Course Structure Overview
The Bachelor of Electronics and Communication program at Iasscom Fortune Institute of Technology is structured over eight semesters, combining foundational sciences, core engineering principles, departmental electives, and practical applications. This comprehensive curriculum ensures that students develop a well-rounded understanding of electronics and communication technologies while gaining hands-on experience through laboratories and projects.
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|---|
| First Year | Semester 1 | MATH101 | Mathematics I | 3-1-0-4 | - |
| PHY101 | Physics I | 3-1-0-4 | - | ||
| CHM101 | Chemistry I | 3-1-0-4 | - | ||
| First Year | Semester 2 | MATH102 | Mathematics II | 3-1-0-4 | MATH101 |
| PHY102 | Physics II | 3-1-0-4 | PHY101 | ||
| CSE101 | Introduction to Programming | 2-0-2-3 | - | ||
| Second Year | Semester 3 | MATH201 | Mathematics III | 3-1-0-4 | MATH102 |
| ECE201 | Digital Logic Design | 3-1-0-4 | - | ||
| ECE202 | Electronic Devices and Circuits | 3-1-0-4 | - | ||
| ECE203 | Signals and Systems | 3-1-0-4 | MATH201 | ||
| ECE204 | Network Analysis | 3-1-0-4 | - | ||
| ECE205 | Electromagnetic Fields | 3-1-0-4 | MATH201 | ||
| ECE206 | Engineering Graphics | 2-0-2-3 | - | ||
| ECE207 | Electronics Lab I | 0-0-4-2 | - | ||
| Second Year | Semester 4 | MATH202 | Mathematics IV | 3-1-0-4 | MATH201 |
| ECE208 | Microprocessors and Microcontrollers | 3-1-0-4 | - | ||
| ECE209 | Control Systems | 3-1-0-4 | ECE201, ECE203 | ||
| ECE210 | Communication Systems | 3-1-0-4 | ECE203 | ||
| ECE211 | Digital Signal Processing | 3-1-0-4 | ECE203 | ||
| ECE212 | Electronics Lab II | 0-0-4-2 | - | ||
| ECE213 | VLSI Design Lab | 0-0-4-2 | ECE202 | ||
| ECE214 | Mini Project I | 0-0-6-3 | - | ||
| Third Year | Semester 5 | MATH301 | Mathematics V | 3-1-0-4 | MATH202 |
| ECE301 | Embedded Systems | 3-1-0-4 | ECE208, ECE203 | ||
| ECE302 | Wireless Communication | 3-1-0-4 | ECE210 | ||
| ECE303 | Antenna and Wave Propagation | 3-1-0-4 | ECE205 | ||
| ECE304 | Digital Image Processing | 3-1-0-4 | ECE211 | ||
| ECE305 | Optical Communication Systems | 3-1-0-4 | ECE210 | ||
| ECE306 | Communication Lab | 0-0-4-2 | - | ||
| ECE307 | Mini Project II | 0-0-6-3 | - | ||
| Third Year | Semester 6 | MATH302 | Mathematics VI | 3-1-0-4 | MATH301 |
| ECE308 | VLSI Design | 3-1-0-4 | ECE213 | ||
| ECE309 | Computer Networks | 3-1-0-4 | ECE210 | ||
| ECE310 | Signal Processing Lab | 0-0-4-2 | ECE211 | ||
| ECE311 | Embedded Systems Lab | 0-0-4-2 | ECE301 | ||
| ECE312 | Power Electronics | 3-1-0-4 | - | ||
| ECE313 | AI and Machine Learning | 3-1-0-4 | - | ||
| ECE314 | Mini Project III | 0-0-6-3 | - | ||
| Fourth Year | Semester 7 | ECE401 | Advanced Communication Systems | 3-1-0-4 | ECE302 |
| ECE402 | Network Security | 3-1-0-4 | ECE309 | ||
| ECE403 | Robotics and Automation | 3-1-0-4 | ECE209 | ||
| ECE404 | Renewable Energy Systems | 3-1-0-4 | - | ||
| ECE405 | Signal and Image Processing | 3-1-0-4 | ECE304 | ||
| ECE406 | Capstone Project | 0-0-12-6 | - | ||
| ECE407 | Advanced VLSI Design | 3-1-0-4 | ECE308 | ||
| ECE408 | Internship | 0-0-12-6 | - | ||
| Fourth Year | Semester 8 | ECE409 | Final Year Thesis | 0-0-12-6 | - |
| ECE410 | Professional Ethics and Communication | 2-0-0-2 | - | ||
| ECE411 | Research Methodology | 2-0-0-2 | - | ||
| ECE412 | Elective Courses | 3-1-0-4 | - | ||
| ECE413 | Capstone Project Presentation | 0-0-6-3 | ECE406 | ||
| ECE414 | Placement Preparation | 2-0-0-2 | - | ||
| ECE415 | Industrial Visits | 0-0-6-3 | - | ||
| ECE416 | Final Evaluation | 0-0-0-2 | - |
Advanced Departmental Elective Courses
The department offers several advanced elective courses designed to deepen students' understanding of specialized areas within Electronics and Communication Engineering. These courses are tailored to meet the evolving needs of industry and research.
