Course Structure Overview
The engineering program at Ramchandra Chandravansi University Palamu is structured over eight semesters, with a carefully designed curriculum that balances foundational knowledge with specialized expertise. Each semester includes a combination of core engineering subjects, departmental electives, science electives, and laboratory courses to ensure a well-rounded education.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | None |
| 1 | ENG102 | Engineering Physics | 3-1-0-4 | None |
| 1 | ENG103 | Engineering Chemistry | 3-1-0-4 | None |
| 1 | ENG104 | Engineering Graphics | 2-1-0-3 | None |
| 1 | ENG105 | Programming and Problem Solving | 3-0-2-4 | None |
| 1 | ENG106 | Introduction to Engineering | 2-0-0-2 | None |
| 2 | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| 2 | ENG202 | Electrical and Electronic Circuits | 3-1-0-4 | ENG102 |
| 2 | ENG203 | Engineering Mechanics | 3-1-0-4 | ENG102 |
| 2 | ENG204 | Materials Science | 3-1-0-4 | ENG103 |
| 2 | ENG205 | Data Structures and Algorithms | 3-0-2-4 | ENG105 |
| 2 | ENG206 | Workshop Practice | 0-0-3-1 | None |
| 3 | ENG301 | Engineering Mathematics III | 3-1-0-4 | ENG201 |
| 3 | ENG302 | Thermodynamics | 3-1-0-4 | ENG202 |
| 3 | ENG303 | Fluid Mechanics | 3-1-0-4 | ENG203 |
| 3 | ENG304 | Machine Design | 3-1-0-4 | ENG203 |
| 3 | ENG305 | Database Management Systems | 3-0-2-4 | ENG205 |
| 3 | ENG306 | Signals and Systems | 3-1-0-4 | ENG201 |
| 4 | ENG401 | Engineering Mathematics IV | 3-1-0-4 | ENG301 |
| 4 | ENG402 | Control Systems | 3-1-0-4 | ENG306 |
| 4 | ENG403 | Heat Transfer | 3-1-0-4 | ENG302 |
| 4 | ENG404 | Manufacturing Processes | 3-1-0-4 | ENG304 |
| 4 | ENG405 | Computer Networks | 3-0-2-4 | ENG305 |
| 4 | ENG406 | Microprocessors and Microcontrollers | 3-0-2-4 | ENG202 |
| 5 | ENG501 | Advanced Mathematics | 3-1-0-4 | ENG401 |
| 5 | ENG502 | Power Systems | 3-1-0-4 | ENG202 |
| 5 | ENG503 | Structural Analysis | 3-1-0-4 | ENG304 |
| 5 | ENG504 | Advanced Algorithms | 3-0-2-4 | ENG305 |
| 5 | ENG505 | Software Engineering | 3-0-2-4 | ENG305 |
| 5 | ENG506 | Environmental Impact Assessment | 3-1-0-4 | ENG302 |
| 6 | ENG601 | Research Methodology | 2-0-0-2 | ENG501 |
| 6 | ENG602 | Project Management | 2-0-0-2 | ENG505 |
| 6 | ENG603 | Industrial Training | 0-0-6-3 | None |
| 6 | ENG604 | Capstone Project | 0-0-6-3 | ENG501 |
| 6 | ENG605 | Elective Course I | 3-0-2-4 | None |
| 6 | ENG606 | Elective Course II | 3-0-2-4 | None |
| 7 | ENG701 | Advanced Elective Course I | 3-0-2-4 | ENG605 |
| 7 | ENG702 | Advanced Elective Course II | 3-0-2-4 | ENG606 |
| 7 | ENG703 | Advanced Elective Course III | 3-0-2-4 | ENG605 |
| 7 | ENG704 | Advanced Elective Course IV | 3-0-2-4 | ENG606 |
| 7 | ENG705 | Research Project | 0-0-6-3 | ENG601 |
| 7 | ENG706 | Internship | 0-0-6-3 | None |
| 8 | ENG801 | Final Year Project | 0-0-6-3 | ENG705 |
| 8 | ENG802 | Professional Ethics | 2-0-0-2 | None |
| 8 | ENG803 | Elective Course III | 3-0-2-4 | None |
| 8 | ENG804 | Elective Course IV | 3-0-2-4 | None |
| 8 | ENG805 | Elective Course V | 3-0-2-4 | None |
| 8 | ENG806 | Elective Course VI | 3-0-2-4 | None |
Advanced Departmental Electives
Advanced departmental electives play a crucial role in the engineering program, offering students the opportunity to specialize in areas of interest and gain in-depth knowledge in specific fields. These courses are designed to complement the core curriculum and provide students with the skills necessary to excel in their chosen career paths.
