Comprehensive Course Listing
The following table outlines the complete curriculum structure for the Engineering program at Maulana Azad University Jodhpur, covering all 8 semesters. Each course includes its code, full title, credit structure (L-T-P-C), and prerequisites where applicable.
| Semester | Course Code | Full Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | Engineering Graphics | 3-0-0-3 | - |
| 1 | MAT101 | Calculus I | 4-0-0-4 | - |
| 1 | PHY101 | Physics I | 3-0-0-3 | - |
| 1 | CHE101 | Chemistry | 3-0-0-3 | - |
| 1 | BIO101 | Biology | 3-0-0-3 | - |
| 1 | ENG102 | Basic Electrical and Electronics Engineering | 3-0-0-3 | - |
| 1 | COM101 | Communication Skills | 2-0-0-2 | - |
| 1 | MAT102 | Calculus II | 4-0-0-4 | MAT101 |
| 1 | PHY102 | Physics II | 3-0-0-3 | PHY101 |
| 1 | BIO102 | Introduction to Biology | 3-0-0-3 | - |
| 2 | MAT201 | Differential Equations | 4-0-0-4 | MAT102 |
| 2 | ENG201 | Strength of Materials | 3-0-0-3 | - |
| 2 | PHY201 | Thermodynamics | 3-0-0-3 | PHY102 |
| 2 | CHE201 | Organic Chemistry | 3-0-0-3 | CHE101 |
| 2 | ENG202 | Fluid Mechanics | 3-0-0-3 | - |
| 2 | COM201 | Technical Writing and Presentation | 2-0-0-2 | - |
| 2 | ENG203 | Basic Computer Programming | 3-0-0-3 | - |
| 2 | MAT202 | Linear Algebra | 4-0-0-4 | MAT102 |
| 2 | PHY202 | Optics and Modern Physics | 3-0-0-3 | PHY102 |
| 3 | ENG301 | Electrical Circuits | 3-0-0-3 | - |
| 3 | MAT301 | Probability and Statistics | 4-0-0-4 | MAT202 |
| 3 | ENG302 | Materials Science | 3-0-0-3 | - |
| 3 | ENG303 | Manufacturing Processes | 3-0-0-3 | - |
| 3 | COM301 | Professional Communication | 2-0-0-2 | - |
| 3 | ENG304 | Data Structures and Algorithms | 3-0-0-3 | - |
| 3 | MAT302 | Numerical Methods | 4-0-0-4 | MAT201 |
| 3 | ENG305 | Control Systems | 3-0-0-3 | - |
| 3 | ENG306 | Thermodynamics II | 3-0-0-3 | PHY201 |
| 4 | ENG401 | Computer Architecture | 3-0-0-3 | - |
| 4 | MAT401 | Advanced Calculus | 4-0-0-4 | MAT201 |
| 4 | ENG402 | Machine Design | 3-0-0-3 | - |
| 4 | ENG403 | Signal Processing | 3-0-0-3 | - |
| 4 | COM401 | Project Management | 2-0-0-2 | - |
| 4 | ENG404 | Embedded Systems | 3-0-0-3 | - |
| 4 | MAT402 | Partial Differential Equations | 4-0-0-4 | MAT201 |
| 4 | ENG405 | Power Electronics | 3-0-0-3 | - |
| 5 | ENG501 | Advanced Control Systems | 3-0-0-3 | - |
| 5 | ENG502 | Advanced Materials | 3-0-0-3 | - |
| 5 | ENG503 | Operations Research | 3-0-0-3 | - |
| 5 | COM501 | Leadership and Ethics | 2-0-0-2 | - |
| 5 | ENG504 | Robotics | 3-0-0-3 | - |
| 5 | MAT501 | Mathematical Modeling | 4-0-0-4 | - |
| 5 | ENG505 | Advanced Thermodynamics | 3-0-0-3 | - |
| 6 | ENG601 | Machine Learning | 3-0-0-3 | - |
| 6 | ENG602 | Neural Networks | 3-0-0-3 | - |
| 6 | ENG603 | Cybersecurity Fundamentals | 3-0-0-3 | - |
| 6 | COM601 | Innovation and Entrepreneurship | 2-0-0-2 | - |
| 6 | ENG604 | Advanced Signal Processing | 3-0-0-3 | - |
| 6 | MAT601 | Stochastic Processes | 4-0-0-4 | - |
| 7 | ENG701 | Capstone Project I | 3-0-0-3 | - |
| 7 | ENG702 | Research Methodology | 3-0-0-3 | - |
| 7 | COM701 | Professional Internship | 2-0-0-2 | - |
| 7 | ENG703 | Advanced Computer Architecture | 3-0-0-3 | - |
| 7 | MAT701 | Advanced Probability Theory | 4-0-0-4 | - |
| 8 | ENG801 | Capstone Project II | 3-0-0-3 | - |
| 8 | ENG802 | Advanced Thesis Writing | 3-0-0-3 | - |
| 8 | COM801 | Industry Interaction Workshop | 2-0-0-2 | - |
| 8 | MAT801 | Advanced Mathematical Analysis | 4-0-0-4 | - |
Detailed Course Descriptions for Advanced Departmental Electives
