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Fees
₹4,50,000
Placement
92.0%
Avg Package
₹5,00,000
Highest Package
₹8,00,000
Fees
₹4,50,000
Placement
92.0%
Avg Package
₹5,00,000
Highest Package
₹8,00,000
Seats
200
Students
200
Seats
200
Students
200
The Computer Applications program at Rungta International Skills University Durg is structured to provide a comprehensive and progressive educational experience. The curriculum is designed to balance theoretical knowledge with practical application, ensuring students are well-prepared for the demands of the modern technology industry. The program spans eight semesters, with each semester carefully planned to build upon the previous one, culminating in a capstone project that integrates all learned concepts.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | CS101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | CS102 | Physics for Computer Applications | 3-1-0-4 | - |
| 1 | CS103 | Introduction to Programming | 3-1-0-4 | - |
| 1 | CS104 | Computer Fundamentals | 3-1-0-4 | - |
| 1 | CS105 | English for Technical Communication | 3-1-0-4 | - |
| 1 | CS106 | Workshop in Programming | 0-0-2-2 | - |
| 2 | CS201 | Engineering Mathematics II | 3-1-0-4 | CS101 |
| 2 | CS202 | Electrical and Electronics Engineering | 3-1-0-4 | - |
| 2 | CS203 | Data Structures and Algorithms | 3-1-0-4 | CS103 |
| 2 | CS204 | Object-Oriented Programming | 3-1-0-4 | CS103 |
| 2 | CS205 | Database Management Systems | 3-1-0-4 | CS103 |
| 2 | CS206 | Computer Organization and Architecture | 3-1-0-4 | CS104 |
| 2 | CS207 | Lab: Programming and Data Structures | 0-0-3-2 | CS103, CS203 |
| 3 | CS301 | Operating Systems | 3-1-0-4 | CS206 |
| 3 | CS302 | Software Engineering | 3-1-0-4 | CS204 |
| 3 | CS303 | Computer Networks | 3-1-0-4 | CS206 |
| 3 | CS304 | Web Technologies | 3-1-0-4 | CS204 |
| 3 | CS305 | Probability and Statistics | 3-1-0-4 | CS101 |
| 3 | CS306 | Lab: Software Engineering and Web Development | 0-0-3-2 | CS204, CS302 |
| 4 | CS401 | Artificial Intelligence | 3-1-0-4 | CS305 |
| 4 | CS402 | Cybersecurity | 3-1-0-4 | CS303 |
| 4 | CS403 | Data Science | 3-1-0-4 | CS305 |
| 4 | CS404 | Mobile Application Development | 3-1-0-4 | CS204 |
| 4 | CS405 | Cloud Computing | 3-1-0-4 | CS303 |
| 4 | CS406 | Lab: Advanced Topics in Computer Applications | 0-0-3-2 | CS302, CS303 |
| 5 | CS501 | Machine Learning | 3-1-0-4 | CS401 |
| 5 | CS502 | Big Data Analytics | 3-1-0-4 | CS403 |
| 5 | CS503 | Internet of Things | 3-1-0-4 | CS303 |
| 5 | CS504 | Blockchain Technology | 3-1-0-4 | CS402 |
| 5 | CS505 | Human-Computer Interaction | 3-1-0-4 | CS304 |
| 5 | CS506 | Lab: Specialized Topics in Computer Applications | 0-0-3-2 | CS401, CS403 |
| 6 | CS601 | Advanced Software Engineering | 3-1-0-4 | CS302 |
| 6 | CS602 | Research Methodology | 3-1-0-4 | - |
| 6 | CS603 | Capstone Project I | 3-1-0-4 | CS501 |
| 6 | CS604 | Project Management | 3-1-0-4 | - |
| 6 | CS605 | Internship Preparation | 3-1-0-4 | - |
| 6 | CS606 | Lab: Capstone Project | 0-0-3-2 | CS603 |
| 7 | CS701 | Capstone Project II | 3-1-0-4 | CS603 |
| 7 | CS702 | Research in Computer Applications | 3-1-0-4 | CS602 |
| 7 | CS703 | Entrepreneurship and Innovation | 3-1-0-4 | - |
| 7 | CS704 | Industry Collaboration Project | 3-1-0-4 | CS603 |
| 7 | CS705 | Professional Ethics and Social Responsibility | 3-1-0-4 | - |
| 7 | CS706 | Lab: Final Project | 0-0-3-2 | CS701 |
| 8 | CS801 | Final Project Presentation | 3-1-0-4 | CS701 |
| 8 | CS802 | Internship | 3-1-0-4 | - |
| 8 | CS803 | Graduation Thesis | 3-1-0-4 | CS702 |
| 8 | CS804 | Industry Review | 3-1-0-4 | - |
| 8 | CS805 | Professional Development | 3-1-0-4 | - |
| 8 | CS806 | Lab: Thesis and Internship | 0-0-3-2 | CS803 |
Advanced departmental elective courses are designed to provide students with specialized knowledge and skills in emerging areas of computer applications. These courses are offered in the later semesters and are tailored to meet the evolving demands of the industry.
