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Fees
₹8,00,000
Placement
94.0%
Avg Package
₹7,50,000
Highest Package
₹12,00,000
Fees
₹8,00,000
Placement
94.0%
Avg Package
₹7,50,000
Highest Package
₹12,00,000
Seats
300
Students
1,200
Seats
300
Students
1,200
The Engineering program at Driems University Cuttack is meticulously structured to ensure a smooth progression from foundational concepts to advanced specialization. The curriculum spans eight semesters, with each semester offering a balanced mix of core engineering courses, departmental electives, science electives, and laboratory sessions.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| I | ENG102 | Basic Electrical and Electronics Engineering | 3-1-0-4 | - |
| I | ENG103 | Introduction to Programming | 2-1-0-3 | - |
| I | ENG104 | Engineering Graphics and Design | 2-1-0-3 | - |
| I | ENG105 | Physics for Engineers | 3-1-0-4 | - |
| I | ENG106 | Chemistry for Engineers | 3-1-0-4 | - |
| I | ENG107 | Workshop Practice | 0-0-2-1 | - |
| II | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| II | ENG202 | Thermodynamics | 3-1-0-4 | - |
| II | ENG203 | Materials Science | 3-1-0-4 | - |
| II | ENG204 | Fluid Mechanics | 3-1-0-4 | - |
| II | ENG205 | Data Structures and Algorithms | 3-1-0-4 | ENG103 |
| II | ENG206 | Control Systems | 3-1-0-4 | - |
| III | ENG301 | Mechanics of Solids | 3-1-0-4 | - |
| III | ENG302 | Electrical Circuits and Networks | 3-1-0-4 | - |
| III | ENG303 | Structural Analysis | 3-1-0-4 | - |
| III | ENG304 | Signals and Systems | 3-1-0-4 | ENG201 |
| III | ENG305 | Digital Electronics | 3-1-0-4 | - |
| III | ENG306 | Computer Organization and Architecture | 3-1-0-4 | ENG205 |
| IV | ENG401 | Heat Transfer | 3-1-0-4 | - |
| IV | ENG402 | Power Electronics | 3-1-0-4 | - |
| IV | ENG403 | Engineering Economics and Management | 3-1-0-4 | - |
| IV | ENG404 | Industrial Engineering | 3-1-0-4 | - |
| IV | ENG405 | Operations Research | 3-1-0-4 | ENG201 |
| IV | ENG406 | Software Engineering | 3-1-0-4 | ENG205 |
| V | ENG501 | Advanced Mathematics for Engineers | 3-1-0-4 | - |
| V | ENG502 | Optimization Techniques | 3-1-0-4 | - |
| V | ENG503 | Renewable Energy Systems | 3-1-0-4 | - |
| V | ENG504 | Embedded Systems | 3-1-0-4 | - |
| V | ENG505 | Artificial Intelligence and Machine Learning | 3-1-0-4 | ENG205 |
| V | ENG506 | Advanced Data Structures | 3-1-0-4 | ENG205 |
| VI | ENG601 | Power System Analysis | 3-1-0-4 | - |
| VI | ENG602 | Robotics and Automation | 3-1-0-4 | - |
| VI | ENG603 | Cybersecurity Fundamentals | 3-1-0-4 | - |
| VI | ENG604 | Nanotechnology and Materials Science | 3-1-0-4 | - |
| VI | ENG605 | Project Management | 3-1-0-4 | - |
| VI | ENG606 | Human-Machine Interaction | 3-1-0-4 | - |
| VII | ENG701 | Advanced Control Systems | 3-1-0-4 | - |
| VII | ENG702 | Computer Vision and Image Processing | 3-1-0-4 | ENG505 |
| VII | ENG703 | Distributed Systems | 3-1-0-4 | ENG605 |
| VII | ENG704 | Advanced Signal Processing | 3-1-0-4 | ENG304 |
| VII | ENG705 | Quantitative Finance and Risk Analysis | 3-1-0-4 | - |
| VII | ENG706 | Smart Grid Technologies | 3-1-0-4 | - |
| VIII | ENG801 | Final Year Project / Thesis | 0-0-6-12 | - |
| VIII | ENG802 | Capstone Design Project | 0-0-4-8 | - |
| VIII | ENG803 | Entrepreneurship and Innovation | 3-1-0-4 | - |
| VIII | ENG804 | Industrial Internship | 0-0-2-4 | - |
| VIII | ENG805 | Advanced Topics in Engineering | 3-1-0-4 | - |
| VIII | ENG806 | Research Methodology | 3-1-0-4 | - |
The department offers several advanced elective courses that allow students to specialize in specific areas of interest. These courses are designed to provide in-depth knowledge and practical skills required for real-world applications.
