Comprehensive Course Structure
The Bachelor of Electrical Engineering program at Iasscom Fortune Institute of Technology is meticulously structured to ensure a seamless progression from foundational concepts to advanced engineering skills. The curriculum spans eight semesters, each designed with careful attention to academic rigor and practical relevance.
Semester-wise Course Breakdown
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|---|
| Year 1 | Semester 1 | MA101 | Calculus I | 3-1-0-4 | - |
| PH101 | Physics for Engineers | 3-1-0-4 | - | ||
| CH101 | Chemistry for Engineers | 3-1-0-4 | - | ||
| ME101 | Introduction to Engineering | 2-0-0-2 | - | ||
| CS101 | Programming Fundamentals | 2-0-2-4 | - | ||
| EG101 | Engineering Graphics | 2-0-2-4 | - | ||
| EC101 | Basic Electrical Engineering | 3-1-0-4 | - | ||
| Year 1 | Semester 2 | MA102 | Calculus II | 3-1-0-4 | MA101 |
| PH102 | Modern Physics | 3-1-0-4 | PH101 | ||
| EC102 | Circuit Analysis | 3-1-0-4 | EC101 | ||
| CS102 | Data Structures and Algorithms | 2-0-2-4 | CS101 | ||
| ES101 | Environmental Science | 3-0-0-3 | - | ||
| EC103 | Electromagnetic Fields | 3-1-0-4 | PH101 | ||
| ME102 | Engineering Mechanics | 3-1-0-4 | - | ||
| Year 2 | Semester 3 | MA201 | Linear Algebra and Differential Equations | 3-1-0-4 | MA102 |
| EC201 | Signals and Systems | 3-1-0-4 | EC102 | ||
| EC202 | Electronic Devices and Circuits | 3-1-0-4 | EC103 | ||
| EC203 | Network Analysis | 3-1-0-4 | EC102 | ||
| CS201 | Object-Oriented Programming | 2-0-2-4 | CS102 | ||
| EC204 | Microprocessor and Microcontroller Applications | 3-1-2-6 | EC202 | ||
| EC205 | Electrical Machines I | 3-1-0-4 | EC102 | ||
| Year 2 | Semester 4 | MA202 | Probability and Statistics | 3-1-0-4 | MA201 |
| EC206 | Power Electronics | 3-1-0-4 | EC202 | ||
| EC207 | Control Systems | 3-1-0-4 | EC201 | ||
| EC208 | Electromagnetic Waves and Transmission Lines | 3-1-0-4 | EC103 | ||
| EC209 | Communication Systems | 3-1-0-4 | EC201 | ||
| EC210 | Digital Logic Design | 3-1-2-6 | EC202 | ||
| EC211 | Electrical Machines II | 3-1-0-4 | EC205 | ||
| Year 3 | Semester 5 | EC301 | Digital Signal Processing | 3-1-0-4 | EC201 |
| EC302 | Power Generation and Distribution | 3-1-0-4 | EC205 | ||
| EC303 | Embedded Systems | 3-1-2-6 | EC204 | ||
| EC304 | Control System Design | 3-1-0-4 | EC207 | ||
| EC305 | Antenna Theory | 3-1-0-4 | EC208 | ||
| EC306 | Optoelectronics | 3-1-0-4 | EC202 | ||
| EC307 | Industrial Automation | 3-1-0-4 | EC207 | ||
| Year 3 | Semester 6 | EC308 | Artificial Intelligence and Machine Learning | 3-1-0-4 | EC201 |
| EC309 | Renewable Energy Systems | 3-1-0-4 | EC202 | ||
| EC310 | Wireless Communication | 3-1-0-4 | EC209 | ||
| EC311 | VLSI Design | 3-1-2-6 | EC202 | ||
| EC312 | Smart Grid Technologies | 3-1-0-4 | EC302 | ||
| EC313 | Image Processing | 3-1-0-4 | EC301 | ||
| EC314 | Robotics and Automation | 3-1-2-6 | EC207 | ||
| Year 4 | Semester 7 | EC401 | Advanced Power Systems | 3-1-0-4 | EC302 |
| EC402 | Research Methodology | 2-0-0-2 | - | ||
| EC403 | Mini Project I | 2-0-2-4 | - | ||
| EC404 | Capstone Project I | 2-0-2-4 | - | ||
| EC405 | Elective I (AI/ML) | 3-1-0-4 | EC308 | ||
| EC406 | Elective II (Embedded Systems) | 3-1-0-4 | EC303 | ||
| EC407 | Elective III (Control Systems) | 3-1-0-4 | EC304 | ||
| Year 4 | Semester 8 | EC408 | Advanced Capstone Project II | 2-0-2-4 | EC404 |
| EC409 | Professional Ethics and Sustainability | 2-0-0-2 | - | ||
| EC410 | Mini Project II | 2-0-2-4 | - | ||
| EC411 | Elective IV (Power Electronics) | 3-1-0-4 | EC206 | ||
| EC412 | Elective V (Robotics) | 3-1-0-4 | EC314 | ||
| EC413 | Elective VI (Signal Processing) | 3-1-0-4 | EC301 | ||
| EC414 | Elective VII (VLSI Design) | 3-1-0-4 | EC311 |
Detailed Departmental Elective Courses
- Digital Signal Processing: This course covers discrete-time signal processing techniques, including filtering, transform methods, and digital filter design. Students learn to implement these concepts using MATLAB and Python for applications in audio/video systems, biomedical engineering, and telecommunications.
