Comprehensive Course Structure
The Engineering program at Sapthagiri Nps University Bangalore is structured to provide students with a robust academic foundation followed by specialized knowledge in their chosen field. The curriculum is designed to be both comprehensive and flexible, allowing students to explore various aspects of engineering while developing expertise in their area of interest. The program is divided into eight semesters, with each semester carrying a specific credit load and focus area. The first four semesters focus on building a strong foundation in core sciences and engineering principles, while the subsequent semesters allow students to specialize in their chosen field and engage in advanced projects and research.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Mathematics I | 3-1-0-4 | None |
| 1 | ENG102 | Engineering Physics | 3-1-0-4 | None |
| 1 | ENG103 | Engineering Chemistry | 3-1-0-4 | None |
| 1 | ENG104 | Engineering Graphics | 2-1-0-3 | None |
| 1 | ENG105 | Computer Programming | 3-0-2-4 | None |
| 1 | ENG106 | Engineering Mechanics | 3-1-0-4 | None |
| 1 | ENG107 | Engineering Workshop | 0-0-3-2 | None |
| 2 | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| 2 | ENG202 | Electrical Engineering Fundamentals | 3-1-0-4 | ENG102 |
| 2 | ENG203 | Thermodynamics | 3-1-0-4 | ENG102 |
| 2 | ENG204 | Materials Science | 3-1-0-4 | ENG103 |
| 2 | ENG205 | Engineering Economics | 3-1-0-4 | ENG101 |
| 2 | ENG206 | Programming with Data Structures | 3-0-2-4 | ENG105 |
| 2 | ENG207 | Engineering Lab | 0-0-3-2 | ENG106 |
| 3 | ENG301 | Engineering Mathematics III | 3-1-0-4 | ENG201 |
| 3 | ENG302 | Control Systems | 3-1-0-4 | ENG202 |
| 3 | ENG303 | Fluid Mechanics | 3-1-0-4 | ENG203 |
| 3 | ENG304 | Manufacturing Processes | 3-1-0-4 | ENG204 |
| 3 | ENG305 | Signals and Systems | 3-1-0-4 | ENG201 |
| 3 | ENG306 | Database Management Systems | 3-0-2-4 | ENG206 |
| 3 | ENG307 | Engineering Lab II | 0-0-3-2 | ENG207 |
| 4 | ENG401 | Engineering Mathematics IV | 3-1-0-4 | ENG301 |
| 4 | ENG402 | Power Systems | 3-1-0-4 | ENG202 |
| 4 | ENG403 | Heat Transfer | 3-1-0-4 | ENG203 |
| 4 | ENG404 | Advanced Manufacturing | 3-1-0-4 | ENG304 |
| 4 | ENG405 | Communication Systems | 3-1-0-4 | ENG305 |
| 4 | ENG406 | Software Engineering | 3-0-2-4 | ENG206 |
| 4 | ENG407 | Engineering Lab III | 0-0-3-2 | ENG307 |
| 5 | ENG501 | Advanced Control Systems | 3-1-0-4 | ENG302 |
| 5 | ENG502 | Refrigeration and Air Conditioning | 3-1-0-4 | ENG403 |
| 5 | ENG503 | Advanced Materials | 3-1-0-4 | ENG304 |
| 5 | ENG504 | Industrial Engineering | 3-1-0-4 | ENG205 |
| 5 | ENG505 | Microprocessors and Microcontrollers | 3-1-0-4 | ENG405 |
| 5 | ENG506 | Machine Learning | 3-0-2-4 | ENG305 |
| 5 | ENG507 | Project I | 0-0-6-6 | ENG407 |
| 6 | ENG601 | Advanced Power Systems | 3-1-0-4 | ENG402 |
| 6 | ENG602 | Advanced Heat Transfer | 3-1-0-4 | ENG403 |
| 6 | ENG603 | Advanced Manufacturing Processes | 3-1-0-4 | ENG404 |
| 6 | ENG604 | Operations Research | 3-1-0-4 | ENG401 |
| 6 | ENG605 | Embedded Systems | 3-1-0-4 | ENG505 |
| 6 | ENG606 | Deep Learning | 3-0-2-4 | ENG506 |
| 6 | ENG607 | Project II | 0-0-6-6 | ENG507 |
| 7 | ENG701 | Advanced Control Systems | 3-1-0-4 | ENG501 |
| 7 | ENG702 | Renewable Energy Systems | 3-1-0-4 | ENG402 |
| 7 | ENG703 | Advanced Materials Science | 3-1-0-4 | ENG503 |
| 7 | ENG704 | Supply Chain Management | 3-1-0-4 | ENG504 |
| 7 | ENG705 | Internet of Things | 3-1-0-4 | ENG605 |
| 7 | ENG706 | Neural Networks | 3-0-2-4 | ENG606 |
| 7 | ENG707 | Project III | 0-0-6-6 | ENG607 |
| 8 | ENG801 | Capstone Project | 0-0-12-12 | ENG707 |
| 8 | ENG802 | Research Methodology | 3-1-0-4 | ENG701 |
| 8 | ENG803 | Professional Ethics | 3-1-0-4 | None |
| 8 | ENG804 | Entrepreneurship | 3-1-0-4 | None |
