Collegese

Welcome to Collegese! Sign in →

Collegese
  • Colleges
  • Courses
  • Exams
  • Scholarships
  • Blog

Search colleges and courses

Search and navigate to colleges and courses

Start your journey

Ready to find your dream college?

Join thousands of students making smarter education decisions.

Watch How It WorksGet Started

Discover

Browse & filter colleges

Compare

Side-by-side analysis

Explore

Detailed course info

Collegese

India's education marketplace helping students discover the right colleges, compare courses, and build careers they deserve.

© 2026 Collegese. All rights reserved. A product of Nxthub Consulting Pvt. Ltd.

Apply

Scholarships & exams

support@collegese.com
+91 88943 57155
Pune, Maharashtra, India

Duration

4 Years

Bachelor of Technology in Engineering

Mahapurusha Srimanta Sankaradeva Viswavidyalaya Nagaon
Duration
4 Years
Engineering UG OFFLINE

Duration

4 Years

Bachelor of Technology in Engineering

Mahapurusha Srimanta Sankaradeva Viswavidyalaya Nagaon
Duration
Apply

Fees

₹2,50,000

Placement

92.0%

Avg Package

₹4,50,000

Highest Package

₹8,00,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Engineering
UG
OFFLINE

Fees

₹2,50,000

Placement

92.0%

Avg Package

₹4,50,000

Highest Package

₹8,00,000

Seats

300

Students

1,200

ApplyCollege

Seats

300

Students

1,200

Curriculum

Comprehensive Course Structure

The curriculum at Mahapurusha Srimanta Sankaradeva Viswavidyalaya Nagaon is meticulously designed to provide students with a robust foundation in engineering principles while allowing flexibility for specialization. The program spans eight semesters, with each semester carrying a specific set of core courses, departmental electives, science electives, and laboratory sessions.

SemesterCourse CodeCourse TitleCredits (L-T-P-C)Prerequisites
1ENG101Engineering Mathematics I3-1-0-4-
1ENG102Physics for Engineering3-1-0-4-
1ENG103Chemistry for Engineers3-1-0-4-
1ENG104Basic Electrical Engineering3-1-0-4-
1ENG105Engineering Drawing & Computer Graphics2-0-2-3-
1ENG106Communication Skills2-0-0-2-
1ENG107Workshop Practice0-0-2-2-
2ENG201Engineering Mathematics II3-1-0-4ENG101
2ENG202Thermodynamics3-1-0-4ENG102
2ENG203Materials Science3-1-0-4ENG103
2ENG204Digital Electronics3-1-0-4ENG104
2ENG205Engineering Mechanics3-1-0-4-
2ENG206Introduction to Programming2-0-2-3-
2ENG207Lab Session: Basic Electronics0-0-2-2ENG104
3ENG301Probability & Statistics3-1-0-4ENG201
3ENG302Mechanics of Solids3-1-0-4ENG205
3ENG303Fluid Mechanics3-1-0-4ENG202
3ENG304Signals & Systems3-1-0-4ENG201
3ENG305Electromagnetic Fields3-1-0-4ENG204
3ENG306Data Structures & Algorithms2-0-2-3ENG206
3ENG307Lab Session: Signals & Systems0-0-2-2ENG304
4ENG401Control Systems3-1-0-4ENG304
4ENG402Machine Design3-1-0-4ENG302
4ENG403Heat Transfer3-1-0-4ENG202
4ENG404Computer Networks3-1-0-4ENG304
4ENG405Embedded Systems3-1-0-4ENG204
4ENG406Software Engineering2-0-2-3ENG306
4ENG407Lab Session: Embedded Systems0-0-2-2ENG405
5ENG501Advanced Mathematics for Engineering3-1-0-4ENG201
5ENG502Operations Research3-1-0-4ENG301
5ENG503Design of Experiments3-1-0-4ENG301
5ENG504Artificial Intelligence3-1-0-4ENG306
5ENG505Cybersecurity Fundamentals3-1-0-4ENG404
5ENG506Industrial Management2-0-0-2-
5ENG507Lab Session: AI & ML0-0-2-2ENG504
6ENG601Advanced Control Systems3-1-0-4ENG401
6ENG602Renewable Energy Systems3-1-0-4ENG202
6ENG603Project Management3-1-0-4ENG506
6ENG604Advanced Machine Learning3-1-0-4ENG504
6ENG605Quantitative Finance3-1-0-4ENG301
6ENG606Research Methodology2-0-0-2-
6ENG607Lab Session: Advanced ML0-0-2-2ENG604
7ENG701Capstone Project I3-0-0-3ENG504, ENG604
7ENG702Advanced Biomedical Engineering3-1-0-4ENG202
7ENG703Smart Grid Technologies3-1-0-4ENG204
7ENG704Internet of Things (IoT)3-1-0-4ENG404
7ENG705Quantum Computing3-1-0-4ENG304
7ENG706Business Analytics2-0-0-2ENG301
7ENG707Lab Session: IoT & Quantum0-0-2-2ENG704, ENG705
8ENG801Capstone Project II3-0-0-3ENG701
8ENG802Entrepreneurship & Innovation2-0-0-2-
8ENG803Sustainable Engineering Practices3-1-0-4-
8ENG804Final Year Research Thesis2-0-0-2ENG606
8ENG805Industry Internship0-0-4-4-
8ENG806Professional Ethics & Social Responsibility2-0-0-2-
8ENG807Capstone Presentation & Viva Voce0-0-2-2ENG801

