Comprehensive Course Structure
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | PH101 | Physics I | 3-0-0-3 | - |
| 1 | CH101 | Chemistry I | 3-0-0-3 | - |
| 1 | MA101 | Mathematics I | 4-0-0-4 | - |
| 1 | ME101 | Introduction to Engineering | 2-0-0-2 | - |
| 1 | EC101 | Basic Electrical Engineering | 3-0-0-3 | - |
| 1 | EE101 | Engineering Drawing | 2-0-0-2 | - |
| 1 | EE102 | Computer Programming | 2-0-0-2 | - |
| 2 | PH102 | Physics II | 3-0-0-3 | PH101 |
| 2 | CH102 | Chemistry II | 3-0-0-3 | CH101 |
| 2 | MA102 | Mathematics II | 4-0-0-4 | MA101 |
| 2 | EC102 | Circuit Analysis | 3-0-0-3 | - |
| 2 | EE201 | Electromagnetic Fields | 3-0-0-3 | PH101, MA101 |
| 2 | EE202 | Signals and Systems | 3-0-0-3 | MA101, EC101 |
| 2 | EE203 | Digital Logic Design | 3-0-0-3 | - |
| 3 | PH201 | Physics III | 3-0-0-3 | PH102 |
| 3 | MA201 | Mathematics III | 4-0-0-4 | MA102 |
| 3 | EC201 | Electronics Devices and Circuits | 3-0-0-3 | EC102, EE202 |
| 3 | EE301 | Control Systems | 3-0-0-3 | EE202, MA201 |
| 3 | EE302 | Power Electronics | 3-0-0-3 | - |
| 3 | EE303 | Microprocessors and Microcontrollers | 3-0-0-3 | EC201, EE203 |
| 4 | PH202 | Physics IV | 3-0-0-3 | PH201 |
| 4 | MA202 | Mathematics IV | 4-0-0-4 | MA201 |
| 4 | EC301 | Communication Systems | 3-0-0-3 | EE202, EC201 |
| 4 | EE401 | Power System Analysis | 3-0-0-3 | EE301, EC201 |
| 4 | EE402 | Renewable Energy Systems | 3-0-0-3 | - |
| 4 | EE403 | Embedded Systems | 3-0-0-3 | EE303, EE202 |
| 5 | EE501 | Advanced Control Systems | 3-0-0-3 | EE301 |
| 5 | EE502 | Digital Signal Processing | 3-0-0-3 | EE202, MA201 |
| 5 | EE503 | Electromagnetic Compatibility | 3-0-0-3 | EE202, EE201 |
| 5 | EE504 | Advanced Power Electronics | 3-0-0-3 | EE302 |
| 6 | EE601 | Artificial Intelligence and Machine Learning | 3-0-0-3 | EE502, MA202 |
| 6 | EE602 | Smart Grid Technologies | 3-0-0-3 | EE401 |
| 6 | EE603 | Research Methodology | 2-0-0-2 | - |
| 7 | EE701 | Capstone Project I | 4-0-0-4 | - |
| 7 | EE702 | Advanced Topics in Electronics | 3-0-0-3 | EC201 |
| 8 | EE801 | Capstone Project II | 6-0-0-6 | - |
Advanced Departmental Elective Courses
The program offers a range of advanced departmental electives designed to provide in-depth knowledge and specialization opportunities. These courses are taught by faculty members who are experts in their respective fields.
Digital Signal Processing (EE502): This course delves into the mathematical foundations of digital signal processing, covering topics such as discrete-time signals and systems, Z-transforms, Fourier analysis, and filter design. Students gain hands-on experience with MATLAB and implement various DSP algorithms. The course emphasizes practical applications in audio and video processing, biomedical signal analysis, and telecommunications.
Artificial Intelligence and Machine Learning (EE601): This elective introduces students to the principles of AI and ML, including supervised and unsupervised learning, neural networks, deep learning architectures, and reinforcement learning. The course includes projects involving image recognition, natural language processing, and robotics applications.
Smart Grid Technologies (EE602): Focused on modern power grid systems, this course explores concepts such as grid stability, renewable energy integration, demand response management, and smart metering. Students learn about grid simulation tools and participate in case studies of real-world smart grid implementations.
Advanced Control Systems (EE501): This advanced course builds upon fundamental control theory by introducing state-space representation, optimal control, robust control, and nonlinear control techniques. The curriculum includes modeling and simulation of complex systems using MATLAB/Simulink and practical experiments with real-time controllers.
Electromagnetic Compatibility (EE503): This course addresses the challenges of electromagnetic interference in electronic devices. Topics include EMI sources, propagation mechanisms, shielding techniques, and compliance testing. Students work on designing EMI-compliant circuits and systems.
Advanced Power Electronics (EE504): Designed for students interested in power conversion technologies, this course covers advanced topics such as resonant converters, multilevel inverters, and wide-bandgap semiconductor devices. It includes laboratory sessions involving the design and testing of power electronic circuits.
Research Methodology (EE603): This course prepares students for conducting independent research. It covers literature review strategies, experimental design, data analysis methods, and scientific writing. Students complete a small-scale research project under faculty supervision.
Capstone Project I (EE701): In this semester, students begin their capstone project under the guidance of faculty mentors. They identify a relevant problem, conduct literature review, propose solutions, and develop a detailed project plan. The focus is on defining research questions, setting objectives, and selecting appropriate methodologies.
Capstone Project II (EE801): The final semester involves full implementation and documentation of the capstone project. Students present their findings, defend their work, and submit a comprehensive thesis. This course culminates in a public presentation and evaluation by a panel of experts.
Project-Based Learning Philosophy
The Electrical Engineering program at Ethics University embraces project-based learning as a cornerstone of education. Projects are integrated throughout the curriculum to ensure that students apply theoretical concepts to real-world problems. The approach emphasizes collaboration, critical thinking, and innovation.
Mini-projects are introduced in early semesters to help students understand practical applications of core concepts. These projects often involve building simple circuits, programming microcontrollers, or analyzing signals using simulation software. As students progress, the complexity of these projects increases, preparing them for more advanced challenges.
The final-year capstone project is a significant component of the program. Students select a topic aligned with their interests and career goals, work closely with faculty mentors, and produce an original contribution to the field. Projects often lead to publications, patents, or commercial ventures.
Faculty members play a crucial role in guiding students through their projects. They provide technical expertise, offer feedback on progress, and facilitate connections with industry partners who may sponsor or collaborate on research initiatives.