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Fees
₹8,50,000
Placement
94.5%
Avg Package
₹6,00,000
Highest Package
₹12,00,000
Fees
₹8,50,000
Placement
94.5%
Avg Package
₹6,00,000
Highest Package
₹12,00,000
Seats
1,200
Students
1,200
Seats
1,200
Students
1,200
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| 1 | ENG102 | Physics for Engineers | 3-1-0-4 | - |
| 1 | ENG103 | Chemistry for Engineers | 3-1-0-4 | - |
| 1 | ENG104 | Basic Electrical Engineering | 3-1-0-4 | - |
| 1 | ENG105 | Introduction to Programming | 2-0-2-3 | - |
| 1 | ENG106 | Engineering Graphics | 2-0-2-3 | - |
| 1 | ENG107 | Communication Skills | 2-0-0-2 | - |
| 2 | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| 2 | ENG202 | Engineering Mechanics | 3-1-0-4 | - |
| 2 | ENG203 | Thermodynamics | 3-1-0-4 | - |
| 2 | ENG204 | Materials Science | 3-1-0-4 | - |
| 2 | ENG205 | Computer Programming | 2-0-2-3 | ENG105 |
| 2 | ENG206 | Engineering Drawing | 2-0-2-3 | ENG106 |
| 3 | ENG301 | Fluid Mechanics | 3-1-0-4 | ENG202 |
| 3 | ENG302 | Electrical Circuits | 3-1-0-4 | ENG104 |
| 3 | ENG303 | Design and Analysis of Algorithms | 3-1-0-4 | ENG205 |
| 3 | ENG304 | Manufacturing Processes | 3-1-0-4 | - |
| 3 | ENG305 | Structural Analysis | 3-1-0-4 | - |
| 3 | ENG306 | Chemical Reaction Engineering | 3-1-0-4 | - |
| 4 | ENG401 | Control Systems | 3-1-0-4 | ENG302 |
| 4 | ENG402 | Heat Transfer | 3-1-0-4 | ENG203 |
| 4 | ENG403 | Database Management Systems | 3-1-0-4 | ENG303 |
| 4 | ENG404 | Robotics and Automation | 3-1-0-4 | - |
| 4 | ENG405 | Geotechnical Engineering | 3-1-0-4 | ENG305 |
| 4 | ENG406 | Process Control | 3-1-0-4 | - |
| 5 | ENG501 | Machine Learning | 3-1-0-4 | ENG303 |
| 5 | ENG502 | Power Systems | 3-1-0-4 | ENG302 |
| 5 | ENG503 | Computer Networks | 3-1-0-4 | ENG303 |
| 5 | ENG504 | Advanced Manufacturing | 3-1-0-4 | ENG304 |
| 5 | ENG505 | Transportation Engineering | 3-1-0-4 | ENG305 |
| 5 | ENG506 | Environmental Engineering | 3-1-0-4 | - |
| 6 | ENG601 | Embedded Systems | 3-1-0-4 | ENG303 |
| 6 | ENG602 | Renewable Energy Systems | 3-1-0-4 | - |
| 6 | ENG603 | Data Science | 3-1-0-4 | ENG303 |
| 6 | ENG604 | Advanced Control Systems | 3-1-0-4 | ENG401 |
| 6 | ENG605 | Structural Dynamics | 3-1-0-4 | ENG305 |
| 6 | ENG606 | Biomedical Engineering | 3-1-0-4 | - |
| 7 | ENG701 | Capstone Project I | 2-0-4-4 | - |
| 7 | ENG702 | Research Methodology | 2-0-0-2 | - |
| 7 | ENG703 | Special Topics in Engineering | 3-1-0-4 | - |
| 7 | ENG704 | Advanced Mathematics | 3-1-0-4 | ENG201 |
| 7 | ENG705 | Industrial Engineering | 3-1-0-4 | - |
| 7 | ENG706 | Entrepreneurship | 2-0-0-2 | - |
| 8 | ENG801 | Capstone Project II | 2-0-4-4 | ENG701 |
| 8 | ENG802 | Internship | 0-0-0-6 | - |
| 8 | ENG803 | Final Year Thesis | 2-0-4-4 | ENG701 |
| 8 | ENG804 | Advanced Electives | 3-1-0-4 | - |
| 8 | ENG805 | Professional Ethics | 2-0-0-2 | - |
| 8 | ENG806 | Industry Exposure | 2-0-0-2 | - |
Advanced departmental elective courses form a crucial part of the engineering curriculum, providing students with specialized knowledge and practical skills. These courses are designed to meet industry demands and prepare students for advanced roles in their chosen fields.