Advanced Departmental Elective Courses

Advanced departmental electives are designed to deepen students' understanding of specialized areas within their engineering discipline. These courses are offered by faculty members with deep expertise in emerging fields and industry trends.

One such course is Artificial Intelligence & Machine Learning, which delves into neural networks, deep learning frameworks, natural language processing, computer vision, reinforcement learning, and ethical implications of AI systems. Students learn to implement algorithms using Python, TensorFlow, and PyTorch. This course prepares students for roles in data science teams at leading tech companies.

Another key elective is Cybersecurity Fundamentals, which covers encryption techniques, network security protocols, threat modeling, penetration testing, secure coding practices, and incident response strategies. The course includes hands-on labs where students simulate real-world attacks and defend against them using tools like Wireshark, Nmap, and Metasploit.

Renewable Energy Systems explores solar photovoltaic systems, wind turbines, hydroelectric generation, energy storage technologies, smart grid integration, and carbon footprint reduction strategies. Students work on projects involving solar panel efficiency optimization and wind turbine design using simulation software like MATLAB/Simulink.

The course Advanced Control Systems focuses on modern control theory, state-space representation, optimal control, robust control, and adaptive systems. It includes practical sessions in MATLAB and Simulink for designing and simulating controllers for industrial processes.

Biomedical Engineering bridges engineering principles with medical applications. Students study biomechanics, bioinstrumentation, medical imaging techniques, tissue engineering, and drug delivery systems. Projects involve developing wearable health monitoring devices and analyzing physiological signals using signal processing tools.

Quantitative Finance introduces financial derivatives, risk management, portfolio optimization, stochastic calculus, and computational methods for pricing securities. Students use Python and R to analyze market data and build trading models that can be deployed in real-world scenarios.

Internet of Things (IoT) covers sensor networks, embedded systems programming, wireless communication protocols, cloud integration, and edge computing. Students design IoT applications for smart cities, agriculture, healthcare, and industrial automation using platforms like Arduino, Raspberry Pi, and AWS IoT Core.

Smart Grid Technologies examines power system dynamics, grid stability, renewable energy integration, demand response programs, and microgrids. Students learn to model electrical grids and optimize power distribution through simulation tools like PowerWorld and ETAP.

Quantum Computing explores qubit manipulation, quantum algorithms, error correction codes, and quantum cryptography. Students use IBM Qiskit and Microsoft Azure Quantum to run experiments on real quantum processors and simulate quantum circuits.

Sustainable Engineering Practices emphasizes eco-design principles, life cycle assessment, green manufacturing techniques, circular economy models, and environmental impact analysis. The course includes field visits to sustainable factories and case studies of successful sustainability initiatives in industry.

Project-Based Learning Philosophy

At Mahapurusha Srimanta Sankaradeva Viswavidyalaya Nagaon, project-based learning is central to the educational philosophy. Students engage in both mini-projects during their second year and a final-year capstone project that integrates knowledge from all semesters.

The Mini-Projects begin in the second semester with a focus on applying theoretical concepts to real-world problems. Students form teams of 3-4 members, select topics aligned with their interests, and work under faculty supervision for 6 weeks. Each project must include documentation, a prototype, and a presentation before a panel of experts.

The Final-Year Capstone Project is the culminating experience of the engineering program. Students propose projects related to current industry challenges or emerging technologies. They collaborate closely with faculty mentors, industry partners, and research labs. The project culminates in a detailed thesis, a demonstration, and a final viva voce examination.

Students have multiple avenues to select their projects. They can choose from pre-approved topics suggested by faculty members, propose independent ideas that align with departmental research goals, or collaborate with industry sponsors on applied problems. The selection process is transparent and involves peer reviews, mentor consultations, and project feasibility assessments.