Curriculum Overview
The Computer Applications program at Ram Krishna Dharmarth Foundation Rkdf University Ranchi is designed to provide a comprehensive and progressive learning experience over four years. The curriculum is structured to ensure that students gain both theoretical knowledge and practical skills, preparing them for successful careers in the technology industry. The program is divided into eight semesters, with each semester consisting of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is continuously updated based on industry feedback and the latest advancements in technology.
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|---|
| 1 | 1 | CS101 | Introduction to Computer Science | 3-0-0-3 | - |
| 1 | 1 | CS102 | Programming in C | 3-0-0-3 | - |
| 1 | 1 | CS103 | Mathematics for Computer Science | 3-0-0-3 | - |
| 1 | 1 | CS104 | Physics for Computer Science | 3-0-0-3 | - |
| 1 | 1 | CS105 | English for Technical Communication | 3-0-0-3 | - |
| 1 | 1 | CS106 | Computer Lab I | 0-0-3-1 | - |
| 1 | 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS102 |
| 1 | 2 | CS202 | Object-Oriented Programming | 3-0-0-3 | CS102 |
| 1 | 2 | CS203 | Discrete Mathematics | 3-0-0-3 | CS103 |
| 1 | 2 | CS204 | Electronic Devices and Circuits | 3-0-0-3 | - |
| 1 | 2 | CS205 | Introduction to Electrical Engineering | 3-0-0-3 | - |
| 1 | 2 | CS206 | Computer Lab II | 0-0-3-1 | CS106 |
| 2 | 3 | CS301 | Database Management Systems | 3-0-0-3 | CS201 |
| 2 | 3 | CS302 | Operating Systems | 3-0-0-3 | CS202 |
| 2 | 3 | CS303 | Computer Networks | 3-0-0-3 | CS204 |
| 2 | 3 | CS304 | Software Engineering | 3-0-0-3 | CS202 |
| 2 | 3 | CS305 | Probability and Statistics | 3-0-0-3 | CS103 |
| 2 | 3 | CS306 | Computer Lab III | 0-0-3-1 | CS206 |
| 2 | 4 | CS401 | Web Technologies | 3-0-0-3 | CS301 |
| 2 | 4 | CS402 | Mobile Application Development | 3-0-0-3 | CS202 |
| 2 | 4 | CS403 | Artificial Intelligence | 3-0-0-3 | CS301 |
| 2 | 4 | CS404 | Cybersecurity | 3-0-0-3 | CS303 |
| 2 | 4 | CS405 | Project Management | 3-0-0-3 | CS304 |
| 2 | 4 | CS406 | Computer Lab IV | 0-0-3-1 | CS306 |
| 3 | 5 | CS501 | Machine Learning | 3-0-0-3 | CS301 |
| 3 | 5 | CS502 | Deep Learning | 3-0-0-3 | CS501 |
| 3 | 5 | CS503 | Data Mining | 3-0-0-3 | CS305 |
| 3 | 5 | CS504 | Cloud Computing | 3-0-0-3 | CS303 |
| 3 | 5 | CS505 | Human-Computer Interaction | 3-0-0-3 | CS304 |
| 3 | 5 | CS506 | Computer Lab V | 0-0-3-1 | CS406 |
| 3 | 6 | CS601 | Advanced Database Systems | 3-0-0-3 | CS301 |
| 3 | 6 | CS602 | Network Security | 3-0-0-3 | CS303 |
| 3 | 6 | CS603 | Software Testing | 3-0-0-3 | CS304 |
| 3 | 6 | CS604 | Information Retrieval | 3-0-0-3 | CS301 |
| 3 | 6 | CS605 | Mobile Security | 3-0-0-3 | CS402 |
| 3 | 6 | CS606 | Computer Lab VI | 0-0-3-1 | CS506 |
| 4 | 7 | CS701 | Capstone Project I | 3-0-0-3 | CS501 |
| 4 | 7 | CS702 | Capstone Project II | 3-0-0-3 | CS701 |
| 4 | 7 | CS703 | Research Methodology | 3-0-0-3 | - |
| 4 | 7 | CS704 | Industrial Training | 0-0-0-3 | - |
| 4 | 7 | CS705 | Project Management | 3-0-0-3 | CS304 |
| 4 | 7 | CS706 | Computer Lab VII | 0-0-3-1 | CS606 |
| 4 | 8 | CS801 | Final Year Thesis | 3-0-0-3 | CS702 |
| 4 | 8 | CS802 | Advanced Topics in Computer Applications | 3-0-0-3 | CS701 |
| 4 | 8 | CS803 | Entrepreneurship | 3-0-0-3 | - |
| 4 | 8 | CS804 | Internship | 0-0-0-3 | - |
| 4 | 8 | CS805 | Capstone Project III | 3-0-0-3 | CS801 |
| 4 | 8 | CS806 | Computer Lab VIII | 0-0-3-1 | CS706 |
Advanced Departmental Electives
The Computer Applications program offers a range of advanced departmental elective courses that allow students to specialize in specific areas of interest. These courses are designed to provide in-depth knowledge and practical skills in emerging technologies and applications.