- Power Generation and Distribution: This course explores the principles of power generation from various sources, including fossil fuels, nuclear, hydroelectric, and renewable energy. It also covers the design and operation of transmission and distribution systems to ensure reliable electricity supply.
- Embedded Systems: Students study embedded system architecture, real-time operating systems, microcontroller programming, and hardware-software co-design. Projects include designing smart home automation systems and IoT devices.
- Control System Design: This course introduces classical and modern control techniques for designing stable and efficient feedback control systems. Topics include state-space representation, PID controllers, root locus analysis, and frequency response methods.
- Antenna Theory: Students explore the fundamentals of electromagnetic wave propagation and antenna design. The course covers radiation patterns, impedance matching, array configurations, and practical applications in wireless communication systems.
- Optoelectronics: This elective delves into optoelectronic devices such as lasers, photodiodes, LEDs, and fiber optic components. Applications include optical communication networks, sensors, and medical imaging technologies.
- Industrial Automation: The course focuses on automation technologies used in manufacturing environments, including PLC programming, SCADA systems, sensor integration, and robotic control. Students work on real-world projects in collaboration with industry partners.
- Artificial Intelligence and Machine Learning: This advanced elective introduces students to AI algorithms, neural networks, deep learning frameworks, and their applications in electrical engineering domains like predictive maintenance, smart grids, and robotics.
- Renewable Energy Systems: Students examine solar, wind, hydro, and geothermal energy systems. The course covers system design, energy storage solutions, grid integration challenges, and environmental impact assessments.
- Wireless Communication: This course covers modulation techniques, multiple access methods, channel coding, and wireless network protocols. Practical sessions involve setting up and testing wireless communication systems using software-defined radios (SDRs).
- VLSI Design: Students learn the design process of very large-scale integration circuits, covering CMOS technology, logic synthesis, layout design, and testing methodologies. Projects include designing custom ICs for specific applications.
- Smart Grid Technologies: This course explores smart grid components such as smart meters, demand response systems, and energy management platforms. Students study how these technologies enhance grid reliability, efficiency, and integration of renewable sources.
- Image Processing: The course teaches digital image processing techniques for enhancement, compression, segmentation, and feature extraction. Applications include medical imaging, surveillance systems, and computer vision in robotics.
- Robotics and Automation: This elective covers robot kinematics, dynamics, control systems, and sensor integration. Students build and program robots for various tasks, from industrial automation to search-and-rescue missions.
Project-Based Learning Philosophy
The Bachelor of Electrical Engineering program at Iasscom Fortune Institute of Technology places significant emphasis on project-based learning (PBL). PBL is integrated throughout the curriculum as a pedagogical approach to foster creativity, innovation, and practical problem-solving skills.
Mini Projects
Mini projects are conducted during the first two years of the program. Each student works on a small-scale project related to core subjects, such as designing a simple electronic circuit or simulating power systems using software tools. These projects help students apply theoretical knowledge in real-world scenarios.
Final-Year Thesis/Capstone Project
The final-year capstone project is the most significant component of the program. Students work on an advanced, industry-relevant problem under the supervision of a faculty mentor. The project involves extensive research, experimentation, and documentation. Students present their findings at an annual showcase event open to faculty, industry partners, and fellow students.
Project Selection and Mentorship
Students can choose their projects based on interest and career goals, or they may be assigned projects aligned with ongoing research initiatives led by faculty members. Each student is paired with a mentor who guides them through the research process, provides feedback, and ensures timely completion of the project.
Evaluation Criteria
Projects are evaluated based on several criteria including innovation, technical depth, presentation quality, documentation, teamwork, and real-world applicability. A panel of faculty members and industry experts assesses each project, providing constructive feedback for improvement.