Comprehensive Course Catalog
The following table presents the complete course catalog for the Electrical Engineering program across all eight semesters. It includes course codes, full titles, credit structure (L-T-P-C), and pre-requisites.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | MATH101 | Calculus I | 3-1-0-4 | - |
| 1 | MATH102 | Linear Algebra and Differential Equations | 3-1-0-4 | - |
| 1 | PHYS101 | Physics I | 3-1-0-4 | - |
| 1 | PHYS102 | Physics Lab I | 0-0-3-1 | - |
| 1 | CSE101 | Introduction to Computer Programming | 2-1-0-3 | - |
| 1 | CSE102 | Programming Lab | 0-0-3-1 | - |
| 1 | ENG101 | English for Engineers | 2-0-0-2 | - |
| 1 | MECH101 | Introduction to Mechanical Engineering | 2-0-0-2 | - |
| 2 | MATH201 | Calculus II | 3-1-0-4 | MATH101 |
| 2 | MATH202 | Probability and Statistics | 3-1-0-4 | MATH101 |
| 2 | PHYS201 | Physics II | 3-1-0-4 | PHYS101 |
| 2 | PHYS202 | Physics Lab II | 0-0-3-1 | PHYS102 |
| 2 | CSE201 | Data Structures and Algorithms | 3-1-0-4 | CSE101 |
| 2 | CSE202 | Algorithm Lab | 0-0-3-1 | CSE102 |
| 2 | ECE101 | Basic Electrical Engineering | 3-1-0-4 | - |
| 2 | ECE102 | Electrical Lab I | 0-0-3-1 | - |
| 3 | MATH301 | Vector Calculus and Complex Variables | 3-1-0-4 | MATH201 |
| 3 | ECE201 | Circuit Analysis | 3-1-0-4 | ECE101 |
| 3 | ECE202 | Circuit Lab | 0-0-3-1 | ECE102 |
| 3 | ECE203 | Electromagnetic Fields | 3-1-0-4 | MATH202, PHYS201 |
| 3 | ECE204 | EMF Lab | 0-0-3-1 | ECE203 |
| 3 | ECE205 | Signals and Systems | 3-1-0-4 | MATH201, ECE201 |
| 3 | ECE206 | Signals Lab | 0-0-3-1 | ECE205 |
| 3 | ECE207 | Digital Logic Design | 3-1-0-4 | ECE101 |
| 3 | ECE208 | Digital Lab | 0-0-3-1 | ECE207 |
| 4 | ECE301 | Electrical Machines I | 3-1-0-4 | ECE201 |
| 4 | ECE302 | Machines Lab I | 0-0-3-1 | ECE301 |
| 4 | ECE303 | Power Electronics | 3-1-0-4 | ECE201 |
| 4 | ECE304 | Power Electronics Lab | 0-0-3-1 | ECE303 |
| 4 | ECE305 | Control Systems | 3-1-0-4 | ECE205 |
| 4 | ECE306 | Control Systems Lab | 0-0-3-1 | ECE305 |
| 4 | ECE307 | Microprocessor Architecture | 3-1-0-4 | CSE201 |
| 4 | ECE308 | Microprocessor Lab | 0-0-3-1 | ECE307 |
| 5 | ECE401 | Power Systems I | 3-1-0-4 | ECE301 |
| 5 | ECE402 | Power Systems Lab I | 0-0-3-1 | ECE401 |
| 5 | ECE403 | Digital Signal Processing | 3-1-0-4 | ECE205 |
| 5 | ECE404 | DSP Lab | 0-0-3-1 | ECE403 |
| 5 | ECE405 | Communication Systems | 3-1-0-4 | ECE205 |
| 5 | ECE406 | Communication Lab | 0-0-3-1 | ECE405 |
| 5 | ECE407 | Electronics Devices and Circuits | 3-1-0-4 | ECE201 |
| 5 | ECE408 | EDC Lab | 0-0-3-1 | ECE407 |
| 6 | ECE501 | Power Systems II | 3-1-0-4 | ECE401 |
| 6 | ECE502 | Power Systems Lab II | 0-0-3-1 | ECE501 |
| 6 | ECE503 | Advanced Control Systems | 3-1-0-4 | ECE305 |
| 6 | ECE504 | Control Systems Advanced Lab | 0-0-3-1 | ECE503 |
| 6 | ECE505 | VLSI Design | 3-1-0-4 | ECE407 |
| 6 | ECE506 | VLSI Lab | 0-0-3-1 | ECE505 |
| 6 | ECE507 | Embedded Systems | 3-1-0-4 | ECE307, CSE201 |
| 6 | ECE508 | Embedded Systems Lab | 0-0-3-1 | ECE507 |
| 7 | ECE601 | Renewable Energy Systems | 3-1-0-4 | ECE401, ECE303 |
| 7 | ECE602 | Renewable Energy Lab | 0-0-3-1 | ECE601 |
| 7 | ECE603 | AI and Machine Learning | 3-1-0-4 | ECE205, MATH202 |
| 7 | ECE604 | ML Lab | 0-0-3-1 | ECE603 |
| 7 | ECE605 | Energy Storage Technologies | 3-1-0-4 | ECE401, ECE303 |
| 7 | ECE606 | Energy Storage Lab | 0-0-3-1 | ECE605 |
| 7 | ECE607 | Smart Grid Technologies | 3-1-0-4 | ECE401 |
| 7 | ECE608 | Smart Grid Lab | 0-0-3-1 | ECE607 |
| 8 | ECE701 | Final Year Project I | 2-0-0-2 | All previous courses |
| 8 | ECE702 | Final Year Project II | 4-0-0-4 | ECE701 |
| 8 | ECE703 | Internship | 0-0-0-2 | All previous courses |
| 8 | ECE704 | Project Presentation | 0-0-0-1 | ECE702 |
Detailed Elective Course Descriptions
The department offers a wide range of advanced elective courses designed to deepen students' understanding and prepare them for specialized careers or further research. Here are detailed descriptions of key advanced departmental electives:
Electronics Devices and Circuits (ECE407)
This course explores the fundamental principles of semiconductor devices, including diodes, transistors, and integrated circuits. Students study device physics, fabrication processes, and circuit design techniques using modern simulation tools. The curriculum covers both theoretical analysis and practical implementation through laboratory experiments.
