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Fees
₹12,00,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Fees
₹12,00,000
Placement
92.0%
Avg Package
₹4,50,000
Highest Package
₹8,00,000
Seats
200
Students
1,500
Seats
200
Students
1,500
| Semester | Course Code | Full Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | MATH101 | Calculus and Differential Equations | 4-0-0-4 | None |
| 1 | PHYS101 | Physics for Engineers | 3-0-0-3 | None |
| 1 | CHEM101 | Chemistry for Engineering | 3-0-0-3 | None |
| 1 | ENG101 | Introduction to Engineering | 2-0-0-2 | None |
| 1 | CS101 | Programming Fundamentals | 3-0-0-3 | None |
| 1 | LAW101 | Engineering Ethics and Legal Awareness | 2-0-0-2 | None |
| 1 | LAB101 | Basic Engineering Lab | 0-0-3-1 | None |
| 2 | MATH201 | Linear Algebra and Numerical Methods | 4-0-0-4 | MATH101 |
| 2 | PHYS201 | Electromagnetic Fields and Waves | 3-0-0-3 | PHYS101 |
| 2 | MECH201 | Mechanics of Materials | 3-0-0-3 | None |
| 2 | CS201 | Data Structures and Algorithms | 3-0-0-3 | CS101 |
| 2 | ELEC201 | Circuit Analysis and Design | 3-0-0-3 | None |
| 2 | LAW201 | Environmental Laws and Sustainability | 2-0-0-2 | None |
| 2 | LAB201 | Physics Lab | 0-0-3-1 | PHYS101 |
| 3 | MATH301 | Probability and Statistics | 3-0-0-3 | MATH201 |
| 3 | MECH301 | Thermodynamics | 3-0-0-3 | MECH201 |
| 3 | CIVIL301 | Structural Analysis | 3-0-0-3 | MECH201 |
| 3 | CS301 | Database Management Systems | 3-0-0-3 | CS201 |
| 3 | ELEC301 | Digital Electronics and Microprocessors | 3-0-0-3 | ELEC201 |
| 3 | MECH301 | Mechanics of Solids | 3-0-0-3 | MECH201 |
| 3 | LAW301 | Intellectual Property Rights | 2-0-0-2 | None |
| 3 | LAB301 | Electronics Lab | 0-0-3-1 | ELEC201 |
| 4 | MATH401 | Advanced Calculus and Optimization | 4-0-0-4 | MATH301 |
| 4 | MECH401 | Fluid Mechanics | 3-0-0-3 | MECH301 |
| 4 | CIVIL401 | Transportation Engineering | 3-0-0-3 | CIVIL301 |
| 4 | CS401 | Software Engineering and Project Management | 3-0-0-3 | CS301 |
| 4 | ELEC401 | Control Systems | 3-0-0-3 | ELEC301 |
| 4 | MECH401 | Mechatronics | 3-0-0-3 | MECH301 |
| 4 | LAW401 | Corporate Governance and Ethics | 2-0-0-2 | None |
| 4 | LAB401 | Mechanical Engineering Lab | 0-0-3-1 | MECH301 |
| 5 | CS501 | Machine Learning and AI | 3-0-0-3 | CS401 |
| 5 | ELEC501 | Signal Processing | 3-0-0-3 | ELEC401 |
| 5 | MECH501 | Design of Machine Elements | 3-0-0-3 | MECH401 |
| 5 | CIVIL501 | Geotechnical Engineering | 3-0-0-3 | CIVIL401 |
| 5 | CS502 | Web Technologies and Cloud Computing | 3-0-0-3 | CS401 |
| 5 | ELEC502 | Embedded Systems | 3-0-0-3 | ELEC401 |
| 5 | MECH502 | Renewable Energy Systems | 3-0-0-3 | MECH401 |
| 5 | LAW501 | Business Laws and Regulations | 2-0-0-2 | None |
| 5 | LAB501 | Advanced Lab in Engineering | 0-0-3-1 | LAB401 |
| 6 | CS601 | Big Data Analytics | 3-0-0-3 | CS501 |
| 6 | ELEC601 | Power Electronics | 3-0-0-3 | ELEC502 |
| 6 | MECH601 | Industrial Engineering | 3-0-0-3 | MECH502 |
| 6 | CIVIL601 | Urban Planning and Development | 3-0-0-3 | CIVIL501 |
| 6 | CS602 | Blockchain Technologies | 3-0-0-3 | CS502 |
| 6 | ELEC602 | Wireless Communication Systems | 3-0-0-3 | ELEC501 |
| 6 | MECH602 | Automation and Control | 3-0-0-3 | MECH501 |
| 6 | LAW601 | International Trade Law | 2-0-0-2 | None |
| 6 | LAB601 | Research Lab Project | 0-0-3-1 | LAB501 |
| 7 | CS701 | Deep Learning and Neural Networks | 3-0-0-3 | CS601 |
| 7 | ELEC701 | Advanced Robotics | 3-0-0-3 | ELEC602 |
| 7 | MECH701 | Advanced Materials Engineering | 3-0-0-3 | MECH602 |
| 7 | CIVIL701 | Environmental Impact Assessment | 3-0-0-3 | CIVIL601 |
| 7 | CS702 | Cybersecurity and Network Protection | 3-0-0-3 | CS602 |
| 7 | ELEC702 | Optoelectronics and Photonics | 3-0-0-3 | ELEC601 |
| 7 | MECH702 | Sustainable Manufacturing | 3-0-0-3 | MECH601 |
| 7 | LAW701 | Technology and Innovation Law | 2-0-0-2 | None |
| 7 | LAB701 | Specialized Engineering Lab | 0-0-3-1 | LAB601 |
| 8 | CS801 | Capstone Project in AI/ML | 0-0-6-6 | CS701 |
| 8 | ELEC801 | Final Year Research Project | 0-0-6-6 | ELEC701 |
| 8 | MECH801 | Final Year Capstone in Mechanical Engineering | 0-0-6-6 | MECH701 |
| 8 | CIVIL801 | Infrastructure Design and Planning | 0-0-6-6 | CIVIL701 |
