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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Bachelor of Technology in Engineering

    Alard University, Pune
    Duration
    4 Years
    Engineering UG OFFLINE

    Duration

    4 Years

    Bachelor of Technology in Engineering

    Alard University, Pune
    Duration
    Apply

    Fees

    ₹2,50,000

    Placement

    94.5%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Engineering
    UG
    OFFLINE

    Fees

    ₹2,50,000

    Placement

    94.5%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    Seats

    180

    Students

    1,800

    ApplyCollege

    Seats

    180

    Students

    1,800

    Curriculum

    Course Structure Overview

    The engineering program at Alard University Pune is structured over eight semesters, with each semester designed to build upon previous knowledge while introducing new concepts and applications. The curriculum emphasizes a balanced blend of theoretical foundations, practical laboratory work, and real-world problem-solving through project-based learning.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    IENG101Engineering Mathematics I3-1-0-4-
    IENG102Physics for Engineers3-1-0-4-
    IENG103Chemistry for Engineers3-1-0-4-
    IENG104Computer Programming2-0-2-3-
    IENG105Engineering Drawing1-0-3-2-
    IENG106English Communication Skills2-0-0-2-
    IENG107Workshop Practice0-0-4-2-
    IIENG201Engineering Mathematics II3-1-0-4ENG101
    IIENG202Basic Electrical Engineering3-1-0-4-
    IIENG203Engineering Mechanics3-1-0-4-
    IIENG204Data Structures and Algorithms3-1-0-4ENG104
    IIENG205Introduction to Materials Science3-1-0-4-
    IIIENG301Engineering Mathematics III3-1-0-4ENG201
    IIIENG302Thermodynamics3-1-0-4ENG202
    IIIENG303Fluid Mechanics3-1-0-4ENG203
    IIIENG304Digital Logic and Computer Organization3-1-0-4ENG104
    IIIENG305Signals and Systems3-1-0-4ENG201
    IVENG401Control Systems3-1-0-4ENG305
    IVENG402Electromagnetic Fields and Waves3-1-0-4ENG202
    IVENG403Probability and Statistics3-1-0-4ENG201
    IVENG404Microprocessors and Microcontrollers3-1-0-4ENG304
    IVENG405Engineering Economics3-1-0-4ENG201
    VENG501Design and Analysis of Algorithms3-1-0-4ENG204
    VENG502Computer Networks3-1-0-4ENG304
    VENG503Software Engineering3-1-0-4ENG204
    VENG504Operating Systems3-1-0-4ENG304
    VENG505Database Management Systems3-1-0-4ENG204
    VIENG601Artificial Intelligence3-1-0-4ENG501
    VIENG602Machine Learning3-1-0-4ENG501
    VIENG603Deep Learning3-1-0-4ENG602
    VIENG604Natural Language Processing3-1-0-4ENG602
    VIENG605Computer Vision3-1-0-4ENG602
    VIIENG701Embedded Systems3-1-0-4ENG404
    VIIENG702Internet of Things3-1-0-4ENG404
    VIIENG703Cybersecurity Fundamentals3-1-0-4ENG502
    VIIENG704Cloud Computing3-1-0-4ENG502
    VIIENG705Big Data Analytics3-1-0-4ENG505
    VIIIENG801Capstone Project0-0-6-6ENG701
    VIIIENG802Research Methodology2-0-0-3-
    VIIIENG803Professional Ethics and Social Responsibility2-0-0-2-
    VIIIENG804Entrepreneurship and Innovation2-0-0-2-
    VIIIENG805Internship0-0-0-3-

    Advanced Departmental Electives

    The program offers a rich selection of advanced departmental electives designed to deepen students' understanding and prepare them for specialized roles in their chosen fields.

    Artificial Intelligence

    This elective explores advanced AI techniques including reinforcement learning, neural architecture search, and generative adversarial networks. Students engage with cutting-edge research papers and implement novel algorithms using Python frameworks like TensorFlow and PyTorch.

    Machine Learning

    This course delves into supervised and unsupervised learning methods, ensemble models, time series forecasting, and advanced optimization techniques. Emphasis is placed on applying ML to real-world problems in finance, healthcare, and automation.

    Deep Learning

    Focusing on deep neural architectures such as CNNs, RNNs, LSTMs, and Transformers, this course teaches students how to design, train, and deploy complex models for image recognition, natural language processing, and audio analysis.

    Natural Language Processing

    This elective covers text preprocessing, sentiment analysis, language modeling, machine translation, and question answering systems. Students build applications using libraries like spaCy and Hugging Face Transformers.

    Computer Vision

    Students learn to detect and classify objects in images, perform image segmentation, and generate synthetic data. Practical applications include autonomous vehicles, medical imaging, and augmented reality systems.

    Embedded Systems

    This course focuses on designing embedded software for microcontrollers, real-time operating systems, and low-power hardware platforms. Students work with ARM Cortex-M series processors and develop IoT-based solutions.

    Internet of Things (IoT)

    Exploring connectivity protocols, sensor integration, edge computing, and cloud integration, this elective prepares students for building scalable IoT ecosystems across industries such as agriculture, manufacturing, and smart cities.

    Cybersecurity Fundamentals

    This course covers network security, cryptography, ethical hacking, and incident response. Students simulate attacks using tools like Kali Linux and learn how to secure enterprise environments from evolving threats.

    Cloud Computing

    Students explore cloud platforms like AWS, Azure, and Google Cloud, learning about virtualization, containerization (Docker, Kubernetes), and serverless computing. Projects involve deploying scalable web applications in the cloud.

    Big Data Analytics

    This elective introduces students to big data technologies such as Hadoop, Spark, and Kafka. Students analyze large datasets using Python and SQL, and gain insights into predictive analytics and data visualization.

    Project-Based Learning Philosophy

    At Alard University Pune, project-based learning is central to the engineering education experience. From semester one, students engage in hands-on projects that bridge theory with practice, reinforcing classroom concepts through real-world applications.

    Mini-Projects

    Each student undertakes two mini-projects during their undergraduate journey—one in the second year and another in the fifth year. These projects are evaluated based on design quality, technical execution, teamwork, and presentation skills.

    Final-Year Capstone Project

    The final-year capstone project is a significant component of the program, requiring students to conceptualize, develop, and present an innovative solution to a real-world challenge. Projects are guided by faculty mentors and often lead to patent filings or startup ventures.

    Project Selection Process

    Students choose projects based on their interests, career aspirations, and available resources. Faculty mentors provide guidance in selecting relevant topics, ensuring alignment with industry needs and academic rigor.