Collegese

Welcome to Collegese! Sign in →

Collegese

    Search colleges and courses

    Search and navigate to colleges and courses

    Start your journey

    Ready to find your dream college?

    Join thousands of students making smarter education decisions.

    Watch How It WorksGet Started

    Discover

    Browse & filter colleges

    Compare

    Side-by-side analysis

    Explore

    Detailed course info

    Collegese

    India's education marketplace helping students discover the right colleges, compare courses, and build careers they deserve.

    © 2026 Collegese. All rights reserved. A product of Nxthub Consulting Pvt. Ltd.

    Apply

    Scholarships & exams

    support@collegese.com
    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Bachelor of Technology

    Aligarh College of Engineering and Technology
    Duration
    4 Years
    Bachelor of Technology UG OFFLINE

    Duration

    4 Years

    Bachelor of Technology

    Aligarh College of Engineering and Technology
    Duration
    Apply

    Fees

    ₹1,20,000

    Placement

    94.0%

    Avg Package

    ₹5,50,000

    Highest Package

    ₹80,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Bachelor of Technology
    UG
    OFFLINE

    Fees

    ₹1,20,000

    Placement

    94.0%

    Avg Package

    ₹5,50,000

    Highest Package

    ₹80,00,000

    Seats

    120

    Students

    1,500

    ApplyCollege

    Seats

    120

    Students

    1,500

    Curriculum

    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.