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Pune, Maharashtra, India

Duration

4 Years

Electrical

Bishamber Sahai Institute Of Technology
Duration
4 Years
Electrical UG OFFLINE

Duration

4 Years

Electrical

Bishamber Sahai Institute Of Technology
Duration
Apply

Fees

₹12,00,000

Placement

93.5%

Avg Package

₹4,20,000

Highest Package

₹8,50,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Electrical
UG
OFFLINE

Fees

₹12,00,000

Placement

93.5%

Avg Package

₹4,20,000

Highest Package

₹8,50,000

Seats

150

Students

300

ApplyCollege

Seats

150

Students

300

Curriculum

Comprehensive Course Structure

Semester Course Code Course Title Credit Structure (L-T-P-C) Pre-requisites
1 EE101 Mathematics I 3-1-0-4 -
1 EE102 Physics for Engineers 3-1-0-4 -
1 EE103 Basic Electrical Engineering 3-1-0-4 -
1 EE104 Engineering Graphics & Design 2-0-0-2 -
1 EE105 Programming & Problem Solving 2-0-2-3 -
1 EE106 Workshop Practice 0-0-2-1 -
2 EE201 Mathematics II 3-1-0-4 EE101
2 EE202 Chemistry for Engineers 3-1-0-4 -
2 EE203 Circuit Analysis 3-1-0-4 EE103
2 EE204 Electromagnetic Fields 3-1-0-4 EE102
2 EE205 Signals & Systems 3-1-0-4 EE201
2 EE206 Digital Logic Design 3-1-0-4 -
3 EE301 Mathematics III 3-1-0-4 EE201
3 EE302 Electronics Devices & Circuits 3-1-0-4 EE203
3 EE303 Power System Analysis 3-1-0-4 EE203
3 EE304 Control Systems 3-1-0-4 EE205
3 EE305 Microprocessors & Microcontrollers 3-1-0-4 EE206
3 EE306 Communication Systems 3-1-0-4 EE205
4 EE401 Mathematics IV 3-1-0-4 EE301
4 EE402 Power Electronics 3-1-0-4 EE302
4 EE403 Electrical Machines 3-1-0-4 EE302
4 EE404 Digital Signal Processing 3-1-0-4 EE205
4 EE405 Embedded Systems 3-1-0-4 EE305
4 EE406 Renewable Energy Systems 3-1-0-4 EE303
5 EE501 Advanced Control Systems 3-1-0-4 EE304
5 EE502 Power System Protection 3-1-0-4 EE303
5 EE503 Industrial Electronics 3-1-0-4 EE402
5 EE504 Wireless Communication 3-1-0-4 EE306
5 EE505 VLSI Design 3-1-0-4 EE305
5 EE506 Biomedical Instrumentation 3-1-0-4 EE205
6 EE601 Smart Grid Technologies 3-1-0-4 EE502
6 EE602 Data Analytics for Electrical Systems 3-1-0-4 EE404
6 EE603 Research Methodology 2-0-0-2 -
6 EE604 Project Management 2-0-0-2 -
6 EE605 Elective I 3-1-0-4 -
6 EE606 Elective II 3-1-0-4 -
7 EE701 Mini Project I 0-0-6-3 -
7 EE702 Mini Project II 0-0-6-3 -
7 EE703 Elective III 3-1-0-4 -
7 EE704 Elective IV 3-1-0-4 -
8 EE801 Final Year Thesis/Capstone Project 0-0-12-6 -

Detailed Course Descriptions for Advanced Departmental Electives

Advanced departmental electives in the Electrical program at Bishamber Sahai Institute Of Technology are designed to provide students with specialized knowledge and skills relevant to current industry trends. These courses go beyond standard curriculum offerings, offering deep dives into emerging fields that drive innovation.

Power Electronics

This course explores the design and application of power electronic converters used in various industries such as renewable energy systems, electric vehicles, and industrial automation. Students learn about different topologies including rectifiers, inverters, DC-DC converters, and AC-AC converters. The course emphasizes practical applications through laboratory sessions where students build and test actual power conversion circuits.

