Course Structure Overview
The engineering curriculum at G L A University Mathura is designed to provide a balanced mix of foundational knowledge, core technical skills, and specialized electives. The program spans eight semesters, with each semester structured to build upon the previous one. Students are required to complete a minimum of 160 credits over the course duration.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| I | ENG102 | Physics for Engineers | 3-1-0-4 | - |
| I | ENG103 | Chemistry for Engineers | 3-1-0-4 | - |
| I | ENG104 | Computer Programming | 2-1-2-5 | - |
| I | ENG105 | Engineering Graphics | 2-1-2-5 | - |
| I | ENG106 | English for Engineers | 3-0-0-3 | - |
| II | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| II | ENG202 | Electrical Circuits and Networks | 3-1-0-4 | - |
| II | ENG203 | Mechanics of Materials | 3-1-0-4 | - |
| II | ENG204 | Signals and Systems | 3-1-0-4 | ENG101 |
| II | ENG205 | Introduction to Programming | 2-1-2-5 | ENG104 |
| III | ENG301 | Thermodynamics | 3-1-0-4 | ENG201 |
| III | ENG302 | Fluid Mechanics | 3-1-0-4 | - |
| III | ENG303 | Digital Logic Design | 3-1-0-4 | ENG205 |
| III | ENG304 | Probability and Statistics | 3-1-0-4 | ENG101 |
| III | ENG305 | Data Structures and Algorithms | 3-1-0-4 | ENG205 |
| IV | ENG401 | Control Systems | 3-1-0-4 | ENG204 |
| IV | ENG402 | Electromagnetic Fields | 3-1-0-4 | ENG202 |
| IV | ENG403 | Manufacturing Processes | 3-1-0-4 | - |
| IV | ENG404 | Computer Architecture | 3-1-0-4 | ENG303 |
| V | ENG501 | Embedded Systems | 3-1-0-4 | ENG404 |
| V | ENG502 | Machine Learning | 3-1-0-4 | ENG304 |
| V | ENG503 | Power Systems | 3-1-0-4 | ENG202 |
| V | ENG504 | Advanced Mathematics | 3-1-0-4 | ENG201 |
| V | ENG505 | Project Management | 3-1-0-4 | - |
| VI | ENG601 | Advanced Control Systems | 3-1-0-4 | ENG401 |
| VI | ENG602 | Neural Networks | 3-1-0-4 | ENG502 |
| VI | ENG603 | Power Electronics | 3-1-0-4 | ENG503 |
| VI | ENG604 | Research Methodology | 3-1-0-4 | - |
| VII | ENG701 | Capstone Project I | 2-0-4-6 | - |
| VIII | ENG801 | Capstone Project II | 2-0-4-6 | ENG701 |
Advanced Departmental Electives
The department offers a wide range of advanced elective courses that allow students to explore specialized areas of interest and gain deeper insights into their chosen fields:
- Deep Learning and Neural Networks: This course delves into the architecture of deep neural networks, including convolutional networks, recurrent networks, and transformers. Students learn to implement models using frameworks like TensorFlow and PyTorch.
- Internet of Things (IoT) and Embedded Systems: Focused on designing and developing IoT applications, this course covers sensor integration, wireless communication protocols, and real-time data processing techniques.
- Renewable Energy Technologies: Students study solar energy systems, wind turbines, and energy storage solutions, with hands-on projects involving renewable energy installation and efficiency analysis.
- Cybersecurity Fundamentals: This course explores cryptographic algorithms, network security, and digital forensics. It prepares students to protect critical infrastructure from cyber threats.
- Robotics and Automation: Covering robot kinematics, control systems, and sensor integration, this course enables students to design autonomous robots for industrial applications.
- Advanced Manufacturing Processes: This course focuses on additive manufacturing, precision machining, and automation in production environments.
- Transportation Systems Engineering: Students analyze traffic flow models, transportation planning, and infrastructure design using simulation tools.
- Biomedical Instrumentation: Combines engineering principles with medical applications to design diagnostic devices and monitoring systems.
Project-Based Learning Philosophy
The philosophy of project-based learning at G L A University Mathura emphasizes experiential education, where students are encouraged to apply theoretical knowledge in practical scenarios. Projects are assigned based on real-world challenges and industry requirements, ensuring relevance and impact.
Mini-projects are conducted throughout the program, typically lasting 4–6 weeks, allowing students to work on small-scale applications or research problems. These projects are evaluated based on innovation, technical execution, teamwork, and presentation skills.
The final-year thesis/capstone project is a major component of the curriculum, requiring students to undertake an in-depth study or design a significant solution to a complex problem. Students select their projects in consultation with faculty mentors who guide them through the research process, from literature review to prototype development and final presentation.