Curriculum
The Engineering program at Eternal University Sirmour is meticulously structured to provide a comprehensive educational experience that balances theoretical knowledge with practical application. The curriculum spans four years, divided into eight semesters, with each semester carefully designed to build upon previous learning and introduce new concepts progressively.
Year one introduces students to foundational disciplines such as engineering mathematics, physics, chemistry, and computing basics. These courses lay the groundwork for advanced studies and ensure that students develop a solid understanding of fundamental principles before delving into specialized areas.
Year two focuses on core engineering subjects like fluid mechanics, materials science, electrical circuits, and control systems. Students also begin engaging in hands-on laboratory work, which reinforces classroom learning and develops essential technical skills.
Year three offers more specialized tracks within the engineering disciplines, allowing students to explore advanced topics such as artificial intelligence, embedded systems, renewable energy technologies, and biomedical instrumentation. Departmental electives are selected based on individual interests and career aspirations, providing flexibility and depth in specialization.
Year four culminates in capstone projects and final-year thesis work, where students apply their accumulated knowledge to solve real-world problems. This phase emphasizes independent research, critical thinking, and collaborative teamwork, preparing graduates for professional success.
Course Structure Overview
Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
---|---|---|---|---|
1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
1 | PHY101 | Physics for Engineers | 3-1-0-4 | - |
1 | CHE101 | Chemistry for Engineers | 3-1-0-4 | - |
1 | ENG102 | Introduction to Computing | 2-0-2-3 | - |
1 | ENG103 | Engineering Graphics and Design | 2-0-2-3 | - |
1 | ENG104 | Workshop Practice | 0-0-2-2 | - |
2 | ENG105 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
2 | PHY102 | Physics Laboratory | 0-0-2-2 | PHY101 |
2 | CHE102 | Chemistry Laboratory | 0-0-2-2 | CHE101 |
2 | ENG106 | Introduction to Programming | 3-1-0-4 | ENG102 |
2 | ENG107 | Basic Electrical Engineering | 3-1-0-4 | - |
2 | ENG108 | Communication Skills | 2-0-0-2 | - |
3 | ENG109 | Engineering Mathematics III | 3-1-0-4 | ENG105 |
3 | ENG110 | Fluid Mechanics | 3-1-0-4 | - |
3 | ENG111 | Materials Science | 3-1-0-4 | - |
3 | ENG112 | Electrical Circuits | 3-1-0-4 | ENG107 |
3 | ENG113 | Computer Programming Lab | 0-0-2-2 | ENG106 |
3 | ENG114 | Design Thinking and Innovation | 2-0-0-2 | - |
4 | ENG115 | Engineering Mathematics IV | 3-1-0-4 | ENG109 |
4 | ENG116 | Thermodynamics | 3-1-0-4 | - |
4 | ENG117 | Signals and Systems | 3-1-0-4 | - |
4 | ENG118 | Control Systems | 3-1-0-4 | - |
4 | ENG119 | Microprocessors and Microcontrollers | 3-1-0-4 | ENG112 |
4 | ENG120 | Entrepreneurship for Engineers | 2-0-0-2 | - |
5 | ENG121 | Advanced Mathematics for Engineering | 3-1-0-4 | ENG115 |
5 | ENG122 | Design Project I | 0-0-6-6 | - |
5 | ENG123 | Electromagnetic Fields and Waves | 3-1-0-4 | - |
5 | ENG124 | Probability and Statistics for Engineers | 3-1-0-4 | - |
5 | ENG125 | Database Systems | 3-1-0-4 | - |
5 | ENG126 | Project Management and Ethics | 2-0-0-2 | - |
6 | ENG127 | Advanced Design Project II | 0-0-6-6 | ENG122 |
6 | ENG128 | Research Methodology | 2-0-0-2 | - |
6 | ENG129 | Final Year Project | 0-0-12-12 | - |
6 | ENG130 | Internship Training | 0-0-4-4 | - |
6 | ENG131 | Capstone Thesis | 0-0-6-6 | - |
6 | ENG132 | Professional Development Workshop | 2-0-0-2 | - |
Advanced Departmental Electives
The department offers a rich array of advanced departmental electives designed to cater to diverse interests and emerging trends in engineering. These courses provide students with specialized knowledge and skills that enhance their competitiveness in the job market.
- Machine Learning and AI: This course explores the theoretical foundations of machine learning, including supervised and unsupervised learning algorithms. Students will implement models using Python and TensorFlow to solve real-world problems.
- Big Data Analytics: Focused on processing large datasets using Hadoop and Spark, this course teaches students how to extract meaningful insights from big data sources.
- Cryptography and Network Security: Students learn about encryption techniques, secure protocols, and cybersecurity frameworks essential for protecting digital assets.
- Software Architecture and Design Patterns: This course covers advanced software design principles, including object-oriented design, architectural patterns, and scalability considerations.
- Embedded Systems Programming: A hands-on course focusing on programming microcontrollers and designing embedded applications for IoT devices.
- Renewable Energy Technologies: Students study solar, wind, and hydroelectric power systems, including design, implementation, and environmental impact assessment.
- Biomedical Instrumentation: This elective introduces students to the design and operation of medical devices used in diagnostics and treatment.
- Advanced Control Systems: Covers modern control theory and applications, including state-space methods and digital controllers for complex systems.
- Data Structures and Algorithms: Explores advanced data structures and algorithmic techniques crucial for efficient problem-solving in software development.
- Computer Vision and Image Processing: Students learn to develop systems that can interpret visual information from the world, with applications in robotics and autonomous vehicles.
The department's philosophy on project-based learning emphasizes experiential education as a means of fostering deep understanding and practical skills. Projects are structured around real-world challenges, encouraging students to apply their knowledge in meaningful ways. Mini-projects begin in Year 2 and grow in complexity each semester, culminating in a final-year thesis or capstone project.
The evaluation criteria for these projects include creativity, technical implementation, documentation quality, presentation skills, and peer feedback. Students select their projects based on personal interest, faculty guidance, and alignment with industry trends. Faculty mentors are assigned according to the student's specialization and research interests, ensuring personalized support throughout the process.