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Fees
₹8,00,000
Placement
94.5%
Avg Package
₹7,50,000
Highest Package
₹18,00,000
Fees
₹8,00,000
Placement
94.5%
Avg Package
₹7,50,000
Highest Package
₹18,00,000
Seats
150
Students
1,200
Seats
150
Students
1,200
The Electrical Engineering program at Future University Bareilly is structured over eight semesters, providing a balanced progression from foundational sciences to advanced engineering disciplines.
| Semester | Course Code | Course Title | Credits (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | MA101 | Mathematics I | 3-1-0-4 | - |
| 1 | PH101 | Physics I | 3-1-0-4 | - |
| 1 | EC101 | Introduction to Electrical Engineering | 2-0-0-2 | - |
| 1 | CS101 | Computer Programming | 2-0-2-4 | - |
| 1 | HS101 | English for Communication | 2-0-0-2 | - |
| 1 | EE101 | Basic Electrical Circuits | 3-1-0-4 | - |
| 1 | ME101 | Engineering Mechanics | 3-1-0-4 | - |
| 2 | MA201 | Mathematics II | 3-1-0-4 | MA101 |
| 2 | PH201 | Physics II | 3-1-0-4 | PH101 |
| 2 | EE201 | Circuit Analysis | 3-1-0-4 | EE101 |
| 2 | EE202 | Digital Logic Design | 3-1-0-4 | EE101 |
| 2 | CS201 | Data Structures and Algorithms | 2-0-2-4 | CS101 |
| 2 | EE203 | Electromagnetic Fields | 3-1-0-4 | PH201 |
| 2 | HS201 | Communication Skills | 2-0-0-2 | - |
| 3 | MA301 | Mathematics III | 3-1-0-4 | MA201 |
| 3 | EE301 | Signals and Systems | 3-1-0-4 | EE201 |
| 3 | EE302 | Analog Electronics | 3-1-0-4 | EE201 |
| 3 | EE303 | Power Electronics | 3-1-0-4 | EE201 |
| 3 | EE304 | Control Systems | 3-1-0-4 | EE201 |
| 3 | CS301 | Object-Oriented Programming | 2-0-2-4 | CS101 |
| 3 | EE305 | Electrical Machines | 3-1-0-4 | EE201 |
| 3 | EE306 | Microprocessors and Microcontrollers | 3-1-0-4 | EE202 |
| 4 | MA401 | Mathematics IV | 3-1-0-4 | MA301 |
| 4 | EE401 | Digital Signal Processing | 3-1-0-4 | EE301 |
| 4 | EE402 | Communication Systems | 3-1-0-4 | EE301 |
| 4 | EE403 | Power System Analysis | 3-1-0-4 | EE305 |
| 4 | EE404 | Embedded Systems | 3-1-0-4 | EE306 |
| 4 | EE405 | Industrial Training | 0-0-2-2 | - |
| 4 | EE406 | Project I | 0-0-0-3 | - |
| 5 | EE501 | Advanced Control Systems | 3-1-0-4 | EE404 |
| 5 | EE502 | Renewable Energy Systems | 3-1-0-4 | EE305 |
| 5 | EE503 | VLSI Design | 3-1-0-4 | EE302 |
| 5 | EE504 | Smart Grid Technologies | 3-1-0-4 | EE403 |
| 5 | EE505 | Signal Processing Applications | 3-1-0-4 | EE401 |
| 5 | EE506 | Instrumentation and Measurement | 3-1-0-4 | EE301 |
| 6 | EE601 | AI for Engineering Applications | 3-1-0-4 | EE505 |
| 6 | EE602 | Advanced Embedded Systems | 3-1-0-4 | EE404 |
| 6 | EE603 | Power System Protection | 3-1-0-4 | EE403 |
| 6 | EE604 | Robotics and Automation | 3-1-0-4 | EE501 |
| 6 | EE605 | Capstone Project I | 0-0-0-4 | - |
| 7 | EE701 | Advanced Power Electronics | 3-1-0-4 | EE303 |
| 7 | EE702 | Research Methodology | 2-0-0-2 | - |
| 7 | EE703 | Capstone Project II | 0-0-0-6 | - |
| 7 | EE704 | Industrial Internship | 0-0-2-2 | - |
| 8 | EE801 | Thesis Proposal | 0-0-0-3 | - |
| 8 | EE802 | Final Thesis | 0-0-0-9 | - |
| 8 | EE803 | Professional Ethics and Social Responsibility | 2-0-0-2 | - |
The department offers a wide range of advanced elective courses designed to deepen students' understanding and enhance their specialization skills.
