Comprehensive Course List Across 8 Semesters
| Semester | Course Code | Full Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | ENG101 | English for Engineers | 3-0-0-3 | - |
| 1 | MAT101 | Calculus and Differential Equations | 4-0-0-4 | - |
| 1 | PHY101 | Physics for Engineers | 3-0-0-3 | - |
| 1 | CHM101 | Chemistry for Engineers | 3-0-0-3 | - |
| 1 | CSE101 | Introduction to Programming | 2-0-2-4 | - |
| 1 | ECE101 | Basic Electrical Engineering | 3-0-0-3 | - |
| 1 | ME101 | Mechanics of Solids | 3-0-0-3 | - |
| 1 | CIV101 | Introduction to Civil Engineering | 3-0-0-3 | - |
| 2 | MAT201 | Linear Algebra and Probability | 4-0-0-4 | MAT101 |
| 2 | CSE201 | Data Structures and Algorithms | 3-0-0-3 | CSE101 |
| 2 | ECE201 | Electronics Circuits | 3-0-0-3 | ECE101 |
| 2 | ME201 | Thermodynamics | 3-0-0-3 | ME101 |
| 2 | CIV201 | Strength of Materials | 3-0-0-3 | CIV101 |
| 2 | PHY201 | Modern Physics and Applications | 3-0-0-3 | PHY101 |
| 3 | CSE301 | Database Management Systems | 3-0-0-3 | CSE201 |
| 3 | ECE301 | Digital Electronics | 3-0-0-3 | ECE201 |
| 3 | ME301 | Mechanics of Machines | 3-0-0-3 | ME201 |
| 3 | CIV301 | Transportation Engineering | 3-0-0-3 | CIV201 |
| 3 | MAT301 | Numerical Methods | 3-0-0-3 | MAT201 |
| 4 | CSE401 | Operating Systems | 3-0-0-3 | CSE201 |
| 4 | ECE401 | Communication Systems | 3-0-0-3 | ECE201 |
| 4 | ME401 | Heat Transfer | 3-0-0-3 | ME201 |
| 4 | CIV401 | Structural Analysis | 3-0-0-3 | CIV201 |
| 4 | MAT401 | Statistics and Probability | 3-0-0-3 | MAT201 |
| 5 | CSE501 | Machine Learning | 3-0-0-3 | CSE201 |
| 5 | ECE501 | Microprocessors and Microcontrollers | 3-0-0-3 | ECE201 |
| 5 | ME501 | Manufacturing Processes | 3-0-0-3 | ME201 |
| 5 | CIV501 | Geotechnical Engineering | 3-0-0-3 | CIV201 |
| 5 | MAT501 | Advanced Calculus | 3-0-0-3 | MAT201 |
| 6 | CSE601 | Computer Networks | 3-0-0-3 | CSE201 |
| 6 | ECE601 | Signal Processing | 3-0-0-3 | ECE201 |
| 6 | ME601 | Design of Machine Elements | 3-0-0-3 | ME201 |
| 6 | CIV601 | Hydraulic Engineering | 3-0-0-3 | CIV201 |
| 6 | MAT601 | Optimization Techniques | 3-0-0-3 | MAT201 |
| 7 | CSE701 | Web Technologies | 3-0-0-3 | CSE201 |
| 7 | ECE701 | Control Systems | 3-0-0-3 | ECE201 |
| 7 | ME701 | Advanced Thermodynamics | 3-0-0-3 | ME201 |
| 7 | CIV701 | Environmental Engineering | 3-0-0-3 | CIV201 |
| 7 | MAT701 | Advanced Statistics | 3-0-0-3 | MAT201 |
| 8 | CSE801 | Capstone Project | 4-0-0-4 | All prior courses |
| 8 | ECE801 | Advanced Electronics | 3-0-0-3 | ECE201 |
| 8 | ME801 | Project Management | 3-0-0-3 | ME201 |
| 8 | CIV801 | Urban Planning and Development | 3-0-0-3 | CIV201 |
| 8 | MAT801 | Research Methodology | 3-0-0-3 | MAT201 |
Advanced Departmental Elective Courses
Machine Learning: This course delves into the theoretical and practical aspects of machine learning algorithms. Students learn to implement classification, regression, clustering, and deep learning models using Python libraries like scikit-learn and TensorFlow. The course includes hands-on projects involving real-world datasets.
