Comprehensive Course Structure Across 8 Semesters
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | ENG102 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | ENG103 | Introduction to Programming | 3-0-2-4 | - |
| 1 | ENG104 | Physics for Engineers | 3-1-0-4 | - |
| 1 | ENG105 | Chemistry for Engineers | 3-1-0-4 | - |
| 1 | ENG106 | Engineering Graphics & Design | 2-1-0-3 | - |
| 1 | ENG107 | Workshop Practice | 0-0-4-2 | - |
| 2 | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| 2 | ENG202 | Electronics Devices & Circuits | 3-1-0-4 | - |
| 2 | ENG203 | Mechanics of Solids | 3-1-0-4 | - |
| 2 | ENG204 | Fluid Mechanics | 3-1-0-4 | - |
| 2 | ENG205 | Thermodynamics | 3-1-0-4 | - |
| 2 | ENG206 | Engineering Materials | 3-1-0-4 | - |
| 2 | ENG207 | Computer Programming Lab | 0-0-4-2 | - |
| 3 | ENG301 | Signals & Systems | 3-1-0-4 | ENG201 |
| 3 | ENG302 | Control Engineering | 3-1-0-4 | - |
| 3 | ENG303 | Strength of Materials | 3-1-0-4 | ENG203 |
| 3 | ENG304 | Heat Transfer | 3-1-0-4 | - |
| 3 | ENG305 | Electromagnetic Fields | 3-1-0-4 | - |
| 3 | ENG306 | Engineering Economics | 3-1-0-4 | - |
| 3 | ENG307 | Electrical Machines Lab | 0-0-4-2 | - |
| 4 | ENG401 | Digital Electronics | 3-1-0-4 | - |
| 4 | ENG402 | Design of Machine Elements | 3-1-0-4 | - |
| 4 | ENG403 | Power Plant Engineering | 3-1-0-4 | - |
| 4 | ENG404 | Operations Research | 3-1-0-4 | ENG201 |
| 4 | ENG405 | Industrial Engineering | 3-1-0-4 | - |
| 4 | ENG406 | Engineering Management | 3-1-0-4 | - |
| 4 | ENG407 | Instrumentation Lab | 0-0-4-2 | - |
| 5 | ENG501 | Microprocessors & Microcontrollers | 3-1-0-4 | - |
| 5 | ENG502 | Structural Analysis | 3-1-0-4 | - |
| 5 | ENG503 | Advanced Thermodynamics | 3-1-0-4 | - |
| 5 | ENG504 | Numerical Methods | 3-1-0-4 | - |
| 5 | ENG505 | Environmental Engineering | 3-1-0-4 | - |
| 5 | ENG506 | Quality Management | 3-1-0-4 | - |
| 5 | ENG507 | Computer Architecture Lab | 0-0-4-2 | - |
| 6 | ENG601 | Power Systems | 3-1-0-4 | - |
| 6 | ENG602 | Advanced Control Systems | 3-1-0-4 | - |
| 6 | ENG603 | Refrigeration & Air Conditioning | 3-1-0-4 | - |
| 6 | ENG604 | Industrial Automation | 3-1-0-4 | - |
| 6 | ENG605 | Project Management | 3-1-0-4 | - |
| 6 | ENG606 | Research Methodology | 3-1-0-4 | - |
| 6 | ENG607 | Automation & Control Lab | 0-0-4-2 | - |
| 7 | ENG701 | AI & Machine Learning | 3-1-0-4 | - |
| 7 | ENG702 | Cybersecurity Fundamentals | 3-1-0-4 | - |
| 7 | ENG703 | Renewable Energy Systems | 3-1-0-4 | - |
| 7 | ENG704 | Biomedical Instrumentation | 3-1-0-4 | - |
| 7 | ENG705 | Materials Science & Engineering | 3-1-0-4 | - |
| 7 | ENG706 | Advanced Chemical Processes | 3-1-0-4 | - |
| 7 | ENG707 | Specialized Research Lab | 0-0-4-2 | - |
| 8 | ENG801 | Final Year Project/Thesis | 0-0-8-10 | - |
| 8 | ENG802 | Capstone Seminar | 3-1-0-4 | - |
| 8 | ENG803 | Professional Ethics & Social Responsibility | 3-1-0-4 | - |
| 8 | ENG804 | Entrepreneurship & Innovation | 3-1-0-4 | - |
| 8 | ENG805 | Internship | 0-0-0-2 | - |
| 8 | ENG806 | Industry Interaction Session | 3-1-0-4 | - |
Advanced Departmental Elective Courses
The following are advanced departmental elective courses offered in the engineering program, each designed to deepen students' expertise in specialized areas:
- Deep Learning and Neural Networks: This course delves into advanced topics in machine learning including convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and reinforcement learning. Students will work on projects involving image classification, natural language processing, and autonomous systems.