| 8 | ENG805 | Advanced Topics in Engineering | 3-1-0-4 | ENG802 |
Advanced Departmental Elective Courses
The department offers a wide range of advanced departmental elective courses that allow students to explore specialized areas of interest and develop expertise in their chosen field. These courses are designed to provide students with in-depth knowledge and practical skills that are essential for success in their careers.
Machine Learning (ENG506): This course provides a comprehensive introduction to machine learning concepts and algorithms. Students will learn about supervised and unsupervised learning, neural networks, deep learning, and reinforcement learning. The course emphasizes practical applications and includes hands-on projects using popular machine learning libraries such as TensorFlow and PyTorch. Students will also explore ethical considerations in machine learning and its applications in various domains such as healthcare, finance, and autonomous systems.
Deep Learning (ENG606): This advanced course delves into the theory and practice of deep learning techniques. Students will study advanced neural network architectures such as convolutional neural networks, recurrent neural networks, and transformers. The course covers topics such as natural language processing, computer vision, and generative models. Students will work on projects involving state-of-the-art deep learning applications and gain experience with industry-standard frameworks.
Embedded Systems (ENG605): This course focuses on the design and implementation of embedded systems for various applications. Students will learn about microcontrollers, real-time operating systems, and hardware-software co-design. The course includes practical sessions on programming embedded systems using C and assembly languages. Students will also explore the integration of sensors, actuators, and communication modules in embedded systems.
Internet of Things (ENG705): This course explores the architecture and applications of Internet of Things (IoT) systems. Students will study sensor networks, wireless communication protocols, and data processing techniques for IoT applications. The course emphasizes practical implementation and includes projects involving smart home systems, industrial automation, and environmental monitoring. Students will gain experience with popular IoT platforms and development tools.
Neural Networks (ENG706): This course provides an in-depth study of neural network architectures and their applications. Students will explore various types of neural networks including feedforward, recurrent, and convolutional networks. The course covers advanced topics such as backpropagation, gradient descent, and optimization techniques. Students will work on projects involving image recognition, natural language processing, and predictive modeling.
Advanced Power Systems (ENG601): This course covers advanced topics in power systems engineering including power system stability, protection, and control. Students will study power system analysis, load flow studies, and fault analysis. The course includes practical sessions on power system simulation using industry-standard software. Students will also explore renewable energy integration and smart grid technologies.
Advanced Heat Transfer (ENG602): This advanced course delves into the principles and applications of heat transfer in various engineering systems. Students will study conduction, convection, and radiation heat transfer in detail. The course covers advanced topics such as heat exchanger design, thermal analysis, and computational fluid dynamics. Students will work on projects involving heat transfer applications in power plants, HVAC systems, and electronic cooling.
