Curriculum Overview
The Computer Applications program at Reva University Bangalore is structured over 8 semesters, with a comprehensive blend of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is designed to provide students with a strong foundation in computer science principles while also allowing them to specialize in areas of interest. The program emphasizes practical application, research, and industry exposure through various learning experiences and collaborative projects.
Course Structure
The curriculum is organized into core courses, departmental electives, science electives, and laboratory sessions. Core courses provide foundational knowledge in mathematics, physics, and computer science. Departmental electives allow students to explore specialized areas of interest. Science electives offer exposure to related fields such as biology, chemistry, and physics. Laboratory sessions provide hands-on experience with tools and technologies used in the industry.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | CS101 | Introduction to Programming | 3-0-0-3 | None |
| 1 | CS102 | Mathematics for Computer Science | 3-0-0-3 | None |
| 1 | CS103 | Computer Organization | 3-0-0-3 | None |
| 1 | CS104 | Physics for Computer Science | 3-0-0-3 | None |
| 1 | CS105 | English for Communication | 3-0-0-3 | None |
| 1 | CS106 | Lab: Programming | 0-0-3-1 | None |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 2 | CS202 | Discrete Mathematics | 3-0-0-3 | CS102 |
| 2 | CS203 | Database Management Systems | 3-0-0-3 | CS101 |
| 2 | CS204 | Object-Oriented Programming | 3-0-0-3 | CS101 |
| 2 | CS205 | Statistics and Probability | 3-0-0-3 | CS102 |
| 2 | CS206 | Lab: Data Structures | 0-0-3-1 | CS101 |
| 3 | CS301 | Operating Systems | 3-0-0-3 | CS201 |
| 3 | CS302 | Computer Networks | 3-0-0-3 | CS201 |
| 3 | CS303 | Software Engineering | 3-0-0-3 | CS201 |
| 3 | CS304 | Web Technologies | 3-0-0-3 | CS201 |
| 3 | CS305 | Linear Algebra | 3-0-0-3 | CS102 |
| 3 | CS306 | Lab: Operating Systems | 0-0-3-1 | CS201 |
| 4 | CS401 | Artificial Intelligence | 3-0-0-3 | CS301 |
| 4 | CS402 | Cybersecurity | 3-0-0-3 | CS301 |
| 4 | CS403 | Data Science | 3-0-0-3 | CS301 |
| 4 | CS404 | Cloud Computing | 3-0-0-3 | CS301 |
| 4 | CS405 | Mobile Application Development | 3-0-0-3 | CS301 |
| 4 | CS406 | Lab: AI | 0-0-3-1 | CS301 |
| 5 | CS501 | Advanced Algorithms | 3-0-0-3 | CS301 |
| 5 | CS502 | Machine Learning | 3-0-0-3 | CS301 |
| 5 | CS503 | Big Data Analytics | 3-0-0-3 | CS301 |
| 5 | CS504 | Human-Computer Interaction | 3-0-0-3 | CS301 |
| 5 | CS505 | Internet of Things | 3-0-0-3 | CS301 |
| 5 | CS506 | Lab: Machine Learning | 0-0-3-1 | CS301 |
| 6 | CS601 | Research Methodology | 3-0-0-3 | CS501 |
| 6 | CS602 | Capstone Project | 3-0-0-3 | CS501 |
| 6 | CS603 | Special Topics in Computer Applications | 3-0-0-3 | CS501 |
| 6 | CS604 | Internship | 0-0-0-3 | CS501 |
| 6 | CS605 | Project Management | 3-0-0-3 | CS501 |
| 6 | CS606 | Lab: Capstone Project | 0-0-3-1 | CS501 |
| 7 | CS701 | Advanced Research Project | 3-0-0-3 | CS601 |
| 7 | CS702 | Thesis | 3-0-0-3 | CS601 |
| 7 | CS703 | Advanced Topics in Computer Applications | 3-0-0-3 | CS601 |
| 7 | CS704 | Industry Exposure | 0-0-0-3 | CS601 |
| 7 | CS705 | Entrepreneurship | 3-0-0-3 | CS601 |
| 7 | CS706 | Lab: Thesis | 0-0-3-1 | CS601 |
| 8 | CS801 | Final Project | 3-0-0-3 | CS701 |
| 8 | CS802 | Final Thesis | 3-0-0-3 | CS701 |
| 8 | CS803 | Industry Internship | 0-0-0-3 | CS701 |
| 8 | CS804 | Graduation Ceremony | 0-0-0-0 | CS701 |
| 8 | CS805 | Final Presentation | 0-0-0-3 | CS701 |
| 8 | CS806 | Lab: Final Project | 0-0-3-1 | CS701 |
Advanced Departmental Electives
Departmental electives provide students with opportunities to explore specialized areas of interest. These courses are designed to offer in-depth knowledge and practical skills in specific domains of computer applications. The following are some of the advanced departmental electives offered in the program:
Artificial Intelligence
This course covers advanced topics in machine learning, deep learning, and neural networks. Students learn to design and implement AI systems for real-world applications. The course includes hands-on projects involving image recognition, natural language processing, and robotics.