The first advanced elective course, Advanced Machine Learning, focuses on the theoretical and practical aspects of machine learning algorithms. Students learn about supervised and unsupervised learning, deep learning architectures, and reinforcement learning techniques. The course includes hands-on projects that involve implementing machine learning models on real-world datasets, providing students with practical experience in data analysis and model development.
Another important elective is Advanced Computer Vision, which explores the principles and applications of computer vision technologies. Students study image processing techniques, object detection, and recognition algorithms, and learn to develop applications that can interpret and understand visual information from the world. The course includes laboratory sessions where students work with image datasets and develop computer vision models using frameworks such as TensorFlow and OpenCV.
Advanced Embedded Systems is an elective that delves into the design and development of embedded systems for various applications. Students learn about microcontrollers, real-time operating systems, and hardware-software integration. The course includes laboratory projects where students design and implement embedded systems for specific tasks, such as sensor networks and smart devices.
Advanced Control Systems is a course that covers the design and analysis of control systems for complex engineering applications. Students study state-space methods, frequency domain analysis, and digital control systems. The course includes simulation and laboratory components that allow students to implement control algorithms and test their performance in real-world scenarios.
Advanced Data Structures and Algorithms is an elective that builds upon the foundational knowledge of data structures and algorithms. Students explore advanced topics such as graph algorithms, dynamic programming, and computational complexity theory. The course includes programming assignments and projects that challenge students to develop efficient algorithms for solving complex problems.
Advanced Signal Processing is a course that focuses on the analysis and processing of signals in various domains. Students learn about digital signal processing techniques, filter design, and spectral analysis. The course includes laboratory sessions where students work with real signals and implement signal processing algorithms using tools such as MATLAB and Python.
Advanced Power Electronics is an elective that covers the design and application of power electronic converters and systems. Students study power semiconductor devices, converter topologies, and control strategies. The course includes laboratory projects where students design and test power electronic circuits for various applications, such as renewable energy systems and motor drives.
Advanced VLSI Design is a course that explores the design and implementation of very large-scale integration (VLSI) systems. Students learn about digital design methodologies, circuit simulation, and layout design. The course includes laboratory sessions where students use industry-standard tools to design and simulate VLSI circuits.
Advanced Network Security is an elective that focuses on the principles and practices of network security. Students study cryptographic techniques, network protocols, and security frameworks. The course includes hands-on projects where students implement security measures and analyze potential vulnerabilities in network systems.
Advanced Robotics and Automation is a course that covers the design and control of robotic systems. Students learn about robot kinematics, control systems, and sensor integration. The course includes laboratory projects where students design and build robots for specific tasks, such as manipulation and navigation.
Project-Based Learning Philosophy
The engineering program at Ramchandra Chandravansi University Palamu emphasizes 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 develop a deep understanding of engineering principles through hands-on experience.
Mini-projects are assigned throughout the program to provide students with opportunities to apply their knowledge in real-world scenarios. These projects are typically completed in small groups and are evaluated based on technical merit, innovation, and presentation skills. The projects are designed to be challenging yet achievable, allowing students to develop problem-solving skills and gain confidence in their abilities.
The final-year thesis/capstone project is a comprehensive endeavor that integrates all aspects of the student's learning experience. Students work closely with faculty mentors to select a project topic that aligns with their interests and career goals. The project involves extensive research, design, and implementation phases, culminating in a final presentation and report.
Students are encouraged to select projects that have real-world applications or address current challenges in their field. The university provides resources and support to help students successfully complete their projects, including access to research facilities, funding, and mentorship.
The evaluation criteria for projects include technical depth, innovation, teamwork, and presentation skills. Students are assessed not only on the outcome of their project but also on their ability to communicate their ideas effectively and work collaboratively with others.
Project-based learning fosters a culture of innovation and entrepreneurship, encouraging students to think creatively and develop solutions to complex problems. This approach prepares students for the challenges they will face in their professional careers and helps them develop the skills necessary to become successful engineers and leaders in their field.