The Machine Learning course delves into advanced algorithms and techniques for building intelligent systems. Students study supervised and unsupervised learning, neural networks, deep learning architectures, and reinforcement learning. The course emphasizes practical implementation using frameworks like TensorFlow and PyTorch. Through hands-on projects, students gain experience in developing and deploying machine learning models for real-world applications.
This course explores the tools and techniques for processing and analyzing large datasets. Students learn about distributed computing frameworks like Hadoop and Spark, data visualization tools, and statistical methods for big data analysis. The course includes practical sessions on data mining, clustering, classification, and regression techniques. Students work on projects involving real-world datasets to gain experience in big data processing and analysis.
The Internet of Things (IoT) course covers the design and implementation of connected systems. Students study sensor networks, embedded systems, wireless communication protocols, and cloud integration. The course includes hands-on labs on IoT development using platforms like Arduino and Raspberry Pi. Students develop projects involving smart home systems, industrial automation, and environmental monitoring.
This course introduces students to blockchain fundamentals and applications. Students study cryptographic principles, consensus mechanisms, smart contracts, and decentralized applications. The course covers practical aspects of blockchain development using platforms like Ethereum and Hyperledger. Students work on projects involving cryptocurrency systems, supply chain tracking, and digital identity management.
The Human-Computer Interaction course focuses on designing user-friendly interfaces and systems. Students study user-centered design principles, usability testing, and interaction design. The course includes practical sessions on prototyping tools like Figma and Sketch. Students work on projects involving user research, interface design, and accessibility improvements.
This course covers advanced topics in software development and management. Students study software architecture, agile methodologies, testing frameworks, and DevOps practices. The course emphasizes practical implementation through team projects and industry collaboration. Students gain experience in software project management and quality assurance.
The Research Methodology course provides students with the skills needed for conducting academic research. Students study research design, data collection, analysis techniques, and academic writing. The course includes practical sessions on literature review, hypothesis testing, and research proposal development. Students work on individual research projects and present their findings.
The Capstone Project I course introduces students to the process of developing a comprehensive project. Students select a topic, conduct research, and develop a project plan. The course emphasizes project management and collaboration skills. Students work in teams to develop a prototype and present their project to faculty and industry experts.
The Capstone Project II course involves the development and implementation of the project started in Capstone Project I. Students refine their project, conduct testing, and prepare for presentation. The course includes guidance on project documentation, presentation skills, and industry feedback. Students present their final project to a panel of experts and receive feedback for future development.
This course focuses on developing entrepreneurial skills and innovation capabilities. Students study business model development, innovation management, and startup creation. The course includes practical sessions on ideation, prototyping, and pitching. Students work on developing business plans and presenting their ideas to potential investors.
The department's philosophy on project-based learning is rooted in the belief that hands-on experience is essential for developing technical and professional skills. The curriculum integrates project-based learning throughout all semesters, with each project building upon the previous one to create a comprehensive learning experience.
Mini-projects are introduced in the early semesters to help students apply theoretical concepts in practical scenarios. These projects are typically completed within a semester and focus on specific topics or skills. Students work in small teams and receive guidance from faculty mentors. The projects are evaluated based on technical execution, creativity, and presentation skills.
The final-year thesis or capstone project is a comprehensive endeavor that integrates all learned concepts and skills. Students select a topic of interest and work under the supervision of a faculty mentor. The project involves extensive research, development, and testing. Students present their work to a panel of experts and receive feedback for future development. The project is a significant component of the program's assessment and provides students with valuable experience in independent research and development.
Students are encouraged to select projects that align with their interests and career goals. The department provides a list of project topics and faculty mentors for guidance. Students can also propose their own project ideas, subject to approval by faculty advisors. The mentorship system ensures that students receive support throughout their project journey, from initial planning to final presentation.
