Course Structure Overview
The Electrical program at Govt Polytechnic Khatima is structured over eight semesters, with a carefully balanced blend of foundational courses, core engineering subjects, departmental electives, and practical laboratory work. The curriculum emphasizes both theoretical understanding and hands-on application, preparing students for real-world challenges in the field of electrical engineering.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | MATH101 | Calculus I | 3-1-0-4 | - |
| 1 | PHYS101 | Physics I | 3-1-0-4 | - |
| 1 | ENGL101 | English Communication Skills | 2-0-0-2 | - |
| 1 | EC101 | Introduction to Electrical Engineering | 2-0-0-2 | - |
| 1 | CSE101 | Programming Fundamentals | 2-0-0-2 | - |
| 2 | MATH102 | Calculus II | 3-1-0-4 | MATH101 |
| 2 | PHYS102 | Physics II | 3-1-0-4 | PHYS101 |
| 2 | EC102 | Circuit Analysis | 3-1-0-4 | - |
| 2 | ELEC101 | Electrical Measurements | 2-0-0-2 | - |
| 2 | EE101 | Basics of Electrical Machines | 2-0-0-2 | - |
| 3 | MATH201 | Differential Equations | 3-1-0-4 | MATH102 |
| 3 | PHYS201 | Electromagnetic Fields | 3-1-0-4 | PHYS102 |
| 3 | EC201 | Network Analysis | 3-1-0-4 | EC102 |
| 3 | ELEC201 | Power System Basics | 2-0-0-2 | - |
| 3 | EE201 | Electrical Machines I | 2-0-0-2 | - |
| 4 | MATH202 | Probability and Statistics | 3-1-0-4 | MATH201 |
| 4 | PHYS202 | Optics and Modern Physics | 3-1-0-4 | PHYS201 |
| 4 | EC301 | Electronic Devices | 3-1-0-4 | EC201 |
| 4 | ELEC301 | Control Systems | 2-0-0-2 | - |
| 4 | EE301 | Electrical Machines II | 2-0-0-2 | EE201 |
| 5 | MATH301 | Numerical Methods | 3-1-0-4 | MATH202 |
| 5 | EC401 | Digital Logic Design | 3-1-0-4 | EC301 |
| 5 | ELEC401 | Power Electronics | 2-0-0-2 | - |
| 5 | EE401 | Microprocessors and Microcontrollers | 2-0-0-2 | - |
| 5 | EE501 | Advanced Electrical Machines | 2-0-0-2 | EE301 |
| 6 | EC501 | Signals and Systems | 3-1-0-4 | EC401 |
| 6 | ELEC501 | Renewable Energy Systems | 2-0-0-2 | - |
| 6 | EE601 | Embedded Systems | 2-0-0-2 | - |
| 6 | EE701 | Power System Protection | 2-0-0-2 | - |
| 7 | EC601 | Communication Systems | 3-1-0-4 | EC501 |
| 7 | ELEC601 | Smart Grids | 2-0-0-2 | - |
| 7 | EE801 | Industrial Automation | 2-0-0-2 | - |
| 7 | EE901 | Artificial Intelligence in Electrical Applications | 2-0-0-2 | - |
| 8 | EC701 | Capstone Project | 3-1-0-4 | All previous semesters |
| 8 | ELEC701 | Research Methodology | 2-0-0-2 | - |
| 8 | EE1001 | Project Presentation and Viva Voce | 2-0-0-2 | - |
Advanced Departmental Electives
Departmental electives offer students the opportunity to specialize in niche areas of interest. These courses are designed to provide depth and breadth beyond the core curriculum, preparing students for advanced roles in industry or further academic pursuits.
The course 'Renewable Energy Systems' delves into solar photovoltaic technology, wind turbine design, hydroelectric generation, and energy storage solutions. Students study real-world case studies and participate in hands-on experiments using actual renewable energy systems.
'Power System Protection' explores the principles of relay operation, fault analysis, and protective relaying schemes in power systems. The course includes simulation exercises using industry-standard software like ETAP and DIgSILENT.
'Embedded Systems' introduces students to microcontroller architecture, real-time operating systems, sensor integration, and embedded C programming. Projects involve building functional prototypes for applications in IoT and automation.
'Control Engineering' covers classical and modern control theory, state-space methods, digital control systems, and system identification techniques. Students gain proficiency in MATLAB/Simulink-based modeling and simulation tools.
'Signal Processing' focuses on digital signal processing algorithms, filter design, and spectral analysis techniques. The course includes practical sessions using software like Python with NumPy/SciPy libraries and MATLAB.
'VLSI Design' provides an in-depth understanding of integrated circuit design processes, logic synthesis, layout design, and verification methods. Students use industry-standard tools such as Cadence and Mentor Graphics for design implementation.
'Smart Grids' examines the integration of modern technologies into traditional power grids to improve efficiency, reliability, and sustainability. Topics include grid automation, demand response systems, and energy management strategies.
'Industrial Automation' focuses on the application of control systems and sensors in manufacturing environments. Students learn about programmable logic controllers (PLCs), industrial communication protocols, and robotic integration.
'Artificial Intelligence in Electrical Applications' introduces students to machine learning algorithms and neural networks applied to electrical systems. The course covers predictive maintenance, energy optimization, and intelligent control systems using Python and TensorFlow.
Project-Based Learning Approach
The department strongly advocates for project-based learning as a cornerstone of the educational experience. This approach encourages students to apply theoretical knowledge in practical scenarios, fostering innovation and problem-solving skills.
Mini-projects are undertaken during the third and fourth semesters, with each project lasting approximately 6-8 weeks. Students form teams and select projects based on their interests and faculty expertise. Each team receives guidance from a designated faculty mentor who ensures academic rigor and practical relevance.
The final-year thesis/capstone project is a comprehensive endeavor that spans the entire eighth semester. Students work closely with faculty advisors to define research questions, conduct literature reviews, design experiments, and present findings. Projects are evaluated based on originality, technical depth, and contribution to the field.
Project selection is facilitated through an online portal where students can browse available projects posted by faculty members. The selection process considers student preferences, project requirements, and availability of resources.