Machine Learning (ENG501) is a comprehensive course that covers supervised and unsupervised learning techniques, neural networks, deep learning, and reinforcement learning. Students learn to implement machine learning algorithms using Python and TensorFlow, gaining hands-on experience with real-world datasets. The course emphasizes practical applications in computer vision, natural language processing, and predictive analytics.
Power Systems (ENG502) delves into the design, operation, and control of electrical power systems. Students study power generation, transmission, distribution, and load flow analysis. The course includes practical sessions on power system simulation using software tools like MATLAB and PSCAD. Students gain insights into renewable energy integration and smart grid technologies.
Computer Networks (ENG503) explores the principles and protocols of modern computer networks. Students learn about network architecture, routing algorithms, data link protocols, and network security. The course includes laboratory sessions on network simulation, packet analysis, and network troubleshooting. Practical projects involve designing and implementing network topologies and securing network communications.
Advanced Manufacturing (ENG504) covers modern manufacturing processes and technologies. Students study computer-aided design, rapid prototyping, additive manufacturing, and automation systems. The course includes hands-on sessions in CAD software, 3D printing, and CNC machining. Practical projects involve designing and manufacturing components using advanced manufacturing techniques.
Transportation Engineering (ENG505) focuses on the planning, design, and operation of transportation systems. Students learn about traffic flow theory, highway design, public transportation systems, and urban mobility. The course includes practical sessions on traffic simulation, road design, and transportation planning. Students work on projects involving transportation network optimization and sustainable mobility solutions.
Environmental Engineering (ENG506) addresses environmental challenges and sustainable solutions. Students study water and wastewater treatment, air pollution control, solid waste management, and environmental impact assessment. The course includes laboratory sessions on water quality analysis, air sampling, and environmental monitoring. Practical projects involve designing environmental protection systems and conducting environmental impact assessments.
Embedded Systems (ENG601) introduces students to the design and implementation of embedded systems. Students learn about microcontrollers, real-time operating systems, and embedded software development. The course includes laboratory sessions on hardware-software integration, embedded system design, and system testing. Practical projects involve developing embedded applications for IoT devices and industrial automation.
Renewable Energy Systems (ENG602) explores the principles and applications of renewable energy technologies. Students study solar, wind, hydro, and geothermal energy systems. The course includes practical sessions on energy system design, performance analysis, and integration with the grid. Students work on projects involving renewable energy system design and optimization.
Data Science (ENG603) covers data analysis, visualization, and machine learning techniques. Students learn to use Python, R, and SQL for data processing and analysis. The course includes hands-on sessions on data mining, statistical modeling, and predictive analytics. Practical projects involve analyzing real-world datasets and building data-driven applications.
Advanced Control Systems (ENG604) delves into advanced control theory and applications. Students study state-space methods, optimal control, and robust control. The course includes practical sessions on control system design, simulation, and implementation. Students work on projects involving control system design for industrial processes and robotics.
Structural Dynamics (ENG605) focuses on the dynamic behavior of structures under various loads. Students study vibration analysis, seismic design, and structural health monitoring. The course includes laboratory sessions on dynamic testing, modal analysis, and structural response analysis. Practical projects involve analyzing and designing structures for dynamic loads.
Biomedical Engineering (ENG606) combines engineering principles with medical and biological sciences. Students study medical device design, bioinstrumentation, and biomedical systems. The course includes laboratory sessions on biomedical signal processing, medical imaging, and prosthetics. Practical projects involve developing biomedical devices and systems for healthcare applications.
Project-based learning is a cornerstone of our engineering curriculum, emphasizing hands-on experience and practical application of theoretical knowledge. The program integrates project-based learning throughout all four years, ensuring that students develop problem-solving skills and gain real-world experience.
The mandatory mini-projects in the first and second years provide students with foundational experience in project planning, execution, and presentation. These projects are designed to reinforce classroom learning and introduce students to the engineering design process. Students work in teams to solve practical problems, developing skills in project management, communication, and collaboration.
The final-year thesis/capstone project is a significant component of the program, allowing students to apply their knowledge to a comprehensive engineering challenge. Students select projects based on their interests and career goals, working closely with faculty mentors. The project involves research, design, implementation, and documentation, culminating in a presentation and report.
Project selection is facilitated through a structured process that considers student interests, faculty expertise, and industry relevance. Students are encouraged to propose innovative ideas and collaborate with industry partners on real-world projects. Faculty mentors provide guidance and support throughout the project lifecycle, ensuring that students develop both technical and professional skills.
