Comprehensive Course Structure
The curriculum for Electrical Engineering at Shivalik College of Engineering is meticulously designed to provide a balanced blend of theoretical knowledge and practical application. The program spans four years with a total of 8 semesters, each carrying specific learning objectives and course requirements.
Semester-wise Course Listing
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|---|
| First Year | I | MA101 | Mathematics I | 3-1-0-4 | - |
| PH101 | Physics | 3-1-0-4 | - | ||
| CH101 | Chemistry | 3-1-0-4 | - | ||
| EE101 | Introduction to Electrical Engineering | 2-0-0-2 | - | ||
| CS101 | Programming for Engineers | 2-0-0-2 | - | ||
| HS101 | English Communication | 2-0-0-2 | - | ||
| ME101 | Engineering Mechanics | 3-0-0-3 | - | ||
| GE101 | Professional Ethics and Values | 2-0-0-2 | - | ||
| II | MA102 | Mathematics II | 3-1-0-4 | MA101 | |
| PH102 | Physics Lab | 0-0-2-1 | PH101 | ||
| CH102 | Chemistry Lab | 0-0-2-1 | CH101 | ||
| EE102 | Circuit Analysis | 3-1-0-4 | EE101 | ||
| CS102 | Data Structures and Algorithms | 3-0-0-3 | CS101 | ||
| HS102 | Technical Writing | 2-0-0-2 | HS101 | ||
| ME102 | Mechanics of Materials | 3-0-0-3 | ME101 | ||
| GE102 | Leadership and Teamwork | 2-0-0-2 | - | ||
| Second Year | III | MA201 | Mathematics III | 3-1-0-4 | MA102 |
| EE201 | Electrical Machines I | 3-1-0-4 | EE102 | ||
| EE202 | Electronic Devices and Circuits | 3-1-0-4 | EE102 | ||
| EE203 | Signals and Systems | 3-1-0-4 | MA102 | ||
| CS201 | Database Management Systems | 3-0-0-3 | CS102 | ||
| HS201 | Communication Skills | 2-0-0-2 | - | ||
| ME201 | Mechanical Engineering Fundamentals | 3-0-0-3 | ME102 | ||
| GE201 | Cultural Awareness and Social Responsibility | 2-0-0-2 | - | ||
| IV | MA202 | Mathematics IV | 3-1-0-4 | MA201 | |
| EE204 | Power Systems I | 3-1-0-4 | EE201 | ||
| EE205 | Digital Logic Design | 3-1-0-4 | EE202 | ||
| EE206 | Control Systems I | 3-1-0-4 | EE203 | ||
| CS202 | Operating Systems | 3-0-0-3 | CS201 | ||
| HS202 | Leadership and Innovation | 2-0-0-2 | HS201 | ||
| ME202 | Thermodynamics | 3-0-0-3 | ME201 | ||
| GE202 | Environmental Awareness | 2-0-0-2 | - | ||
| Third Year | V | EE301 | Power Electronics | 3-1-0-4 | EE204 |
| EE302 | Electromagnetic Fields | 3-1-0-4 | EE203 | ||
| EE303 | Microprocessors and Microcontrollers | 3-1-0-4 | EE205 | ||
| EE304 | Communication Systems | 3-1-0-4 | EE203 | ||
| EE305 | Signal Processing | 3-1-0-4 | EE203 | ||
| CS301 | Computer Networks | 3-0-0-3 | CS202 | ||
| HS301 | Business Ethics and Management | 2-0-0-2 | - | ||
| GE301 | Global Perspectives | 2-0-0-2 | - | ||
| VI | EE306 | Industrial Automation | 3-1-0-4 | EE301 | |
| EE307 | Renewable Energy Systems | 3-1-0-4 | EE204 | ||
| EE308 | Advanced Control Systems | 3-1-0-4 | EE206 | ||
| EE309 | Embedded Systems | 3-1-0-4 | EE303 | ||
| EE310 | Machine Learning for Engineers | 3-1-0-4 | EE305 | ||
| CS302 | Software Engineering | 3-0-0-3 | CS202 | ||
| HS302 | Project Management | 2-0-0-2 | - | ||
| GE302 | Sustainable Development | 2-0-0-2 | - | ||
| Fourth Year | VII | EE401 | Advanced Power Systems | 3-1-0-4 | EE301 |
| EE402 | VLSI Design | 3-1-0-4 | EE309 | ||
| EE403 | Biomedical Instrumentation | 3-1-0-4 | EE302 | ||
| EE404 | Smart Grid Technologies | 3-1-0-4 | EE307 | ||
| EE405 | Research Methodology | 2-0-0-2 | - | ||
| CS401 | Artificial Intelligence | 3-0-0-3 | CS302 | ||
| HS401 | Entrepreneurship and Innovation | 2-0-0-2 | - | ||
| GE401 | Global Challenges and Solutions | 2-0-0-2 | - | ||
| VIII | EE406 | Final Year Project I | 3-0-0-3 | EE401, EE402 | |
| EE407 | Final Year Project II | 3-0-0-3 | EE406 | ||
| EE408 | Elective I (Departmental) | 3-0-0-3 | - | ||
| EE409 | Elective II (Departmental) | 3-0-0-3 | - | ||
| EE410 | Elective III (Science) | 2-0-0-2 | - | ||
| CS402 | Capstone Project | 3-0-0-3 | CS401 | ||
| HS402 | Professional Development | 2-0-0-2 | - | ||
| GE402 | Capstone Presentation | 2-0-0-2 | - |
Advanced Departmental Elective Courses
Departmental electives provide students with opportunities to specialize in emerging areas within Electrical Engineering. These courses are designed to align with current industry trends and research directions, ensuring that graduates remain competitive in the global marketplace.