- Cryptography & Network Security: A comprehensive study of cryptographic algorithms, secure communication protocols, and network vulnerabilities. This course includes hands-on labs using tools like OpenSSL, Wireshark, and Metasploit for penetration testing.
- Renewable Energy Systems Design: Students learn to design and optimize solar panels, wind turbines, and microgrids. The curriculum covers energy storage systems, smart grid integration, and policy frameworks supporting renewable energy adoption.
- Bioinstrumentation and Medical Devices: Focuses on designing and developing medical devices such as pacemakers, MRI machines, and wearable sensors. Students work with real-world clinical data and collaborate with hospital partners for practical applications.
- Advanced Materials Characterization: Explores modern techniques for analyzing material properties including X-ray diffraction, scanning electron microscopy (SEM), and atomic force microscopy (AFM). Projects involve developing new materials for aerospace and biomedical applications.
- Process Control & Optimization: Covers PID controllers, state-space models, and optimal control strategies. Students implement control systems using MATLAB/Simulink and experiment with industrial PLCs for process automation.
- Artificial Intelligence in Robotics: Integrates AI concepts with robotics platforms such as ROS (Robot Operating System), enabling students to build autonomous robots capable of navigation, object recognition, and manipulation tasks.
- Power Electronics & Drives: Studies power conversion circuits, inverters, and motor drives. Includes lab sessions with real-time digital signal processors (DSPs) and variable frequency drives (VFDs).
- Sustainable Manufacturing Processes: Examines green manufacturing techniques including additive manufacturing (3D printing), waste minimization, and life cycle assessment of industrial processes.
- Advanced Fluid Dynamics: Builds upon basic fluid mechanics to explore turbulent flows, compressible flow, and multiphase systems. Applications include aerospace propulsion, environmental modeling, and heat exchanger design.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is centered around experiential education that bridges theory with real-world application. From the first year onwards, students are encouraged to engage in small-scale projects, culminating in major capstone initiatives in their final year.
The structure of these projects follows a phased approach:
- Mini-Projects (Years 1-3): These are typically completed in teams of 3-5 students over one semester. They focus on solving specific problems using fundamental engineering principles, encouraging creativity and collaboration.
- Final-Year Thesis/Capstone Project (Year 4): Students choose a research topic aligned with their specialization track or industry interest. Projects are supervised by faculty mentors from the relevant domain, ensuring academic rigor and practical relevance.
Evaluation criteria for projects include:
- Technical Execution: Demonstrated understanding of core concepts and effective use of engineering tools and methodologies.
- Innovation & Creativity: Originality in approach, potential impact, and ability to propose novel solutions to existing challenges.
- Presentation Skills: Clarity in communicating findings, professionalism in delivering technical presentations, and engagement with peers and faculty.
- Team Collaboration: Effective division of responsibilities, mutual support, and adherence to deadlines throughout the project lifecycle.
Students can select projects through a formal proposal submission process where they present their ideas to faculty advisors. The department maintains a database of available research topics, industry-sponsored projects, and alumni-initiated ventures to facilitate meaningful project selection.