Electrical Engineering Curriculum at Ramchandra Chandravansi University Palamu
The Electrical Engineering program at Ramchandra Chandravansi University Palamu is structured over eight semesters, with a carefully designed curriculum that balances theoretical knowledge with practical application. The program is divided into core subjects, departmental electives, science electives, and laboratory courses to ensure a well-rounded education.
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | None |
| 1 | PHY101 | Physics for Engineers | 3-1-0-4 | None |
| 1 | CHM101 | Chemistry for Engineers | 3-1-0-4 | None |
| 1 | ECO101 | Engineering Economics | 2-0-0-2 | None |
| 1 | CS101 | Introduction to Programming | 2-0-2-4 | None |
| 1 | LAB101 | Basic Engineering Lab | 0-0-3-3 | None |
| 2 | ENG102 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| 2 | PHY102 | Modern Physics | 3-1-0-4 | PHY101 |
| 2 | ECO102 | Business Communication | 2-0-0-2 | None |
| 2 | CS102 | Data Structures | 2-0-2-4 | CS101 |
| 2 | LAB102 | Basic Electronics Lab | 0-0-3-3 | None |
| 3 | EEE201 | Circuit Theory | 3-1-0-4 | ENG101, PHY101 |
| 3 | EEE202 | Electronic Devices | 3-1-0-4 | PHY101 |
| 3 | EEE203 | Digital Logic Design | 3-1-0-4 | CS101 |
| 3 | EEE204 | Signals and Systems | 3-1-0-4 | ENG102 |
| 3 | LAB201 | Circuit and Electronics Lab | 0-0-3-3 | None |
| 4 | EEE301 | Electromagnetic Fields | 3-1-0-4 | ENG102, PHY102 |
| 4 | EEE302 | Microprocessors and Microcontrollers | 3-1-0-4 | EEE203 |
| 4 | EEE303 | Control Systems | 3-1-0-4 | EEE201 |
| 4 | EEE304 | Power Electronics | 3-1-0-4 | EEE202 |
| 4 | LAB301 | Control and Power Electronics Lab | 0-0-3-3 | None |
| 5 | EEE401 | Power Systems | 3-1-0-4 | EEE201, EEE301 |
| 5 | EEE402 | Communication Systems | 3-1-0-4 | EEE204 |
| 5 | EEE403 | Signal Processing | 3-1-0-4 | EEE204 |
| 5 | EEE404 | Embedded Systems | 3-1-0-4 | EEE203 |
| 5 | LAB401 | Advanced Electronics Lab | 0-0-3-3 | None |
| 6 | EEE501 | Renewable Energy Systems | 3-1-0-4 | EEE401 |
| 6 | EEE502 | Industrial Automation | 3-1-0-4 | EEE303 |
| 6 | EEE503 | Artificial Intelligence | 3-1-0-4 | CS102 |
| 6 | EEE504 | Data Science | 3-1-0-4 | CS102 |
| 6 | LAB501 | Specialized Lab | 0-0-3-3 | None |
| 7 | EEE601 | Research Methodology | 2-0-0-2 | None |
| 7 | EEE602 | Capstone Project I | 0-0-6-6 | None |
| 7 | EEE603 | Mini Project | 0-0-3-3 | None |
| 7 | EEE604 | Advanced Topics in EEE | 2-0-0-2 | None |
| 7 | LAB601 | Capstone Lab | 0-0-3-3 | None |
| 8 | EEE701 | Capstone Project II | 0-0-6-6 | None |
| 8 | EEE702 | Internship | 0-0-0-12 | None |
| 8 | EEE703 | Professional Ethics | 2-0-0-2 | None |
| 8 | EEE704 | Elective Course | 3-1-0-4 | None |
| 8 | LAB701 | Final Lab | 0-0-3-3 | None |
Advanced Departmental Electives
Advanced departmental electives in the Electrical Engineering program at Ramchandra Chandravansi University Palamu are designed to provide students with specialized knowledge in emerging fields. These courses are offered in the final two years of the program and are tailored to meet the evolving demands of the industry.
One such course is 'Renewable Energy Systems,' which delves into the principles and technologies of solar, wind, and hydroelectric power generation. The course covers topics such as grid integration, energy storage systems, and environmental impact assessment. Students are exposed to real-world case studies and are encouraged to work on projects that address current energy challenges.
The 'Industrial Automation' course focuses on the design and implementation of automated systems in manufacturing and industrial processes. Students learn about programmable logic controllers (PLCs), sensor integration, and process control systems. The course emphasizes practical applications and includes hands-on laboratory sessions.
'Artificial Intelligence' is a cutting-edge elective that introduces students to machine learning, neural networks, and deep learning algorithms. The course includes programming assignments and projects that allow students to apply AI techniques to real-world problems. The faculty leading this course are experts in AI and have collaborated with industry leaders to ensure that the curriculum is aligned with current trends.
'Data Science' is another advanced elective that covers statistical analysis, data mining, and visualization techniques. Students are trained in tools such as Python, R, and SQL, and are exposed to big data technologies. The course includes a capstone project where students work on a real dataset to solve a business problem.
'Signal Processing' explores the mathematical techniques used to process and analyze signals. The course covers topics such as digital signal processing, filter design, and spectral analysis. Students gain practical experience through laboratory sessions and project work.
'Communication Systems' focuses on the principles of data communication and networking. Students study topics such as modulation techniques, error correction, and network protocols. The course includes laboratory experiments that simulate real-world communication systems.
'Power Electronics' is an advanced course that deals with the design and application of power electronic converters and inverters. Students learn about semiconductor devices, power conversion techniques, and applications in renewable energy and motor drives.
'Control Systems' is a core elective that delves into the theory and application of control systems. Students study feedback control, stability analysis, and system design. The course includes laboratory sessions that allow students to implement control algorithms in real-time systems.
'Embedded Systems' is an elective that focuses on the design and implementation of embedded software and hardware. Students learn about microcontrollers, real-time operating systems, and IoT applications. The course includes hands-on projects that involve building embedded systems from scratch.
'Nanotechnology' is an interdisciplinary elective that explores the applications of nanoscale materials and devices in electrical engineering. Students study topics such as quantum dots, nanoelectronics, and nanomaterials. The course includes laboratory sessions and projects that involve working with nanoscale components.
Project-Based Learning Philosophy
The Electrical Engineering program at Ramchandra Chandravansi University Palamu places a strong emphasis on project-based learning. This approach is designed to provide students with practical experience and to foster innovation and creativity.
Mini-projects are introduced in the third year of the program and are integrated into the curriculum as part of the course structure. These projects are designed to be small-scale and are typically completed in a semester. Students are assigned to teams and are guided by faculty mentors. The projects are evaluated based on the quality of the solution, the team's collaboration, and the presentation.
The final-year thesis/capstone project is a significant component of the program. Students are required to select a project topic that aligns with their interests and career goals. The project is typically a large-scale, complex task that requires students to apply all the knowledge and skills they have acquired throughout their studies.
Students are encouraged to choose their projects in consultation with faculty mentors. The selection process is based on the availability of resources, the feasibility of the project, and the student's interest and aptitude. Faculty mentors provide guidance and support throughout the project lifecycle, from planning to execution to final presentation.
The evaluation criteria for projects include technical merit, innovation, presentation, and the ability to work in a team. The department also encourages students to participate in national and international competitions, which provides them with exposure and recognition.