Curriculum Overview
The Electrical Engineering program at Govt Polytechnic Gopeshwar Chamoli is structured over 8 semesters, with a balanced mix of theoretical subjects, practical labs, departmental electives, and core engineering principles. This curriculum aims to build a strong foundation in electrical sciences while preparing students for real-world challenges through project-based learning and industry exposure.
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| I | MATH-101 | Mathematics I | 3-1-0-4 | - |
| I | PHY-101 | Physics for Electrical Engineering | 3-1-0-4 | - |
| I | CHEM-101 | Chemistry for Engineers | 3-1-0-4 | - |
| I | ENG-101 | English Communication Skills | 2-0-0-2 | - |
| I | ESC-101 | Engineering Drawing & Computer Graphics | 2-1-0-3 | - |
| I | ECO-101 | Environmental Science | 2-0-0-2 | - |
| I | LAB-101 | Basic Electrical Lab | 0-0-3-1 | - |
| I | LAB-102 | Basic Electronics Lab | 0-0-3-1 | - |
| II | MATH-201 | Mathematics II | 3-1-0-4 | MATH-101 |
| II | ECE-201 | Basic Electrical Engineering | 3-1-0-4 | - |
| II | EE-201 | Electromagnetic Fields | 3-1-0-4 | MATH-201, PHY-101 |
| II | CS-201 | Introduction to Programming | 2-1-0-3 | - |
| II | LIT-201 | Leadership & Teamwork | 2-0-0-2 | - |
| II | LAB-201 | Circuit Analysis Lab | 0-0-3-1 | - |
| III | MATH-301 | Mathematics III | 3-1-0-4 | MATH-201 |
| III | EE-301 | Network Analysis & Synthesis | 3-1-0-4 | ECE-201, MATH-201 |
| III | EE-302 | Electrical Machines I | 3-1-0-4 | ECE-201 |
| III | EE-303 | Power Electronics | 3-1-0-4 | - |
| III | CS-301 | Data Structures & Algorithms | 2-1-0-3 | CS-201 |
| III | LAB-301 | Machine Lab | 0-0-3-1 | - |
| IV | MATH-401 | Mathematics IV | 3-1-0-4 | MATH-301 |
| IV | EE-401 | Control Systems | 3-1-0-4 | EE-301, MATH-301 |
| IV | EE-402 | Electrical Machines II | 3-1-0-4 | EE-302 |
| IV | EE-403 | Power Systems | 3-1-0-4 | EE-301 |
| IV | CS-401 | Computer Architecture | 2-1-0-3 | CS-301 |
| IV | LAB-401 | Control Systems Lab | 0-0-3-1 | - |
| V | EE-501 | Digital Signal Processing | 3-1-0-4 | MATH-401, EE-401 |
| V | EE-502 | Embedded Systems | 3-1-0-4 | CS-401 |
| V | EE-503 | Renewable Energy Systems | 3-1-0-4 | EE-403 |
| V | EE-504 | Electronics Devices & Circuits | 3-1-0-4 | EE-303 |
| V | EE-505 | Communication Systems | 3-1-0-4 | EE-501 |
| V | LAB-501 | DSP & Embedded Lab | 0-0-3-1 | - |
| VI | EE-601 | Smart Grid Technologies | 3-1-0-4 | EE-503 |
| VI | EE-602 | Power System Protection | 3-1-0-4 | EE-403 |
| VI | EE-603 | Robotics & Automation | 3-1-0-4 | EE-401 |
| VI | EE-604 | Energy Storage Systems | 3-1-0-4 | EE-503 |
| VI | EE-605 | Advanced Control Theory | 3-1-0-4 | EE-401 |
| VI | LAB-601 | Advanced Lab Project | 0-0-3-1 | - |
| VII | EE-701 | Capstone Project I | 2-0-0-4 | - |
| VII | EE-702 | Project Management | 2-0-0-2 | - |
| VII | EE-703 | Internship | 0-0-0-4 | - |
| VIII | EE-801 | Capstone Project II | 2-0-0-6 | - |
| VIII | EE-802 | Research Methodology | 2-0-0-2 | - |
| VIII | EE-803 | Industrial Training | 0-0-0-4 | - |
Advanced Departmental Electives
These advanced courses allow students to specialize in emerging domains and prepare them for future leadership roles in their respective fields:
- Digital Signal Processing (DSP): This course focuses on mathematical methods used to process digital signals such as audio, video, and biomedical data. Students learn about sampling theory, filter design, and fast Fourier transforms.
- Embedded Systems Design: Students are introduced to microcontrollers, real-time operating systems, and hardware-software integration techniques essential for designing embedded applications in automotive, aerospace, and consumer electronics.
- Renewable Energy Systems: This course covers solar photovoltaic systems, wind energy conversion, hydroelectric power, and energy storage solutions. It includes practical sessions on system design and simulation tools.
- Power Electronics & Drives: Covers power electronic converters, motor drives, inverter technologies, and their applications in industrial automation and renewable energy systems.
- Smart Grid Technologies: Explores smart meters, demand response programs, grid stability analysis, and integration of distributed generation sources into the main grid.
- Control Systems & Automation: Focuses on modern control theory, state-space methods, PID controllers, and automation systems used in manufacturing and process industries.
- Energy Storage Systems: Teaches principles of battery technologies, supercapacitors, fuel cells, and energy storage management for grid-scale applications.
- Robotics & AI Integration: Combines robotics with artificial intelligence to develop intelligent autonomous systems for applications in manufacturing, healthcare, and exploration.
- Power System Protection: Covers relay settings, fault analysis, protection schemes, and cybersecurity aspects of power systems.
- Advanced Control Theory: Delves into optimal control, robust control, nonlinear control systems, and adaptive control methods for complex industrial processes.
Project-Based Learning Philosophy
The department follows a rigorous project-based learning model that emphasizes critical thinking, innovation, and teamwork. Students begin with guided mini-projects in their second year and progress to independent capstone projects in their final year.
Mini-projects are assigned at the end of each semester and typically last 4–6 weeks. These projects are designed to reinforce concepts learned in class and introduce students to real-world engineering challenges. Projects may involve designing circuits, simulating systems, or developing software tools.
The final-year thesis/capstone project is a comprehensive endeavor that spans two semesters. Students select their topic under the guidance of a faculty mentor based on their interest areas and career goals. The project involves extensive literature review, experimental design, implementation, testing, and documentation.
Students are evaluated through continuous assessments, peer reviews, oral presentations, and final project reports. Faculty mentors provide feedback throughout the process to ensure quality and relevance of outcomes.