Advanced Manufacturing Processes (ENG603): This course explores advanced manufacturing techniques and technologies including additive manufacturing, precision machining, and automation. Students will study various manufacturing processes and their applications in different industries. The course includes practical sessions on CAD/CAM software and manufacturing equipment. Students will also explore the integration of Industry 4.0 technologies in manufacturing.
Operations Research (ENG604): This course introduces students to mathematical optimization techniques and their applications in engineering and business. Students will study linear programming, integer programming, and network optimization. The course covers topics such as decision analysis, queuing theory, and simulation. Students will work on projects involving resource allocation, scheduling, and logistics optimization.
Advanced Control Systems (ENG701): This advanced course covers modern control system design techniques including state-space methods, optimal control, and robust control. Students will study control system analysis and design using computer simulation tools. The course includes practical sessions on control system implementation and testing. Students will also explore applications of control systems in robotics, aerospace, and process control.
Renewable Energy Systems (ENG702): This course focuses on the design and implementation of renewable energy systems including solar, wind, and hydroelectric power. Students will study energy conversion processes, system integration, and grid connection technologies. The course includes practical sessions on renewable energy system design and simulation. Students will also explore environmental impact assessment and policy frameworks for renewable energy development.
Advanced Materials Science (ENG703): This course provides an in-depth study of advanced materials and their properties. Students will explore nanomaterials, composite materials, and smart materials. The course covers topics such as materials characterization, processing techniques, and applications in various industries. Students will work on projects involving materials design and development for specific applications.
Supply Chain Management (ENG704): This course explores the principles and practices of supply chain management in engineering and manufacturing. Students will study logistics, inventory management, and procurement strategies. The course includes practical sessions on supply chain optimization and risk management. Students will also explore the integration of digital technologies in supply chain management.
Research Methodology (ENG802): This course provides students with the skills and knowledge needed to conduct research in engineering. Students will learn about research design, data collection, and analysis techniques. The course covers topics such as literature review, hypothesis testing, and scientific writing. Students will also explore ethical considerations in research and prepare for their capstone project.
Project-Based Learning Philosophy
The department's philosophy on project-based learning is rooted in the belief that hands-on experience is essential for developing practical skills and deep understanding of engineering principles. The program emphasizes experiential learning through a structured approach that includes mini-projects, capstone projects, and industry collaborations.
The project-based learning approach is designed to simulate real-world engineering challenges and provide students with opportunities to apply their theoretical knowledge to practical problems. Students are encouraged to work in multidisciplinary teams, fostering collaboration and communication skills that are essential in professional environments.
The structure of project-based learning includes several phases:
- Problem Identification: Students identify real-world problems and define project scope and objectives.
- Research and Analysis: Students conduct literature reviews and analyze existing solutions.
- Design and Development: Students design and develop solutions using engineering principles and tools.
- Implementation and Testing: Students implement their solutions and test their effectiveness.
- Documentation and Presentation: Students document their work and present findings to faculty and peers.
The scope of projects ranges from small-scale laboratory experiments to large-scale industry-sponsored initiatives. Students have the opportunity to work on projects that align with their interests and career goals, ensuring relevance and engagement.
Evaluation criteria for projects include:
- Technical Competence: Demonstrated understanding of engineering principles and application of appropriate methods.
- Problem-Solving Skills: Ability to identify, analyze, and solve complex engineering problems.
- Team Collaboration: Effectiveness in working with team members and contributing to group success.
- Communication Skills: Ability to present ideas clearly and professionally.
- Innovation and Creativity: Originality in approach and potential for impact.
The final-year thesis/capstone project is a comprehensive endeavor that integrates all aspects of the student's engineering education. Students work closely with faculty mentors to select projects that align with their interests and career aspirations. The project involves extensive research, design, implementation, and documentation, culminating in a final presentation and report.
Students select their projects and faculty mentors through a structured process that considers their academic performance, interests, and career goals. The department facilitates this process by providing information about ongoing research projects and faculty expertise. Students are encouraged to explore multiple options and make informed decisions about their capstone projects.