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Duration

4 Years

Electrical Engineering

Himalayan University Nahalagun
Duration

Apply

Scholarships & exams

support@collegese.com
+91 88943 57155
Pune, Maharashtra, India
4 Years
Electrical Engineering
UG
OFFLINE

Duration

4 Years

Electrical Engineering

Himalayan University Nahalagun
Duration
4 Years
Electrical Engineering UG OFFLINE

Fees

₹6,00,000

Placement

95.0%

Avg Package

₹6,50,000

Highest Package

₹18,00,000

ApplyCollege
Apply

Fees

₹6,00,000

Placement

95.0%

Avg Package

₹6,50,000

Highest Package

₹18,00,000

Seats

100

Students

300

OverviewAdmissionsCurriculumFeesPlacements

Curriculum

Electrical Engineering Curriculum Overview

The Electrical Engineering curriculum at Himalayan University Nahalagun is designed to provide students with a strong foundation in core principles while offering flexibility through specialized electives and research opportunities. The program spans four years, divided into eight semesters, each building upon the previous one to ensure comprehensive understanding and practical application.

Course Schedule - All Eight Semesters

Semester Course Code Course Title Credit Structure (L-T-P-C) Pre-requisites
1 EE101 Engineering Mathematics I 3-1-0-4 -
1 EE102 Physics for Engineers 3-1-0-4 -
1 EE103 Introduction to Programming 2-1-0-3 -
1 EE104 Basic Electrical Circuits 3-1-0-4 -
1 EE105 Engineering Drawing & Design 2-1-0-3 -
1 EE106 Workshop Practice 2-1-0-3 -
2 EE201 Engineering Mathematics II 3-1-0-4 EE101
2 EE202 Electromagnetic Fields 3-1-0-4 EE102
2 EE203 Digital Logic Design 3-1-0-4 EE104
2 EE204 Signals and Systems 3-1-0-4 EE101
2 EE205 Electrical Machines I 3-1-0-4 EE104
2 EE206 Laboratory Workshop I 2-1-0-3 -
3 EE301 Power Systems Analysis 3-1-0-4 EE205
3 EE302 Control Systems 3-1-0-4 EE204
3 EE303 Communication Systems 3-1-0-4 EE204
3 EE304 Microprocessors and Microcontrollers 3-1-0-4 EE203
3 EE305 Electronics Devices and Circuits 3-1-0-4 EE202
3 EE306 Laboratory Workshop II 2-1-0-3 -
4 EE401 Power Electronics 3-1-0-4 EE305
4 EE402 Advanced Signal Processing 3-1-0-4 EE303
4 EE403 Industrial Automation 3-1-0-4 EE302
4 EE404 Renewable Energy Systems 3-1-0-4 EE301
4 EE405 Embedded Systems Design 3-1-0-4 EE304
4 EE406 Laboratory Workshop III 2-1-0-3 -
5 EE501 Power System Protection 3-1-0-4 EE401
5 EE502 Wireless Communication 3-1-0-4 EE303
5 EE503 Machine Learning for Engineers 3-1-0-4 EE204
5 EE504 Advanced Control Systems 3-1-0-4 EE302
5 EE505 Cybersecurity in Electronics 3-1-0-4 EE305
5 EE506 Project Lab I 2-1-0-3 -
6 EE601 Smart Grid Technologies 3-1-0-4 EE501
6 EE602 RF and Microwave Engineering 3-1-0-4 EE202
6 EE603 Robotics and Automation 3-1-0-4 EE504
6 EE604 VLSI Design 3-1-0-4 EE505
6 EE605 Advanced Embedded Systems 3-1-0-4 EE505
6 EE606 Project Lab II 2-1-0-3 -
7 EE701 Capstone Project I 4-2-0-6 EE501, EE504
7 EE702 Special Topics in Electrical Engineering 3-1-0-4 -
7 EE703 Research Methodology 2-1-0-3 -
8 EE801 Capstone Project II 4-2-0-6 EE701
8 EE802 Professional Practices and Ethics 2-1-0-3 -
8 EE803 Industrial Internship 2-1-0-3 -

Advanced Departmental Electives

Advanced elective courses offer students opportunities to explore specialized areas within electrical engineering and tailor their education according to their interests and career aspirations. Below are detailed descriptions of several key advanced electives:

1. Power System Protection

This course delves into the principles and practices of protecting power systems against faults and disturbances. Students learn about protective relaying, fault analysis, and system design for reliability and security. The course includes both theoretical study and hands-on simulation using industry-standard software.

