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    Scholarships & exams

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

    Duration

    4 Years

    Bachelor of Computer Science

    Gyan Ganga College of Technology
    Duration
    4 Years
    Bachelor of Computer Science UG OFFLINE

    Duration

    4 Years

    Bachelor of Computer Science

    Gyan Ganga College of Technology
    Duration
    Apply

    Fees

    N/A

    Placement

    92.0%

    Avg Package

    ₹4,50,000

    Highest Package

    ₹8,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Bachelor of Computer Science
    UG
    OFFLINE

    Fees

    N/A

    Placement

    92.0%

    Avg Package

    ₹4,50,000

    Highest Package

    ₹8,00,000

    Seats

    1,200

    Students

    1,200

    ApplyCollege

    Seats

    1,200

    Students

    1,200

    Curriculum

    Course Structure Overview

    The Bachelor of Computer Science program at Gyan Ganga College of Technology is meticulously structured over eight semesters, with each semester designed to build upon previously acquired knowledge and skills. The curriculum integrates foundational sciences, core engineering principles, and advanced specializations tailored to individual career aspirations.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    ICS101Introduction to Programming3-0-0-3-
    ICS102Discrete Mathematics4-0-0-4-
    ICS103Physics for Engineers3-0-0-3-
    ICS104Chemistry for Engineers3-0-0-3-
    ICS105English for Technical Communication2-0-0-2-
    ICS106Introduction to Computer Science2-0-0-2-
    IICS201Data Structures and Algorithms3-0-0-3CS101
    IICS202Object-Oriented Programming with Java3-0-0-3CS101
    IICS203Computer Organization and Architecture3-0-0-3CS103
    IICS204Database Systems3-0-0-3CS201
    IICS205Linear Algebra and Calculus4-0-0-4-
    IIICS301Operating Systems3-0-0-3CS201, CS202
    IIICS302Computer Networks3-0-0-3CS203
    IIICS303Software Engineering Principles3-0-0-3CS202
    IIICS304Probability and Statistics4-0-0-4CS205
    IIICS305Human-Computer Interaction3-0-0-3CS106
    IVCS401Artificial Intelligence and Machine Learning3-0-0-3CS301, CS304
    IVCS402Cybersecurity Fundamentals3-0-0-3CS302
    IVCS403Web Development and Databases3-0-0-3CS204, CS202
    IVCS404Mobile Application Development3-0-0-3CS202
    IVCS405Data Mining and Big Data Analytics3-0-0-3CS304, CS301
    VCS501Advanced Algorithms and Complexity3-0-0-3CS201
    VCS502Distributed Systems3-0-0-3CS301, CS302
    VCS503Cloud Computing and DevOps3-0-0-3CS301, CS302
    VCS504Computer Vision and Image Processing3-0-0-3CS401, CS304
    VCS505Internet of Things (IoT) and Embedded Systems3-0-0-3CS302, CS303
    VICS601Research Methodology and Thesis Writing2-0-0-2-
    VICS602Special Topics in Computer Science3-0-0-3CS401, CS402
    VICS603Capstone Project - Phase I2-0-0-2-
    VIICS701Capstone Project - Phase II4-0-0-4CS603
    VIICS702Advanced Cybersecurity Techniques3-0-0-3CS402
    VIIICS801Final Thesis and Presentation4-0-0-4CS701
    VIIICS802Internship/Co-op Training3-0-0-3-

    Advanced Departmental Electives

    Departmental electives are offered to provide depth and specialization in various domains of computer science. These courses are designed to allow students to explore advanced topics based on their interests and career goals.

    • Advanced Artificial Intelligence and Machine Learning: This course explores deep learning architectures, reinforcement learning, natural language processing, and computer vision techniques used in modern AI applications.
    • Cybersecurity and Ethical Hacking: Students learn about network security, cryptography, penetration testing, and incident response strategies through hands-on labs and real-world simulations.
    • Data Mining and Big Data Analytics: Focuses on extracting meaningful insights from large datasets using tools like Apache Spark, Hadoop, and Python-based analytics libraries.
    • Software Testing and Quality Assurance: Covers software testing methodologies, automation frameworks, continuous integration pipelines, and quality metrics in agile development environments.
    • Cloud Computing and DevOps: Explores cloud infrastructure management, containerization technologies (Docker, Kubernetes), CI/CD pipelines, and infrastructure as code practices.
    • Human-Computer Interaction and User Experience Design: Combines principles of psychology, design theory, and usability research to create intuitive interfaces for digital products.
    • Internet of Things (IoT) and Embedded Systems: Teaches students how to build and program embedded systems for IoT applications using microcontrollers and wireless communication protocols.
    • Game Development and Interactive Media: Provides a comprehensive overview of game design, 3D modeling, animation, physics engines, and game engine architecture using Unity and Unreal Engine.
    • Quantitative Finance and Algorithmic Trading: Introduces students to financial markets, derivatives pricing models, risk management, and algorithmic trading strategies using Python and R.
    • Distributed Systems and Microservices Architecture: Focuses on designing scalable distributed systems, service-oriented architectures, and implementing microservices using modern frameworks like Spring Boot and Node.js.

    Project-Based Learning Philosophy

    Our department emphasizes project-based learning as a core component of the educational experience. Students begin working on small-scale projects from their first semester to develop practical skills and apply theoretical concepts in real-world scenarios.

    Mini-projects are assigned during the second and third years, allowing students to explore specific areas within computer science under faculty guidance. These projects are typically completed in groups of 2-4 students and involve research, design, implementation, and documentation phases.

    The final-year thesis/capstone project is a significant undertaking that spans two semesters. Students select a topic related to their specialization area and work closely with a faculty mentor to conduct original research or develop an innovative solution. The evaluation criteria include the novelty of the approach, technical depth, presentation quality, and overall contribution to the field.

    Students have access to dedicated project spaces within the labs, along with resources such as cloud computing credits, software licenses, and mentorship from senior researchers and industry professionals.