.
To create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
To apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
To understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
To apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
To function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
To communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
To demonstrate knowledge and understanding of the engineering 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.
To recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Curriculum Details
| S.No. | Course Code | Course Name | L | T | P | C | |
|---|---|---|---|---|---|---|---|
| 1 | CAP1005/CAP1005L | Programming and Problem Solving using C | 3 | 0 | 2 | 4 | SEC |
| 2 | CAP4103/CAP4103L | Data Structures and Applications | 3 | 0 | 2 | 4 | DSC |
| 3 | CAP4708 | Computer Organization and Architecture | 3 | 0 | 0 | 3 | DSC |
| 4 | CAP4102/CAP4102L | Advanced Database Management Systems / Advanced Database Management Systems Lab | 3 | 0 | 2 | 4 | DSC |
| 5 | CAP4008/CAP4008L | Software Engineering / Software Engineering Lab | 3 | 0 | 2 | 4 | SEC |
| Total Credits | 19 | ||||||
| S.No. | Course Code | Course Name | L | T | P | C | |
|---|---|---|---|---|---|---|---|
| 1 | MAT2003/MAT2003L | Probability and Statistics using Python | 3 | 0 | 2 | 4 | DSC |
| 2 | CAP4005/CAP4005L | Computer Networks and Security Essentials | 3 | 0 | 2 | 4 | DSC |
| 3 | CAP3004 | Artificial Intelligence | 3 | 0 | 0 | 3 | DSC |
| 4 | CAP4009/CAP4009L | Java Programming | 3 | 0 | 2 | 4 | SEC |
| 5 | GMT2761 | Principles of Management | 2 | 0 | 0 | 2 | AEC |
| 6 | CAP2016/CAP2016L | Full Stack Development | 3 | 0 | 2 | 4 | SEC |
| Total Credits | 21 | ||||||
| S.No. | Course Code | Course Name | L | T | P | C | |
|---|---|---|---|---|---|---|---|
| 1 | CAP5006 / CAP5006L | Operating System | 3 | 0 | 2 | 4 | DSC |
| 2 | CAP5707 | Data warehousing and Data Mining | 3 | 0 | 0 | 3 | DSC |
| 3 | CAP5007 / CAP5007L | Cloud Computing | 3 | 0 | 2 | 4 | DSC |
| 4 | Departmental elective - 1 | 3 | 0 | 0 | 3 | MIC | |
| 5 | Departmental elective - 2 | 3 | 0 | 0 | 3 | MIC | |
| 6 | CAP4013 / CAP4013L | Machine Learning using Python | 3 | 0 | 2 | 4 | SEC |
| 7 | CAP4601 | Minor Project | 5 | MDC | |||
| Total Credits | 26 | ||||||
| Course Code | Course Title | L | T | P | Credits | |
|---|---|---|---|---|---|---|
| CAP4502 | Major Project | 0 | 0 | 0 | 18 | MIC |
| Total Credits | 18 | |||||
| S.No. | Course Code | Course Name | L | T | P | C |
|---|---|---|---|---|---|---|
| 1 | CAP4707 | Introduction to Social Network Analysis | 3 | 0 | 0 | 3 |
| 2 | CSE2721 | Image Processing | 3 | 0 | 0 | 3 |
| 3 | CAP4704 | Big Data Technologies | 3 | 0 | 0 | 3 |
| 4 | CAP5706 | Artificial Neural Networks and Deep Learning | 3 | 0 | 0 | 3 |
| 5 | CAP5705 | Cryptography and Network Security | 3 | 0 | 0 | 3 |
| 6 | CSE3803 | Introduction to Data Science | 3 | 0 | 0 | 3 |
| 7 | CSE3704 | Software Testing Methodologies | 3 | 0 | 0 | 3 |
| 8 | CAP4705 | E-Commerce | 3 | 0 | 0 | 3 |
Career Path

- Database Administrator
- System Administrator
- Programmer
- Full Stack Developer
- Software Developer/Tester
- Data Analys
- Researcher
- Product manager.
Fee Structure
Yearly
| 1st Year | 2nd Year |
|---|---|
| ₹1,65,000 | ₹1,35,000 |
Semester Wise
| 1st Sem | 2nd Sem | 3rd Sem | 4th Sem |
|---|---|---|---|
| ₹97,500 | ₹67,500 | ₹67,500 | ₹67,500 |
Admission Process
Complete the Application
Appear for Entrance test and interview
Get shortlisted and Received the offer letter
Master of Computer Applications
Passed BCA/ Bachelor Degree in Computer Science Engineering or equivalent Degree. OR Passed B.Sc./ B.Com./ B.A. with Mathematics at 10+2 Level or at Graduation Level (with additional bridge Courses as per the norms of the University). Obtained at least 50% marks in the qualifying examination.