Machine Learning: This course provides a comprehensive introduction to machine learning algorithms and their applications. Students learn about supervised and unsupervised learning, neural networks, deep learning, and reinforcement learning. The course includes hands-on projects using popular machine learning frameworks such as TensorFlow and PyTorch. Students are exposed to real-world datasets and learn how to build and evaluate machine learning models. The course also covers ethical considerations in machine learning and its impact on society.
Deep Learning: This course focuses on advanced neural network architectures and their applications in computer vision, natural language processing, and speech recognition. Students learn about convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. The course includes practical sessions on building and training deep learning models using frameworks such as Keras and PyTorch. Students are also exposed to cutting-edge research in deep learning and are encouraged to contribute to ongoing research projects.
Data Mining: This course covers the techniques and tools used in data mining and knowledge discovery. Students learn about data preprocessing, clustering, classification, association rules, and anomaly detection. The course includes hands-on projects using data mining tools such as Weka and RapidMiner. Students are exposed to real-world datasets and learn how to extract meaningful patterns and insights from large datasets. The course also covers ethical considerations in data mining and its impact on privacy.
Cloud Computing: This course provides a comprehensive overview of cloud computing technologies and services. Students learn about virtualization, distributed systems, and cloud infrastructure. The course includes hands-on sessions on deploying applications on cloud platforms such as AWS, Azure, and Google Cloud. Students are exposed to cloud security and governance and learn how to design and implement scalable cloud solutions. The course also covers emerging trends in cloud computing such as edge computing and serverless architectures.
Human-Computer Interaction: This course focuses on the design and evaluation of user interfaces and user experiences. Students learn about user research, usability testing, interaction design, and accessibility. The course includes hands-on projects involving user-centered design and prototyping. Students are exposed to tools and techniques for evaluating user interfaces and are encouraged to conduct user studies. The course also covers emerging trends in human-computer interaction such as virtual reality, augmented reality, and wearable computing.
Network Security: This course provides a comprehensive introduction to network security principles and practices. Students learn about encryption, network protocols, firewalls, intrusion detection systems, and risk management. The course includes hands-on sessions on securing networks and identifying vulnerabilities. Students are exposed to real-world security challenges and learn how to design and implement secure network solutions. The course also covers emerging trends in network security such as zero-trust architecture and security automation.
Software Testing: This course covers the principles and practices of software testing and quality assurance. Students learn about testing methodologies, test design, automation tools, and defect tracking. The course includes hands-on sessions on testing software applications and identifying bugs and issues. Students are exposed to industry-standard testing frameworks and tools such as Selenium and JUnit. The course also covers advanced topics such as test-driven development and continuous integration.
Information Retrieval: This course focuses on the techniques and algorithms used in information retrieval and search engines. Students learn about indexing, ranking, query processing, and relevance feedback. The course includes hands-on projects involving search engine development and evaluation. Students are exposed to real-world search engines and learn how to improve search results and user experience. The course also covers emerging trends in information retrieval such as semantic search and voice search.
Mobile Security: This course provides a comprehensive overview of mobile security threats and countermeasures. Students learn about mobile platforms, security vulnerabilities, and secure coding practices. The course includes hands-on sessions on securing mobile applications and identifying security issues. Students are exposed to real-world mobile security challenges and learn how to design and implement secure mobile solutions. The course also covers emerging trends in mobile security such as mobile device management and secure multi-factor authentication.
Advanced Database Systems: This course covers advanced topics in database design and management. Students learn about database normalization, transaction processing, indexing, and query optimization. The course includes hands-on sessions on database design and implementation using SQL and NoSQL databases. Students are exposed to real-world database challenges and learn how to design and manage scalable database systems. The course also covers emerging trends in database systems such as distributed databases and in-memory databases.
Project-Based Learning Philosophy
The Computer Applications program at Ram Krishna Dharmarth Foundation Rkdf University Ranchi places a strong emphasis on project-based learning as a core component of the educational experience. This approach is designed to bridge the gap between theoretical knowledge and practical application, ensuring that students are not only well-versed in concepts but also capable of solving real-world problems.
The program incorporates project-based learning at multiple levels, starting from the early semesters with mini-projects and culminating in a comprehensive final-year thesis or capstone project. The mini-projects are designed to be collaborative, allowing students to work in teams and develop their communication and teamwork skills. These projects are typically assigned at the end of each semester and are evaluated based on the quality of the solution, the application of theoretical concepts, and the ability to work within a team.
The final-year thesis or capstone project is a significant component of the program, providing students with the opportunity to apply their knowledge and skills to a real-world problem or research question. Students are encouraged to select projects that align with their interests and career goals, and they are provided with guidance and mentorship from faculty members. The project is typically a multi-semester endeavor, with students working on it under the supervision of a faculty advisor.
The evaluation criteria for project-based learning are designed to assess not only the technical aspects of the project but also the student's ability to communicate, collaborate, and manage their work effectively. The evaluation includes peer review, faculty assessment, and a final presentation to a panel of experts. This comprehensive approach ensures that students develop a well-rounded skill set that is essential for success in the technology industry.