Power Electronics and Drives
This course explores the principles and applications of power electronics converters, including DC-DC converters, AC-DC rectifiers, and inverters. Students learn to design and analyze circuits for various applications such as renewable energy systems, electric vehicle charging stations, and industrial motor drives.
Smart Grid Technologies
This course covers the integration of distributed energy resources into electrical grids, including concepts like grid stability, demand response, and intelligent control strategies. It addresses challenges in modernizing aging infrastructure while incorporating renewable sources and smart metering technologies.
Renewable Energy Systems
Focusing on solar photovoltaic systems, wind energy conversion, and hydroelectric generation, this course provides a comprehensive understanding of clean energy technologies. Students explore system design, efficiency optimization, and grid integration challenges specific to renewable sources.
Embedded Systems Design
This advanced elective introduces students to the architecture and programming of embedded systems using microcontrollers and real-time operating systems. Topics include hardware-software co-design, sensor integration, communication protocols, and application-specific development techniques.
VLSI Design Principles
Students learn to design complex integrated circuits using CAD tools and design methodologies. The course covers digital design, logic synthesis, layout design, and verification methods for modern semiconductor devices used in electronics applications.
Biomedical Instrumentation
This interdisciplinary course bridges electrical engineering with healthcare by focusing on medical device development and signal processing techniques. Students explore biomedical sensors, patient monitoring systems, and diagnostic equipment used in clinical settings.
Signal Processing Applications
Building upon foundational knowledge of signals and systems, this course applies advanced signal processing techniques to real-world problems. It covers digital filtering, spectral analysis, image processing, and audio applications using MATLAB and other industry-standard tools.
Control Systems Engineering
This elective delves into modern control theory including state-space representation, optimal control, and robust control strategies. Students gain hands-on experience in designing control systems for mechanical and electrical processes.
Machine Learning for Electrical Engineers
Integrating artificial intelligence concepts with electrical engineering applications, this course focuses on using machine learning techniques to solve problems in power systems, communication networks, and signal processing. Students learn to implement algorithms using Python and TensorFlow libraries.
Industrial Automation and Robotics
This course explores automation technologies used in manufacturing environments including programmable logic controllers (PLCs), human-machine interfaces (HMIs), and robotic systems. Students gain practical experience in designing and implementing automated solutions for industrial applications.
Project-Based Learning Philosophy
Project-based learning is central to our educational philosophy, emphasizing hands-on experience that bridges theory with real-world practice. Students begin working on projects from their first semester, gradually increasing complexity as they progress through the program.
Mini-Projects
Mini-projects are undertaken during the first and second years, focusing on fundamental concepts and practical skills development. These projects typically involve designing and building simple circuits or systems, fostering early engagement with engineering principles.
Final Year Thesis/Capstone Project
The capstone project is a comprehensive endeavor that spans the entire final year. Students select a topic aligned with their interests and career goals, working under the guidance of faculty mentors. Projects often involve collaboration with industry partners, leading to innovations that can be patented or commercialized.
Project Selection Process
Students are encouraged to propose project ideas during their third year, considering available resources and faculty expertise. The selection process involves a review committee that evaluates proposals based on feasibility, relevance, and potential impact. Faculty mentors are assigned based on project requirements and individual student interests.
Evaluation Criteria
Projects are evaluated using multiple criteria including technical soundness, innovation, presentation quality, and peer collaboration. Students must submit progress reports at defined intervals and present their findings to faculty panels. The final evaluation includes a demonstration of the implemented solution and a written report documenting the process and outcomes.