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Fees
₹3,50,000
Placement
92.5%
Avg Package
₹6,50,000
Highest Package
₹80,00,000
Fees
₹3,50,000
Placement
92.5%
Avg Package
₹6,50,000
Highest Package
₹80,00,000
Seats
120
Students
1,200
Seats
120
Students
1,200
The Bachelor of Technology program at Allahabad College of Engineering and Management is structured over eight semesters, providing a comprehensive blend of theoretical knowledge and practical application. The curriculum is designed to align with industry standards while fostering innovation and critical thinking skills.
| SEMESTER | COURSE CODE | COURSE TITLE | CREDIT STRUCTURE (L-T-P-C) | PREREQUISITES |
|---|---|---|---|---|
| I | ENG101 | English for Engineering Communication | 3-0-0-3 | - |
| I | MAT101 | Engineering Mathematics I | 4-0-0-4 | - |
| I | PHY101 | Physics for Engineers | 3-0-0-3 | - |
| I | CHE101 | Chemistry for Engineers | 3-0-0-3 | - |
| I | ECO101 | Engineering Economics and Management | 2-0-0-2 | - |
| I | COM101 | Computer Programming using C | 2-0-2-3 | - |
| I | LAB101 | Programming Lab | 0-0-2-2 | - |
| II | MAT102 | Engineering Mathematics II | 4-0-0-4 | MAT101 |
| II | PHY102 | Electromagnetic Fields and Waves | 3-0-0-3 | PHY101 |
| II | CHE102 | Organic Chemistry | 3-0-0-3 | CHE101 |
| II | ECE101 | Basic Electrical Engineering | 3-0-0-3 | - |
| II | COM201 | Data Structures and Algorithms | 3-0-0-3 | COM101 |
| II | LAB201 | Data Structures Lab | 0-0-2-2 | - |
| III | MAT201 | Engineering Mathematics III | 4-0-0-4 | MAT102 |
| III | MEC101 | Applied Mechanics and Strength of Materials | 3-0-0-3 | - |
| III | ECE201 | Electronic Devices and Circuits | 3-0-0-3 | ECE101 |
| III | CSE201 | Object-Oriented Programming with Java | 3-0-0-3 | COM201 |
| III | LAB301 | Java Lab | 0-0-2-2 | - |
| IV | MAT202 | Engineering Mathematics IV | 4-0-0-4 | MAT201 |
| IV | MEC201 | Thermodynamics | 3-0-0-3 | MEC101 |
| IV | ECE301 | Digital Electronics | 3-0-0-3 | ECE201 |
| IV | CSE301 | Database Management Systems | 3-0-0-3 | CSE201 |
| IV | LAB401 | DBMS Lab | 0-0-2-2 | - |
| V | MAT301 | Probability and Statistics | 3-0-0-3 | MAT202 |
| V | MEC301 | Fluid Mechanics | 3-0-0-3 | MEC201 |
| V | ECE401 | Signals and Systems | 3-0-0-3 | ECE301 |
| V | CSE401 | Software Engineering | 3-0-0-3 | CSE301 |
| V | LAB501 | Software Engineering Lab | 0-0-2-2 | - |
| VI | MAT302 | Linear Algebra and Numerical Methods | 4-0-0-4 | MAT301 |
| VI | MEC401 | Machine Design | 3-0-0-3 | MEC301 |
| VI | ECE501 | Control Systems | 3-0-0-3 | ECE401 |
| VI | CSE501 | Computer Networks | 3-0-0-3 | CSE401 |
| VI | LAB601 | Computer Networks Lab | 0-0-2-2 | - |
| VII | MAT401 | Advanced Mathematics | 3-0-0-3 | MAT302 |
| VII | MEC501 | Heat Transfer | 3-0-0-3 | MEC401 |
| VII | ECE601 | Microprocessors and Microcontrollers | 3-0-0-3 | ECE501 |
| VII | CSE601 | Artificial Intelligence | 3-0-0-3 | CSE501 |
| VII | LAB701 | AI Lab | 0-0-2-2 | - |
| VIII | MAT402 | Advanced Probability and Stochastic Processes | 3-0-0-3 | MAT401 |
| VIII | MEC601 | Industrial Engineering | 3-0-0-3 | MEC501 |
| VIII | ECE701 | Embedded Systems | 3-0-0-3 | ECE601 |
| VIII | CSE701 | Big Data Analytics | 3-0-0-3 | CSE601 |
| VIII | LAB801 | Big Data Lab | 0-0-2-2 | - |
Advanced departmental electives at Allahabad College of Engineering and Management are designed to deepen students' understanding of specialized fields and prepare them for advanced research or professional roles.
Course: Artificial Intelligence and Machine Learning
This course introduces students to fundamental concepts in AI and ML, including supervised and unsupervised learning, neural networks, deep learning architectures, reinforcement learning, and natural language processing. Students gain hands-on experience with frameworks like TensorFlow and PyTorch, applying these tools to real-world problems.
Course: Cybersecurity and Digital Forensics
This elective covers essential cybersecurity principles, including network security protocols, cryptography, intrusion detection systems, and digital forensics. Students learn to identify vulnerabilities in systems and develop strategies for protecting sensitive data against cyber threats.
Course: Renewable Energy Technologies
Focusing on solar, wind, hydroelectric, and geothermal energy sources, this course explores the design and implementation of renewable power generation systems. Students study energy conversion processes, grid integration, environmental impacts, and economic considerations.
Course: Sustainable Manufacturing Processes
This elective delves into sustainable manufacturing techniques that reduce environmental impact while maintaining productivity. Topics include life cycle assessment, green chemistry, waste minimization, and circular economy principles.
Course: Data Science and Analytics
Students explore data analysis methodologies, statistical modeling, machine learning algorithms, and visualization tools. This course prepares graduates for careers in business intelligence, predictive analytics, and data-driven decision-making.
Course: Materials Science and Nanotechnology
This course examines the properties and applications of advanced materials at nanoscale dimensions. Students study synthesis techniques, characterization methods, and emerging technologies in fields like graphene, carbon nanotubes, and smart polymers.
Course: Biomedical Engineering
Combining engineering principles with medical sciences, this course focuses on designing devices and systems for healthcare applications. Topics include biomechanics, bioinstrumentation, tissue engineering, and medical imaging.
Course: Environmental Impact Assessment
This elective teaches students how to evaluate the environmental consequences of proposed projects or policies. It covers regulatory frameworks, impact mitigation strategies, and sustainable development practices.
Course: Smart Cities and IoT
This course explores the integration of information and communication technologies in urban planning. Students study smart transportation, energy management, public safety, and citizen engagement systems.
Course: Advanced Control Systems
Focusing on modern control theory and applications, this elective covers state-space representation, optimal control, robust control, and adaptive control. Students apply these concepts to robotics, aerospace, and industrial automation.
The department's philosophy on project-based learning emphasizes experiential education that bridges theory and practice. Students engage in mini-projects during the second and third years, followed by a final-year thesis or capstone project.
Mini-projects are assigned based on student interests and faculty expertise, allowing students to explore specific domains within their discipline. These projects typically last 6–8 weeks and involve research, experimentation, and documentation.
The final-year thesis/capstone project is a comprehensive endeavor that requires students to apply all acquired knowledge to solve an open-ended problem or develop an innovative solution. Projects are selected in consultation with faculty mentors who guide students through the process from conception to completion.
Evaluation criteria include technical competency, creativity, presentation skills, and adherence to ethical standards. Students must present their work publicly and defend it before a panel of experts.
