- Faculty
Faculty of Engineering and Technology
- Campus
Technology Campus (Peenya Campus)
- Engagement Mode
Full Time
Overview
The 2-year Master of Computer Applications (MCA) degree is in demand because it provides advanced, industry-relevant knowledge in areas like software development, data science, artificial intelligence, machine learning and cybersecurity, equipping graduates with specialized skills for high-paying roles in the tech sector. This shorter, intensive program allows students with foundational computer science knowledge to quickly upskill and pursue advanced career opportunities. Additionally, the MCA degree is recognized by employers across industries, as companies increasingly need skilled professionals to drive digital transformation and innovation. It offers the NEP-2020 aligned curriculum with focus on Industry 4.0. The program is approved by the All India Council for Technical Education (AICTE), New Delhi.
Program Objectives
- - A renowned establishment with a 62-year history
- - Accredited with NAAC A+ and ranked by NIRF
- - State-of-the-art computing facilities
- - Opportunity to upskill by the exclusive Ramaiah Skill Academy.
- - Opportunity for placements with higher package in the IT industry.
Curriculum Details
2025-26
| Sl. No. | Course Type | Course Name | Theory | Tutorials | Practical | Max Marks | Total Credits |
|---|---|---|---|---|---|---|---|
| 1 | PCC | Mathematical Foundation for Computer Applications | 3 | 1 | 0 | 100 | 4 |
| 2 | PCC | Operating Systems | 3 | 0 | 2 | 100 | 4 |
| 3 | PCC | Data Structures with Algorithms | 4 | 0 | 0 | 100 | 4 |
| 4 | PCC | Computer Networks | 3 | 0 | 0 | 100 | 3 |
| 5 | PCC | Design and Analysis of Algorithms | 3 | 1 | 0 | 100 | 4 |
| 6 | PCC | Data Structures Laboratory | 0 | 0 | 4 | 100 | 2 |
| 7 | PCC | Computer Networks Laboratory | 0 | 0 | 4 | 100 | 2 |
| 8 | PCC | Research Methodology and IPR | 2 | 0 | 0 | 100 | 2 |
| 9 | PCC | Programming in C & Computer Organisation | 2 | 2 | 0 | 100 | 0 |
| Total | 20 | 4 | 10 | 900 | 25 | ||
| Total number of contact hours per week: 34 | |||||||
| Sl. No. | Course Type | Course Name | Theory | Tutorials | Practical | Max Marks | Total Credits |
|---|---|---|---|---|---|---|---|
| 1 | PCC | Database Management System | 3 | 0 | 0 | 100 | 3 |
| 2 | PCC | Object Oriented Programming Using Java | 3 | 0 | 0 | 100 | 3 |
| 3 | PCC | Software Engineering | 4 | 0 | 0 | 100 | 4 |
| 4 | SEC | Full Stack Development | 3 | 0 | 2 | 100 | 4 |
| 5 | SEC | Artificial Intelligence and Machine Learning | 4 | 0 | 0 | 100 | 4 |
| 6 | PEC | Professional Elective-1: Distributed Computing / Cloud Computing | 4 | 0 | 0 | 100 | 4 |
| 7 | PCC | DBMS Laboratory | 0 | 0 | 4 | 100 | 2 |
| 8 | PCC | Java Programming Laboratory | 0 | 0 | 4 | 100 | 2 |
| 9 | PCC | Internship | 0 | 0 | 12 | 100 | 6 |
| Total | 21 | 0 | 22 | 900 | 32 | ||
| Total number of contact hours per week: 44 | |||||||
| Sl. No. | Course Type | Course Name | Theory | Tutorials | Practical | Max Marks | Total Credits |
|---|---|---|---|---|---|---|---|
| 1 | SEC | Data Analytics with Python | 3 | 0 | 0 | 100 | 3 |
| 2 | SEC | Internet of Things | 3 | 0 | 0 | 100 | 3 |
| 3 | PEC | Professional Elective-2: Deep Learning / Natural Language Processing | 4 | 0 | 0 | 100 | 4 |
| 4 | PEC | Professional Elective-3: Blockchain Technology / AI for Healthcare | 4 | 0 | 0 | 100 | 4 |
| 5 | SEC | User Interface Design | 4 | 0 | 0 | 100 | 4 |
| 6 | SEC | Cyber Security | 3 | 0 | 2 | 100 | 4 |
| 7 | SEC | Data Analytics Lab | 0 | 0 | 4 | 100 | 2 |
| 8 | SEC | IoT Laboratory | 0 | 0 | 4 | 100 | 2 |
| 9 | PCC | Project Work - Phase 1 | 0 | 0 | 4 | 100 | 2 |
| Total | 21 | 0 | 14 | 1000 | 28 | ||
| Total number of contact hours per week: 35 | |||||||
| Sl. No. | Course Type | Course Name | Theory | Tutorials | Practical | Max Marks | Total Credits |
|---|---|---|---|---|---|---|---|
| 1 | PCC | Project Work - Phase 2 | 0 | 0 | 40 | 200 | 20 |
| Total number of contact hours per week: 40 | |||||||
| Sl. No. | Course Name |
|---|---|
| 1 | Distributed Computing |
| 2 | Cloud Computing |
| 3 | Deep Learning |
| 4 | Natural Language Processing |
| 5 | Blockchain Technology |
| 6 | AI for Healthcare |
Eligibility Criteria
Graduates with a bachelor's degree from an recognized institution in any BCA/ Bachelor Degree in Computer Science or Engineering or equivalent degree or B.Sc/B Com/BA with Mathematics at 10+2 level or at Graduation level (with additional bridge courses as per the norms of concerned University and a minimum aggregate score of 50%.
Admission selection process for will be based on RUAS AT scores, and CUET-PG/KMAT/PGCET scores are also accepted and RUAS AT will be exempted for these candidates.
Career Path
- The two years MCA program is well-accepted and recognized by the industry for its various roles like Software Developer, Data Scientist, Machine Learning (ML) Specialist, Artificial Intelligence (AI) Engineer, Cloud Architect, Web Developer, Software Engineer, Business Analyst, Network Engineer, Quality Assurance Professional, Application Developer, Cyber Security Analyst and Test Engineer.
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