Cybersecurity
This course focuses on network security, cryptography, and ethical hacking. Students learn to identify and mitigate security threats in digital environments. The course includes practical labs and simulations of real-world cyber-attacks.
Data Science
This course emphasizes data analysis, visualization, and predictive modeling. Students learn to extract insights from large datasets using statistical methods and machine learning. The course includes projects involving big data technologies and data mining.
Cloud Computing
This course covers cloud architecture, virtualization, and containerization. Students learn to design and deploy scalable cloud applications. The course includes hands-on experience with major cloud platforms such as AWS, Azure, and Google Cloud.
Mobile Application Development
This course focuses on developing applications for iOS and Android platforms. Students learn mobile app design, development frameworks, and deployment strategies. The course includes practical projects involving app development and testing.
Human-Computer Interaction
This course explores how users interact with computing systems and how interfaces can be designed to improve usability and user experience. Students learn user research, interface design, and prototyping techniques. The course includes practical sessions with user testing tools and virtual reality systems.
Internet of Things (IoT)
This course focuses on the design and implementation of IoT systems that connect physical devices to the internet. Students study sensor networks, embedded systems, and real-time data processing. The course includes hands-on projects involving IoT hardware and software development.
Software Engineering
This course emphasizes software architecture, testing, and project management. Students learn to design and develop software systems using industry-standard tools and methodologies. The course includes collaborative projects that simulate real-world software development environments.
Database Systems
This course covers database design, management, and optimization. Students learn to design and implement database systems for various applications. The course includes hands-on projects involving database modeling and query optimization.
Network Security
This course focuses on network security protocols, threat detection, and security management. Students learn to design and implement secure network systems. The course includes practical labs and simulations of network security challenges.
Project-Based Learning
The Computer Applications program at Reva University Bangalore places a strong emphasis on project-based learning. This approach ensures that students gain practical experience and apply theoretical knowledge to real-world problems. The program includes mandatory mini-projects and a final-year thesis/capstone project.
Mini-Projects
Mini-projects are conducted throughout the program to provide students with hands-on experience. These projects are typically completed in teams and are designed to reinforce concepts learned in class. Students are evaluated based on their project presentation, documentation, and demonstration.
Final-Year Thesis/Capstone Project
The final-year thesis or capstone project is a significant component of the program. Students work under the guidance of faculty mentors to develop a comprehensive solution to a significant problem in the field of computer applications. The project is typically completed in collaboration with industry partners or research institutions. Students are evaluated based on their project proposal, progress reports, final presentation, and documentation.
Project Selection and Mentorship
Students are encouraged to select projects that align with their interests and career goals. The program provides a platform for students to explore various domains and find suitable mentors. Faculty mentors are selected based on their expertise and research experience. Students are also encouraged to collaborate with industry partners and research institutions to gain exposure to real-world challenges.