Learning Objectives:
- Understand the operation principles of various semiconductor devices
- Analyze and simulate electronic circuits using industry-standard software
- Design and fabricate simple integrated circuits
- Apply knowledge to real-world applications in electronics design
Digital Signal Processing (ECE403)
This course provides comprehensive coverage of digital signal processing techniques, including time-domain and frequency-domain analysis, filter design, and implementation. Students gain proficiency in MATLAB-based tools and learn how to apply DSP concepts to audio, image, and biomedical signal processing.
Learning Objectives:
- Develop understanding of discrete-time signals and systems
- Design digital filters using various methods (FIR, IIR)
- Implement signal processing algorithms on hardware platforms
- Analyze real-world signals in both time and frequency domains
Communication Systems (ECE405)
This course covers the principles of analog and digital communication systems, including modulation techniques, noise analysis, and system performance evaluation. Students explore modern communication technologies such as OFDM, spread spectrum, and wireless networks.
Learning Objectives:
- Understand transmission media and signal propagation
- Design communication protocols and systems
- Analyze performance under various noise conditions
- Implement basic communication schemes using simulation tools
VLSI Design (ECE505)
This course introduces students to the design and implementation of very large scale integrated circuits. Topics include CMOS technology, logic synthesis, circuit optimization, and testing methods. The curriculum emphasizes practical design experience through laboratory sessions.
Learning Objectives:
- Understand VLSI architecture and design flow
- Design combinational and sequential circuits at gate level
- Implement custom IC designs using CAD tools
- Optimize circuits for performance, area, and power consumption
Embedded Systems (ECE507)
This course focuses on designing and implementing embedded systems using microcontrollers and real-time operating systems. Students learn about hardware-software co-design, memory management, interrupt handling, and system integration.
Learning Objectives:
- Design embedded software for various hardware platforms
- Develop real-time applications using RTOS concepts
- Integrate sensors and actuators in embedded systems
- Implement communication protocols in embedded environments
AI and Machine Learning (ECE603)
This course provides an introduction to machine learning algorithms and their application in electrical engineering domains. Students study supervised and unsupervised learning techniques, neural networks, deep learning architectures, and reinforcement learning.
Learning Objectives:
- Understand fundamental ML concepts and algorithms
- Apply ML techniques to solve engineering problems
- Design and train neural network models using TensorFlow/PyTorch
- Evaluate model performance and optimize results
Power Electronics (ECE303)
This course covers the principles of power electronics, including converters, inverters, rectifiers, and motor drives. Students gain hands-on experience in designing power electronic circuits and analyzing their behavior under different operating conditions.
Learning Objectives:
- Understand power conversion principles and applications
- Design and analyze power electronic circuits
- Implement control strategies for power systems
- Evaluate efficiency and reliability of power electronic devices
Control Systems (ECE305)
This course provides a comprehensive treatment of classical and modern control theory, including system modeling, stability analysis, controller design, and state-space methods. Students apply these concepts to mechanical and electrical systems.
Learning Objectives:
- Model dynamic systems using differential equations
- Analyze system response and stability
- Design controllers for desired performance specifications
- Implement control systems in simulation environments
Renewable Energy Systems (ECE601)
This course addresses the integration of renewable energy sources into power grids. Students study photovoltaic systems, wind turbines, and other clean energy technologies, along with their control and monitoring strategies.
Learning Objectives:
- Understand renewable energy generation mechanisms
- Analyze grid integration challenges and solutions
- Design renewable energy systems for specific applications
- Evaluate environmental impact of energy systems
Smart Grid Technologies (ECE607)
This course explores smart grid concepts, including demand response, energy storage, and grid automation. Students examine how modern technologies improve efficiency, reliability, and sustainability in power distribution.
Learning Objectives:
- Understand smart grid architecture and components
- Analyze integration of distributed resources
- Design intelligent control systems for power grids
- Evaluate impact of smart technologies on energy markets
Project-Based Learning Philosophy
The department places significant emphasis on project-based learning as a cornerstone of its educational approach. This philosophy recognizes that hands-on experience is essential for developing practical skills and fostering innovation among students.
The mandatory mini-projects are designed to reinforce theoretical concepts learned in core courses while encouraging creativity and problem-solving. These projects typically span one semester and involve teams of 3-5 students working under faculty supervision. Each project is evaluated based on technical execution, innovation, presentation quality, and team collaboration.
The final-year thesis/capstone project represents the culmination of a student's academic journey. Students are expected to tackle complex real-world problems in their chosen specialization area, often collaborating with industry partners or faculty research groups. The project involves extensive literature review, experimental design, data analysis, and documentation.
Project selection is facilitated through a structured process where students present their interests and capabilities to faculty mentors. Faculty members provide guidance on project feasibility, scope, and resource requirements. The department maintains an online portal for project proposals, progress tracking, and milestone reporting.
Evaluation criteria include:
- Technical rigor and soundness of methodology
- Innovation and originality of approach
- Effective communication and documentation
- Teamwork and project management skills
- Adherence to deadlines and quality standards