Course Structure Overview
The Bachelor of Technology program at Gyan Ganga Institute of Technology and Sciences is structured over eight semesters, with each semester comprising a mix of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is designed to provide students with a solid foundation in engineering principles while allowing them to explore specialized areas based on their interests and career goals.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | PHYS101 | Physics for Engineers | 3-1-0-4 | None |
| 1 | MATH101 | Calculus and Differential Equations | 4-0-0-4 | None |
| 1 | CHEM101 | Chemistry for Engineers | 3-1-0-4 | None |
| 1 | ENGL101 | English Communication Skills | 2-0-0-2 | None |
| 1 | CS101 | Introduction to Programming | 3-0-2-5 | None |
| 1 | MECH101 | Engineering Mechanics | 3-1-0-4 | MATH101 |
| 2 | MATH201 | Linear Algebra and Numerical Methods | 3-0-0-3 | MATH101 |
| 2 | PHYS201 | Thermodynamics and Heat Transfer | 3-1-0-4 | PHYS101 |
| 2 | CHEM201 | Organic Chemistry | 3-1-0-4 | CHEM101 |
| 2 | CS201 | Data Structures and Algorithms | 3-0-2-5 | CS101 |
| 2 | EE201 | Electrical Circuits and Networks | 3-1-0-4 | MATH101 |
| 3 | MATH301 | Probability and Statistics | 3-0-0-3 | MATH201 |
| 3 | PHYS301 | Optics and Modern Physics | 3-1-0-4 | PHYS201 |
| 3 | CS301 | Database Management Systems | 3-0-2-5 | CS201 |
| 3 | MECH301 | Mechanics of Materials | 3-1-0-4 | MECH101 |
| 3 | CIVIL301 | Strength of Materials | 3-1-0-4 | MECH101 |
| 4 | MATH401 | Differential Equations | 3-0-0-3 | MATH301 |
| 4 | PHYS401 | Quantum Physics | 3-1-0-4 | PHYS301 |
| 4 | CS401 | Software Engineering | 3-0-2-5 | CS301 |
| 4 | MECH401 | Fluid Mechanics | 3-1-0-4 | MECH301 |
| 4 | CIVIL401 | Structural Analysis | 3-1-0-4 | CIVIL301 |
| 5 | CS501 | Machine Learning | 3-0-2-5 | CS401 |
| 5 | MECH501 | Heat Transfer | 3-1-0-4 | PHYS201 |
| 5 | CIVIL501 | Geotechnical Engineering | 3-1-0-4 | CIVIL401 |
| 5 | EE501 | Digital Electronics | 3-1-0-4 | EE201 |
| 6 | CS601 | Cybersecurity | 3-0-2-5 | CS401 |
| 6 | MECH601 | Manufacturing Processes | 3-1-0-4 | MECH401 |
| 6 | CIVIL601 | Transportation Engineering | 3-1-0-4 | CIVIL501 |
| 6 | EE601 | Control Systems | 3-1-0-4 | EE201 |
| 7 | CS701 | Advanced Data Science | 3-0-2-5 | CS501 |
| 7 | MECH701 | Advanced Thermodynamics | 3-1-0-4 | MECH501 |
| 7 | CIVIL701 | Environmental Engineering | 3-1-0-4 | CIVIL601 |
| 7 | EE701 | Power Systems | 3-1-0-4 | EE201 |
| 8 | CS801 | Capstone Project | 0-0-6-12 | All previous courses |
| 8 | MECH801 | Final Year Thesis | 0-0-6-12 | All previous courses |
| 8 | CIVIL801 | Final Year Project | 0-0-6-12 | All previous courses |
| 8 | EE801 | Research and Development | 0-0-6-12 | All previous courses |
Advanced Departmental Electives
The department offers a variety of advanced elective courses designed to deepen students' understanding of specialized topics. These courses are taught by experienced faculty members and often incorporate current industry trends.
Machine Learning
This course introduces students to machine learning algorithms, including supervised and unsupervised learning techniques. Students learn to implement these algorithms using Python libraries like scikit-learn and TensorFlow. The course emphasizes practical applications in areas such as image recognition, natural language processing, and predictive analytics.
Cybersecurity
Students explore the principles of cybersecurity, including network security, cryptography, and ethical hacking. The course covers real-world threat scenarios and defensive strategies, preparing students for careers in information security. Practical sessions involve penetration testing and vulnerability assessment tools.
Advanced Data Science
This course delves into advanced data science techniques, including deep learning, neural networks, and big data analytics. Students work on large datasets using tools like Apache Spark and Hadoop. The focus is on extracting insights from complex data and building scalable machine learning models.
Robotics and Automation
The course covers the design and implementation of robotic systems, including sensors, actuators, and control systems. Students work on hands-on projects involving autonomous navigation, object recognition, and human-robot interaction. The curriculum includes both theoretical foundations and practical applications in manufacturing and service industries.
Sustainable Energy Systems
This course explores renewable energy technologies, including solar, wind, and hydroelectric power. Students study the principles of energy conversion and storage, with a focus on sustainability and environmental impact. Practical sessions involve designing and testing energy systems using simulation software.
Materials Science and Nanotechnology
The course introduces students to advanced materials science concepts, including crystallography, polymer science, and nanofabrication techniques. Students learn about the properties and applications of various materials, from metals to ceramics to polymers. Practical sessions involve working with advanced characterization tools.
Biomedical Engineering
This course combines engineering principles with medical science to develop innovative healthcare solutions. Topics include biomechanics, bioinstrumentation, and medical imaging. Students work on projects involving prosthetics, diagnostic devices, and therapeutic systems.
Data Mining and Big Data Analytics
The course covers data mining techniques, including clustering, classification, and association rule mining. Students learn to use tools like Python, R, and SQL for analyzing large datasets. Practical sessions involve working with real-world datasets from various industries.
Internet of Things (IoT)
This course explores the architecture and implementation of IoT systems, including sensor networks, wireless communication protocols, and cloud integration. Students work on projects involving smart home automation, industrial monitoring, and environmental sensing.
Advanced Control Systems
The course covers advanced topics in control theory, including state-space representation, optimal control, and robust control. Students learn to design and analyze control systems for complex dynamic processes. Practical sessions involve using MATLAB/Simulink for simulation and implementation.
Project-Based Learning Philosophy
Gyan Ganga's approach to project-based learning is centered on experiential education and real-world application. The philosophy emphasizes that students learn best when they are actively engaged in solving authentic problems.
Mini-Projects
Mini-projects are introduced in the second year, allowing students to apply theoretical concepts to practical challenges. These projects typically span 8-10 weeks and involve small groups working under faculty supervision. Students are encouraged to choose topics aligned with their interests and career aspirations.
Final-Year Thesis/Capstone Project
The final-year project is a comprehensive endeavor that integrates knowledge from all previous semesters. Students work on individual or group projects that address significant engineering challenges. The project involves literature review, design, implementation, testing, and documentation.
Evaluation Criteria
Projects are evaluated based on multiple criteria, including technical merit, innovation, teamwork, presentation skills, and adherence to deadlines. Faculty mentors play a crucial role in guiding students throughout the project lifecycle.
Project Selection Process
Students select projects through a structured process involving proposal submission, faculty review, and approval. The selection considers academic relevance, feasibility, and alignment with industry trends. Faculty members serve as mentors, providing guidance and support throughout the project.