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Pune, Maharashtra, India

Duration

4 Years

Bachelor of Technology in Engineering

Maganbhai Adenwala Mahagujarat University, Nadiad
Duration
4 Years
Engineering UG OFFLINE

Duration

4 Years

Bachelor of Technology in Engineering

Maganbhai Adenwala Mahagujarat University, Nadiad
Duration
Apply

Fees

₹1,30,000

Placement

95.0%

Avg Package

₹5,20,000

Highest Package

₹9,50,000

OverviewAdmissionsCurriculumFeesPlacements
4 Years
Engineering
UG
OFFLINE

Fees

₹1,30,000

Placement

95.0%

Avg Package

₹5,20,000

Highest Package

₹9,50,000

Seats

1,200

Students

2,500

ApplyCollege

Seats

1,200

Students

2,500

Curriculum

Curriculum Overview

The curriculum at Maganbhai Adenwala Mahagujarat University Nadiad is meticulously designed to align with global standards while incorporating local industry needs. It ensures a balanced progression from foundational knowledge to advanced specialization, enabling students to develop both technical proficiency and critical thinking skills.

Each semester is structured around core subjects, departmental electives, science electives, and laboratory sessions. The curriculum emphasizes not only academic excellence but also practical application through real-world projects and industry exposure. This holistic approach prepares graduates for immediate contribution in their chosen fields.

Course Structure

The engineering program spans eight semesters, with each semester comprising core courses, departmental electives, science electives, and laboratory sessions. The following table outlines the course structure:

SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
1ENG101Engineering Mathematics I3-1-0-4-
1PHYS101Physics for Engineers3-1-0-4-
1CHEM101Chemistry for Engineering3-1-0-4-
1ES101Engineering Graphics2-1-0-3-
1ECE101Basic Electrical Circuits3-1-0-4-
2ENG201Engineering Mathematics II3-1-0-4ENG101
2MATH201Statistics and Probability3-1-0-4-
2PHYS201Thermodynamics3-1-0-4PHYS101
2CIV201Mechanics of Materials3-1-0-4-
2ECE201Electrical Circuits and Networks3-1-0-4ECE101
3ENG301Signals and Systems3-1-0-4ENG201
3MATH301Differential Equations3-1-0-4ENG201
3CIV301Structural Analysis3-1-0-4CIV201
3ECE301Control Systems3-1-0-4ECE201
3MECH301Machine Design3-1-0-4-
4ENG401Probability and Statistics for Engineers3-1-0-4MATH201
4CIV401Transportation Engineering3-1-0-4CIV301
4ECE401Digital Signal Processing3-1-0-4ENG301
4MECH401Thermal Engineering3-1-0-4-
4CS401Data Structures and Algorithms3-1-0-4-
5CS501Artificial Intelligence3-1-0-4CS401
5MECH501Robotics and Automation3-1-0-4MECH401
5CIV501Environmental Engineering3-1-0-4CIV401
5ECE501Wireless Communication3-1-0-4ECE401
6CS601Machine Learning3-1-0-4CS501
6MECH601Manufacturing Technology3-1-0-4-
6CIV601Construction Management3-1-0-4-
6ECE601Embedded Systems3-1-0-4ECE501
7CS701Big Data Analytics3-1-0-4CS601
7MECH701Advanced Thermodynamics3-1-0-4-
7CIV701Geotechnical Engineering3-1-0-4-
7ECE701VLSI Design3-1-0-4ECE601
8CS801Capstone Project2-0-6-8-
8MECH801Final Year Thesis2-0-6-8-
8CIV801Project Management3-1-0-4-
8ECE801Internet of Things3-1-0-4ECE701

Advanced Departmental Electives

The advanced departmental elective courses provide students with specialized knowledge and skills relevant to their chosen career paths. These courses are taught by faculty members who are experts in their respective fields.

  • Machine Learning (CS601): This course covers supervised and unsupervised learning algorithms, neural networks, deep learning frameworks, and applications in computer vision and natural language processing. Students will work on projects involving real datasets to apply theoretical concepts practically.
  • Big Data Analytics (CS701): Students learn about data mining techniques, Hadoop ecosystems, Spark programming, and real-time analytics for business intelligence. The course includes hands-on labs using industry-standard tools such as Apache Spark and Hadoop.
  • Robotics and Automation (MECH501): The course explores robot kinematics, control systems, sensor integration, and automation in manufacturing environments. Students will build and program robots to perform specific tasks, gaining practical experience in robotics engineering.
  • VLSI Design (ECE701): This elective introduces students to digital design principles, ASIC development, FPGA implementation, and hardware description languages like Verilog and VHDL. Projects involve designing and simulating integrated circuits using industry-standard tools.
  • Environmental Engineering (CIV501): Focused on pollution control, waste management, water treatment systems, and sustainable engineering practices for environmental impact mitigation. Students will analyze case studies and propose solutions to environmental challenges.
  • Digital Signal Processing (ECE401): Covers discrete-time signal processing techniques, filter design, frequency domain analysis, and DSP applications in audio and image processing. Labs involve implementing algorithms using MATLAB and Python.
  • Advanced Thermodynamics (MECH701): Students study thermodynamic cycles, phase equilibrium, energy conversion systems, and advanced topics in heat transfer. The course includes laboratory experiments to validate theoretical concepts.
  • Artificial Intelligence (CS501): This course delves into AI fundamentals, problem-solving techniques, knowledge representation, and agent-based systems. Students will develop intelligent agents and explore applications in game theory and robotics.
  • Construction Management (CIV601): Provides insights into project planning, resource allocation, risk management, and quality control in construction projects. Case studies from real-world construction sites enhance learning outcomes.
  • Embedded Systems (ECE601): Students explore microcontroller architectures, embedded programming, real-time operating systems, and IoT device development. Labs involve building embedded systems using Arduino and Raspberry Pi platforms.

Project-Based Learning Philosophy

The department strongly advocates for a project-based learning approach that integrates theoretical knowledge with practical skills. From the first year, students engage in mini-projects that reinforce classroom learning through hands-on experimentation.

Mini-projects in early semesters focus on basic design tasks such as circuit simulation, simple mechanical designs, or data analysis using spreadsheets and programming tools. As students progress, the complexity increases, with advanced mini-projects involving software development, prototype building, and system integration.

The final-year capstone project is a comprehensive endeavor that spans the entire semester. Students select projects aligned with their interests or industry needs, working closely with faculty mentors who provide guidance and feedback throughout the process. Projects are evaluated based on innovation, technical depth, feasibility, and presentation quality.