Artificial Intelligence and Machine Learning
This course introduces students to the fundamental concepts of AI and ML, including supervised and unsupervised learning, neural networks, deep learning architectures, and reinforcement learning. Students will implement algorithms using Python and TensorFlow, gaining practical experience in building intelligent systems.
Wireless Communication Systems
The course explores modern wireless communication techniques such as OFDM, MIMO, beamforming, and 5G technologies. It covers both theoretical foundations and practical applications, including mobile network design, channel modeling, and interference management. Students will engage in simulations and lab experiments to reinforce learning.
Embedded Systems Design
This course focuses on designing embedded systems for real-time applications using microcontrollers, DSPs, and FPGAs. Topics include hardware-software co-design, real-time operating systems, sensor integration, and power optimization techniques. Students will develop projects involving IoT devices and robotics.
VLSI Design and Testing
The course delves into the design and testing of very large-scale integrated circuits (VLSI). It covers CMOS technology, logic synthesis, physical design, and testability issues. Students will use CAD tools like Cadence and Synopsys to implement designs and perform simulation and verification tasks.
Digital Image Processing
This course introduces students to techniques used in image acquisition, enhancement, restoration, compression, segmentation, and object recognition. Applications include medical imaging, satellite imagery analysis, and computer vision systems. Students will utilize MATLAB for implementing image processing algorithms.
Network Security Protocols
The course examines security mechanisms in communication networks, including cryptography, authentication, intrusion detection, and secure protocols like SSL/TLS and IPSec. It includes hands-on labs where students implement security measures and analyze vulnerabilities in network systems.
Robotics and Automation
This course covers the fundamentals of robotics, including kinematics, dynamics, control systems, sensor integration, and autonomous navigation. Students will design and build robotic platforms for specific applications, integrating mechanical, electrical, and software components.
Power Electronics and Drives
The course explores power conversion techniques used in renewable energy systems, electric drives, and industrial applications. Topics include rectifiers, inverters, DC-DC converters, and motor control strategies. Students will analyze and design power electronic circuits using simulation software.
Optical Communication Systems
This course covers the principles of optical fiber communication, including transmission media, modulation techniques, amplification, and network topologies. It includes laboratory sessions on designing and testing optical links, providing students with practical insights into modern communication infrastructure.
Signal Processing for Multimedia Applications
The course focuses on applying signal processing techniques to multimedia data such as audio, video, and speech signals. Students will learn about compression standards (MPEG, H.264), streaming protocols, and real-time processing methods. Projects involve developing multimedia applications using DSP libraries.
Project-Based Learning Philosophy
The department strongly emphasizes project-based learning as a core component of the curriculum. This approach ensures that students not only acquire theoretical knowledge but also develop practical skills required for industry readiness. Projects are designed to simulate real-world challenges, encouraging innovation and problem-solving.
Mini Projects
Mini projects are assigned in semesters 4, 5, and 6. These projects typically span 3-4 weeks and involve working in small teams of 3-5 students. The focus is on applying concepts learned in earlier semesters to solve specific engineering problems. Students receive guidance from faculty mentors throughout the project lifecycle.
Final-Year Thesis/Capstone Project
The final-year capstone project is a comprehensive endeavor that allows students to integrate their learning and demonstrate mastery in a chosen area of specialization. Students select a topic relevant to current industry trends or research directions, working closely with a faculty advisor. The project culminates in a written thesis and oral presentation.
Project Selection Process
Students are encouraged to propose project ideas aligned with their interests and career goals. Faculty members review proposals and provide feedback on feasibility, scope, and relevance. Projects can be individual or group-based, depending on complexity and resource requirements. The department maintains a database of approved project topics and faculty expertise areas to assist in matching students with suitable mentors.
Evaluation Criteria
Projects are evaluated based on multiple criteria including technical depth, innovation, presentation quality, teamwork, and adherence to deadlines. Regular progress reports are submitted at predefined intervals, ensuring continuous monitoring and support from faculty advisors. Final evaluations include peer reviews, mentor assessments, and external panel presentations.