| 8 | CS802 | Startup Innovation Project | 0-0-6-6 | CS702 |
| 8 | ELEC802 | Robotics and Automation Final Project | 0-0-6-6 | ELEC702 |
| 8 | MECH802 | Advanced Manufacturing Capstone | 0-0-6-6 | MECH702 |
| 8 | CIVIL802 | Smart City Development Project | 0-0-6-6 | CIVIL701 |
Departmental electives form a crucial part of the engineering curriculum, allowing students to explore specialized areas within their chosen field. These courses are designed to provide in-depth knowledge and practical skills needed for advanced engineering practice.
This elective course focuses on deep learning frameworks, neural network architectures, reinforcement learning, and natural language processing. Students learn how to build intelligent systems that can analyze data, make predictions, and improve performance over time.
This course introduces students to the tools and techniques used in analyzing large datasets. Topics include data mining, statistical modeling, distributed computing, and visualization methods. Practical applications include marketing analytics, financial risk assessment, and scientific research.
Students gain expertise in protecting digital assets from threats such as hacking, malware, and insider attacks. The course covers encryption techniques, firewall configuration, incident response protocols, and secure coding practices.
This course explores robotics design, control systems, sensor integration, and autonomous navigation. Students develop robots that can perform complex tasks in industrial and research environments.
Students learn about the principles of light manipulation and how to apply them in devices such as lasers, photodetectors, and fiber optic communication systems. Applications include medical imaging, telecommunications, and solar energy conversion.
This elective provides a comprehensive overview of material properties, processing techniques, and applications. Students study polymers, ceramics, metals, composites, and nanomaterials in both theoretical and practical contexts.
Students explore eco-friendly manufacturing processes that reduce waste, energy consumption, and environmental impact. The course covers lean production methods, life cycle analysis, and circular economy principles.
This course teaches students how to evaluate the potential ecological consequences of engineering projects. Topics include regulatory compliance, mitigation strategies, and sustainability metrics for industrial development.
Students work on designing smart infrastructure solutions for urban environments, including intelligent transportation systems, energy-efficient buildings, and digital governance platforms.
This course introduces students to blockchain fundamentals, cryptographic security, smart contracts, and decentralized applications. It explores how blockchain can be applied in supply chain management, financial services, and digital identity verification.
The department strongly believes in project-based learning as a means of fostering innovation, collaboration, and critical thinking among students. Projects are structured to simulate real-world engineering challenges and encourage interdisciplinary problem-solving.
Mini-projects are assigned at the end of each semester to reinforce classroom learning. These projects typically last 2-3 weeks and involve small teams working on specific engineering problems under faculty supervision. Evaluation criteria include technical depth, creativity, presentation quality, and teamwork.
The final-year project is a major undertaking that requires students to apply all their knowledge and skills to solve a significant real-world problem. Students select a topic in consultation with faculty mentors, conduct extensive research, and develop a prototype or solution. The project is evaluated based on innovation, feasibility, impact, and presentation.
Each student is paired with a faculty mentor who guides them through the project selection process, provides technical advice, and helps refine their approach. Mentors are selected based on expertise in relevant areas and availability to support students throughout their projects.