2. Wireless Communication

Students gain an in-depth understanding of wireless communication systems including modulation techniques, channel coding, and multiple access protocols. Practical sessions involve working with RF equipment and simulating wireless networks using MATLAB and Simulink.

3. Machine Learning for Engineers

This course bridges the gap between electrical engineering fundamentals and modern machine learning techniques. Students learn how to apply ML algorithms in signal processing, control systems, and power system optimization. The course includes real-world case studies and project-based learning.

4. Advanced Control Systems

Building upon basic control theory, this course explores advanced topics such as state-space representation, optimal control, and robust control design. Students engage in complex modeling and simulation projects involving industrial applications.

5. Cybersecurity in Electronics

Focused on securing electronic devices and systems from cyber threats, this course covers hardware-level security, embedded system vulnerabilities, and secure communication protocols. Practical labs involve penetration testing and implementing secure firmware solutions.

6. Smart Grid Technologies

This course examines the evolution of smart grids and their integration with renewable energy sources. Topics include grid automation, demand response systems, and energy management platforms. Students work on simulation projects using real-world datasets.

7. RF and Microwave Engineering

Students explore the design and analysis of high-frequency circuits and systems used in wireless communications and radar applications. The course includes both theoretical concepts and practical lab sessions involving microwave measurement techniques and component design.

8. Robotics and Automation

This elective combines mechanical engineering principles with electrical controls to build autonomous robotic systems. Students learn about sensor integration, motor control, path planning, and AI-based decision-making in robotics.

9. VLSI Design

The course focuses on designing integrated circuits using very-large-scale integration (VLSI) techniques. Students learn about logic synthesis, layout design, and verification methods. The course includes hands-on experience with CAD tools like Cadence and Synopsys.

10. Advanced Embedded Systems

This course covers advanced topics in embedded system development including real-time operating systems, embedded networking, and microcontroller architecture. Students develop complex embedded applications using C/C++ and ARM-based platforms.

Project-Based Learning Philosophy

Himalayan University Nahalagun strongly emphasizes project-based learning as a core component of its Electrical Engineering curriculum. This approach integrates theoretical knowledge with practical application, fostering innovation, problem-solving skills, and collaborative work environments.

Mini-Projects Structure

Throughout the first four semesters, students undertake several mini-projects that are typically completed in groups of 3-5 members. These projects focus on solving real-world problems using basic electrical engineering principles. Mini-projects are designed to enhance understanding and encourage creativity while providing foundational experience for larger capstone efforts.

Final-Year Thesis/Capstone Project

The final-year capstone project is a significant milestone in the program. Students select a research topic under the guidance of a faculty mentor and work on an original investigation or design project over two semesters. The project must demonstrate advanced technical proficiency, innovative thinking, and effective communication of results.

Project Selection Process

Students can propose their own project ideas or choose from a list of pre-approved topics suggested by faculty members. The selection process involves submitting a proposal, attending an interview with potential mentors, and final approval from the departmental advisory committee. Projects are evaluated based on feasibility, novelty, relevance to industry trends, and alignment with student interests.

Evaluation Criteria

Projects are assessed using multiple criteria including technical depth, innovation, teamwork, presentation quality, and final deliverables. Regular progress reports and milestone reviews ensure that projects stay on track and meet academic standards. Students receive continuous feedback from faculty advisors throughout the project lifecycle.

Seats

100

Students

300