AI for Engineering Applications: This course explores the integration of artificial intelligence techniques with traditional engineering domains. Students learn to apply machine learning algorithms, neural networks, and deep learning models to solve complex engineering problems in areas such as signal processing, control systems, and robotics.
Advanced Power Electronics: Focusing on modern power conversion techniques, this course covers advanced topologies for DC-DC converters, AC-DC rectifiers, inverters, and other power electronic devices. Emphasis is placed on efficiency optimization, thermal management, and system integration in high-power applications.
Renewable Energy Systems: Students study various renewable energy sources including solar photovoltaic systems, wind turbines, hydroelectric plants, and geothermal energy. The course includes practical aspects such as grid integration, energy storage solutions, and policy frameworks supporting sustainable energy development.
VLSI Design: This advanced course introduces students to the principles of Very Large Scale Integration (VLSI) design, covering digital IC design, layout techniques, and CAD tools. Topics include logic synthesis, timing analysis, and physical implementation of integrated circuits.
Smart Grid Technologies: This course examines smart grid architecture, communication protocols, and intelligent control systems for modern power networks. Students explore topics such as demand response, distributed generation, and cyber security in energy systems.
Advanced Control Systems: Building upon foundational control theory, this course delves into advanced control strategies including robust control, adaptive control, and optimal control. Practical applications are explored through case studies involving aerospace, automotive, and industrial systems.
Signal Processing Applications: This elective focuses on real-world applications of signal processing techniques in audio, image, biomedical, and communication domains. Students gain hands-on experience using MATLAB, Python, and other industry-standard tools for processing and analyzing signals.
Instrumentation and Measurement: The course covers precision measurement techniques and instrumentation design for various physical quantities such as temperature, pressure, flow rate, and electrical parameters. It includes laboratory sessions on sensor integration, calibration, and data acquisition systems.
Robotics and Automation: Students are introduced to robotics fundamentals including kinematics, dynamics, control systems, and perception technologies. The course emphasizes practical implementation through robotic platforms and simulation environments.
Power System Protection: This course provides an in-depth understanding of protective relays, fault analysis, and protection coordination in power systems. Students learn to design and implement protection schemes for different types of electrical networks and components.
Research Methodology: Designed to prepare students for advanced research, this course covers scientific methods, hypothesis testing, data collection, and statistical analysis techniques commonly used in engineering research.
The Electrical Engineering program at Future University Bareilly places a strong emphasis on project-based learning as a core component of the educational experience. Projects are designed to simulate real-world challenges, encouraging students to apply theoretical knowledge to practical problems while developing critical thinking and problem-solving skills.
Mini-projects are integrated throughout the curriculum, starting from the first semester with basic circuit design exercises and progressing to complex system integration tasks in later years. These projects typically involve small teams of 3-5 students working under faculty supervision.
The final-year thesis/capstone project is a significant milestone where students select a research topic aligned with their interests or industry needs. They work closely with a faculty mentor, conduct literature reviews, perform experiments, analyze results, and present findings in both written and oral formats.
Project selection is guided by student preferences, faculty expertise, and current industry trends. Students are encouraged to propose innovative ideas that address societal or technological challenges. Faculty members play a crucial role in guiding students through the research process, ensuring they gain valuable experience in project management, technical writing, and presentation skills.