This course introduces students to the fundamental concepts of artificial intelligence and machine learning. It covers supervised and unsupervised learning algorithms, neural networks, deep learning architectures, and reinforcement learning techniques. Students will gain hands-on experience with tools like TensorFlow and PyTorch, enabling them to develop AI solutions for complex problems.
This course explores the principles of cybersecurity, including network security, cryptography, ethical hacking, and digital forensics. Students will learn how to identify vulnerabilities, protect systems from threats, and respond effectively to cyber incidents. Practical labs simulate real-world scenarios to enhance understanding.
This course focuses on the design and implementation of renewable energy technologies such as solar, wind, hydroelectric, and bioenergy systems. Students will study energy conversion processes, grid integration strategies, and environmental impact assessments to prepare for careers in clean energy development.
This course delves into the architecture and programming of embedded systems used in IoT devices, automotive systems, and industrial automation. Students will gain experience with microcontrollers, real-time operating systems, and hardware-software co-design techniques to build efficient embedded solutions.
This course builds upon basic data structures by introducing advanced topics such as graph algorithms, dynamic programming, and computational complexity theory. Students will develop proficiency in algorithm design and analysis, preparing them for competitive programming challenges and technical interviews.
This course examines the principles of human-computer interaction and user experience design. It covers usability testing, prototyping, accessibility standards, and emerging technologies such as virtual reality and augmented reality in interface development.
This course explores modern power grid technologies including smart meters, demand response systems, and renewable energy integration strategies. Students will study the operational challenges of modern grids and learn how to design resilient, efficient, and sustainable electrical networks.
This course covers image processing techniques, computer vision algorithms, and machine learning applications in visual recognition tasks. Students will implement projects involving object detection, facial recognition, and medical imaging using deep learning frameworks.
This course introduces students to financial modeling, risk management, and quantitative analysis techniques used in investment banking and hedge funds. Topics include derivatives pricing, portfolio optimization, and stochastic calculus applied to financial markets.
This course examines the design and implementation of distributed systems including cloud computing platforms, middleware architectures, and fault tolerance mechanisms. Students will work on projects involving scalable application deployment and cluster management.
This course explores modern control theory including state-space methods, optimal control, and robust control techniques. Students will study system identification, controller design, and stability analysis in both linear and nonlinear systems.
This course covers robotics fundamentals, kinematics, sensor integration, and autonomous navigation systems. Students will engage in hands-on projects involving robot assembly, programming, and real-world problem-solving in automation environments.
This course explores the science of nanomaterials, their synthesis, properties, and applications in electronics, medicine, and energy sectors. Students will gain insight into advanced characterization techniques and emerging technologies at the atomic scale.
This course provides an overview of project management methodologies including Agile, Scrum, and Waterfall models. Students will learn how to plan, execute, and monitor engineering projects while managing risks and stakeholder expectations effectively.
This course encourages entrepreneurial thinking by teaching innovation frameworks, business model development, and startup creation strategies. Students will develop a viable business idea and present it to industry experts for feedback and mentorship.
The department places great emphasis on project-based learning as a core component of engineering education. Projects are designed to simulate real-world challenges and encourage interdisciplinary collaboration.
Mini-projects are assigned during the third through fifth semesters to reinforce classroom learning and promote practical application. These projects typically involve teams of 3-5 students working under faculty supervision on specific engineering problems or research questions. The evaluation criteria include technical depth, presentation quality, innovation level, and teamwork effectiveness.
The final-year project is a significant undertaking that allows students to apply all knowledge gained during their undergraduate studies. Students choose topics aligned with current industry trends or faculty research interests. They work closely with assigned mentors throughout the process, culminating in a comprehensive report and presentation before a panel of experts.
Students can propose project ideas or select from suggested topics provided by faculty members. Each student is paired with a mentor based on their interests and expertise areas. The selection process involves discussions between students, mentors, and department heads to ensure alignment with academic goals and industry relevance.