Smart Grid Technologies

As the traditional power grid evolves into a more intelligent and responsive system, this course delves into smart grid concepts including advanced metering infrastructure, demand response systems, and integration of renewable energy sources. Students are introduced to topics like grid stability analysis, cyber security in power systems, and real-time monitoring using IoT technologies.

Renewable Energy Systems

This course provides a comprehensive overview of renewable energy technologies including solar photovoltaic systems, wind turbines, hydroelectric plants, and geothermal systems. Students learn about system design, performance evaluation, and economic analysis of renewable energy projects. Practical components involve simulations and case studies of successful installations in India and abroad.

Digital Signal Processing

Digital signal processing is essential for modern communication systems, audio/video processing, and biomedical applications. This course covers discrete-time signals and systems, z-transforms, Fast Fourier Transform (FFT), and filter design techniques. Students gain hands-on experience with software tools like MATLAB and Python for implementing DSP algorithms.

Control Systems

This course builds upon earlier concepts in control theory and introduces advanced topics such as state-space representation, robust control, and nonlinear systems. Students learn to model complex systems, design controllers using classical and modern methods, and analyze stability and performance characteristics of feedback control systems.

Embedded Systems

Embedded systems are at the heart of modern devices ranging from smartphones to industrial machinery. This course covers microcontroller architectures, real-time operating systems, embedded software development, and hardware-software co-design. Students work on projects involving sensor integration, data acquisition, and control applications using platforms like Arduino and Raspberry Pi.

Biomedical Instrumentation

This interdisciplinary course bridges electrical engineering with medical sciences. Students learn about bioelectricity, medical imaging techniques, and instrumentation for physiological monitoring. The curriculum includes hands-on labs where students design and test biomedical devices such as ECG monitors, pulse oximeters, and pacemakers.

VLSI Design

Very Large Scale Integration (VLSI) is critical in the development of integrated circuits used in modern electronics. This course covers semiconductor physics, circuit design, layout techniques, and testing methodologies. Students gain experience with CAD tools like Cadence and Synopsys, learning how to design custom chips for specific applications.

Wireless Communication

With the proliferation of mobile devices and IoT, wireless communication has become a cornerstone of modern technology. This course covers modulation techniques, multiple access schemes, error correction codes, and network protocols. Students explore current standards like 5G and future technologies such as satellite communications.

Data Analytics for Electrical Systems

This emerging field combines data science with electrical engineering to extract insights from large datasets in power systems, communication networks, and control systems. Topics include statistical modeling, machine learning algorithms, predictive analytics, and visualization techniques. Students work on real-world problems using tools like Python, R, and TensorFlow.

Project-Based Learning Framework

The Electrical program at Bishamber Sahai Institute Of Technology emphasizes project-based learning as a core component of student development. This approach fosters creativity, critical thinking, and practical application of theoretical knowledge.

The project-based learning framework is structured across three phases: Mini Projects, Major Projects, and Final-Year Thesis/Capstone Project.

Mini Projects

Mini projects are introduced in the seventh semester, allowing students to apply concepts learned in earlier semesters. These projects typically last 3-4 months and involve small teams of 2-4 students working under faculty supervision. Students select topics aligned with their interests or emerging trends in electrical engineering.

Major Projects

In the eighth semester, students engage in more substantial projects that often involve collaboration with industry partners or research institutions. These projects require advanced skills in system design, implementation, testing, and documentation. Students are expected to present their findings at departmental symposiums and potentially publish papers in journals.

Final-Year Thesis/Capstone Project

The final-year project represents the culmination of a student's academic journey. It involves extensive research, design, and development work culminating in a comprehensive report and presentation. Students are encouraged to pursue innovative ideas that address real-world challenges or contribute to ongoing research efforts.

Project Selection and Mentorship

Students select their projects based on faculty availability, research interests, and alignment with industry needs. Each project is assigned a faculty mentor who provides guidance throughout the process. Regular meetings, progress reports, and milestone reviews ensure timely completion and quality outcomes.