Machine Learning: This course introduces students to the foundational concepts of machine learning, including supervised and unsupervised learning algorithms, neural networks, and deep learning techniques. Students will gain hands-on experience with Python-based tools like TensorFlow and PyTorch.
Neural Networks: Focused on designing and implementing artificial neural networks, this course covers architectures such as convolutional networks, recurrent networks, and transformer models. Students will work on real-world applications in computer vision and natural language processing.
Cybersecurity Fundamentals: This course explores the principles of information security, including cryptography, network security, and ethical hacking. Students will learn how to protect systems from cyber threats and implement secure coding practices.
Advanced Signal Processing: Delving into advanced topics in signal processing, this course covers wavelets, filter banks, and spectral estimation techniques. It includes practical applications in audio and image processing.
Robotics: This course combines principles of mechanical engineering, electrical engineering, and computer science to design and build autonomous robots. Students will gain experience with sensors, actuators, and control systems.
Advanced Control Systems: Building on foundational knowledge, this course explores modern control theory including state-space methods, optimal control, and robust control. Applications in aerospace and industrial automation are emphasized.
Operations Research: Students will learn mathematical optimization techniques for solving complex decision-making problems. Topics include linear programming, integer programming, and simulation methods.
Advanced Thermodynamics: This course delves into advanced thermodynamic concepts, including phase equilibrium, chemical reactions, and energy systems. It prepares students for careers in power generation and environmental engineering.
Advanced Materials: This course examines the structure-property relationships of advanced materials, including composites, ceramics, and nanomaterials. Students will explore manufacturing techniques and applications in engineering.
Research Methodology: Designed to prepare students for research-oriented careers, this course covers experimental design, data analysis, and scientific writing. Students will learn how to conduct independent research projects.
Project-Based Learning Philosophy
The department's philosophy on project-based learning emphasizes the integration of theoretical knowledge with practical application. From the first year onwards, students are exposed to small-scale projects that build upon each other to form a comprehensive understanding of engineering principles.
Mini-projects are assigned in the second and third years, allowing students to apply concepts learned in class to real-world scenarios. These projects are evaluated based on creativity, technical execution, teamwork, and presentation skills.
The final-year thesis/capstone project is a significant component of the program. Students select topics aligned with their interests and career goals, working closely with faculty mentors. Projects often involve collaboration with industry partners, providing students with exposure to current challenges and solutions in engineering.
Students choose their projects through a proposal process that involves faculty reviews and alignment with departmental resources. Faculty mentors are selected based on expertise and availability, ensuring quality guidance throughout the project lifecycle.