Advanced Computer Networks: Designed for students interested in networking and distributed systems, this course explores topics such as network security, cloud computing, and wireless communication protocols. Students gain experience with tools like Wireshark and Cisco Packet Tracer.
Cybersecurity Fundamentals: This elective introduces students to cybersecurity principles and practices. Topics include cryptography, penetration testing, incident response, and compliance frameworks. Students work on ethical hacking labs and participate in capture-the-flag competitions.
Data Science with Python: This course focuses on data analysis using Python libraries such as Pandas, NumPy, and Matplotlib. Students learn to clean, visualize, and model data for business intelligence and decision-making purposes.
Renewable Energy Systems: Students study solar, wind, hydroelectric, and geothermal power systems. The course covers energy conversion efficiency, grid integration, and environmental impact assessments. Practical sessions include building small-scale renewable energy prototypes.
Robotics and Automation: This course combines mechanical design with electronics and programming to build autonomous robots. Students use Arduino, Raspberry Pi, and ROS (Robot Operating System) for hands-on experimentation and project development.
Smart Grid Technologies: This advanced topic explores the integration of renewable energy sources into power grids. Students learn about smart meters, demand response systems, and microgrids using simulation tools like MATLAB/Simulink.
Sustainable Urban Development: This elective focuses on sustainable city planning, green building practices, and environmental impact assessment. Students analyze real urban development projects and propose solutions for reducing carbon footprints.
Biomedical Instrumentation: Designed for students interested in medical engineering, this course covers the design and application of biomedical devices. Topics include biosensors, imaging systems, and clinical monitoring equipment.
Finite Element Analysis: This course teaches students how to model and simulate mechanical structures using finite element methods. Tools like ANSYS and ABAQUS are used for stress analysis, thermal modeling, and dynamic simulations.
Industrial Internet of Things (IIoT): Students explore the role of IoT in manufacturing environments, including sensor networks, data analytics, and predictive maintenance. The course includes case studies from leading industrial companies.
Cloud Computing: This elective introduces cloud infrastructure, virtualization, and containerization technologies. Students learn to deploy applications on platforms like AWS, Azure, and Google Cloud using Docker and Kubernetes.
Advanced Materials Science: This course explores the structure-property relationships in advanced materials such as composites, ceramics, and nanomaterials. Students conduct experiments in materials characterization labs.
Advanced Control Systems: This course builds upon basic control theory by introducing modern techniques like state-space methods, robust control, and optimal control. Students implement controllers using MATLAB and Simulink.
Quantitative Finance: Designed for students interested in financial engineering, this course covers derivatives pricing, risk management, and portfolio optimization using mathematical models and programming tools.
Project-Based Learning Philosophy
The Department of Engineering at Aligarh College of Engineering and Technology places a strong emphasis on project-based learning as a cornerstone of its educational approach. This pedagogy encourages students to apply theoretical knowledge in practical settings, fostering creativity, critical thinking, and teamwork.
Projects are structured across three levels: mini-projects (semester-specific), mid-term projects (year-long), and final-year capstone projects. Mini-projects typically span 4–6 weeks and involve small teams working on real-world problems under faculty supervision. These projects help students build foundational skills and confidence.
Mid-term projects are more comprehensive, lasting up to one semester. Students collaborate with industry partners or research labs to address complex challenges. These projects often result in publishable papers, patents, or commercial prototypes.
The final-year capstone project is the most significant component of the program. Students select a topic aligned with their specialization and work closely with a faculty advisor for 6–8 months. The project culminates in a presentation to an industry panel and a written report. Successful projects may be submitted for publication or presented at national conferences.
Project selection is guided by student interests, faculty expertise, and industry relevance. Students are encouraged to propose innovative ideas that address societal needs or emerging technologies. The department provides access to funding, lab facilities, and mentorship throughout the project lifecycle.