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    Scholarships & exams

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

    Duration

    4 Years

    Computer Science

    Bishamber Sahai Institute Of Technology
    Duration
    4 Years
    Computer Science UG OFFLINE

    Duration

    4 Years

    Computer Science

    Bishamber Sahai Institute Of Technology
    Duration
    Apply

    Fees

    ₹12,00,000

    Placement

    94.5%

    Avg Package

    ₹7,50,000

    Highest Package

    ₹25,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Computer Science
    UG
    OFFLINE

    Fees

    ₹12,00,000

    Placement

    94.5%

    Avg Package

    ₹7,50,000

    Highest Package

    ₹25,00,000

    Seats

    150

    Students

    800

    ApplyCollege

    Seats

    150

    Students

    800

    Curriculum

    Course Structure Overview

    The Computer Science program at Bishamber Sahai Institute Of Technology is structured over 8 semesters, with a balanced mix of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is designed to progressively build technical competence while encouraging innovation and critical thinking.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-requisites
    1CS101Introduction to Programming3-0-0-3-
    1CS102Mathematics for Computer Science3-0-0-3-
    1CS103Engineering Graphics2-0-0-2-
    1CS104English for Engineers2-0-0-2-
    1CS105Introduction to Computer Science3-0-0-3-
    2CS201Data Structures and Algorithms3-0-0-3CS101
    2CS202Computer Organization3-0-0-3-
    2CS203Digital Electronics3-0-0-3-
    2CS204Database Systems3-0-0-3CS101
    2CS205Discrete Mathematics3-0-0-3CS102
    3CS301Operating Systems3-0-0-3CS201
    3CS302Computer Networks3-0-0-3CS202
    3CS303Software Engineering3-0-0-3CS201
    3CS304Web Technologies3-0-0-3CS201
    3CS305Object-Oriented Programming3-0-0-3CS101
    4CS401Machine Learning3-0-0-3CS201, CS205
    4CS402Cybersecurity3-0-0-3CS302
    4CS403Data Mining and Analytics3-0-0-3CS201, CS205
    4CS404Distributed Systems3-0-0-3CS301, CS302
    4CS405Compiler Design3-0-0-3CS201
    5CS501Artificial Intelligence3-0-0-3CS401, CS303
    5CS502Human-Computer Interaction3-0-0-3CS303
    5CS503Mobile Application Development3-0-0-3CS304
    5CS504Internet of Things3-0-0-3CS203
    5CS505Cloud Computing3-0-0-3CS404
    6CS601Advanced Algorithms3-0-0-3CS201, CS301
    6CS602Big Data Technologies3-0-0-3CS403
    6CS603Quantitative Finance3-0-0-3CS205, CS403
    6CS604Game Development3-0-0-3CS503
    6CS605Research Methodology3-0-0-3-
    7CS701Capstone Project I0-0-6-3CS501, CS502
    7CS702Mini Project I0-0-3-2CS401
    7CS703Internship0-0-0-6-
    8CS801Capstone Project II0-0-6-3CS701
    8CS802Mini Project II0-0-3-2CS702
    8CS803Final Thesis0-0-0-6CS605

    Advanced Departmental Electives

    The department offers a range of advanced elective courses that allow students to specialize in specific domains and gain deeper insights into emerging technologies. These courses are taught by faculty members who are active researchers and industry experts.

    • Deep Learning: This course explores neural networks, convolutional networks, recurrent networks, and transformer architectures. Students learn to implement models using TensorFlow and PyTorch and apply them to real-world problems such as image classification and natural language understanding.
    • Computer Vision: The course covers fundamental concepts in computer vision including image processing, feature extraction, object detection, and segmentation. Students work on projects involving facial recognition, autonomous vehicles, and medical imaging.
    • Natural Language Processing (NLP): This course introduces students to language modeling, sentiment analysis, machine translation, and text summarization. The curriculum includes hands-on labs using BERT, GPT, and other transformer-based models.
    • Reinforcement Learning: Students learn about Markov decision processes, Q-learning, policy gradients, and deep reinforcement learning techniques. Projects involve training agents to play games or control robotic systems.
    • Quantum Computing: An introduction to quantum algorithms, quantum circuits, and quantum error correction. The course includes simulations using Qiskit and discusses current developments in the field.
    • Blockchain Technologies: Covers blockchain fundamentals, smart contracts, cryptocurrency mechanisms, and decentralized applications. Students build their own blockchain-based systems and explore real-world use cases.
    • Computer Security: Explores network security, cryptographic protocols, vulnerability assessment, and incident response. The course includes labs on penetration testing and secure coding practices.
    • Big Data Analytics: Focuses on processing large datasets using Hadoop, Spark, and other distributed computing frameworks. Students learn to extract insights from unstructured data sources.
    • Mobile App Development: Teaches students how to design and develop cross-platform mobile applications using Flutter and React Native. The course emphasizes user experience and app performance optimization.
    • Internet of Things (IoT): Covers sensor networks, embedded systems, wireless communication protocols, and edge computing. Students implement IoT solutions for smart homes, agriculture, and healthcare.

    Project-Based Learning Philosophy

    At Bishamber Sahai Institute Of Technology, project-based learning is central to our educational philosophy. We believe that learning occurs best when students engage in meaningful, hands-on experiences that connect theory with practice.

    The program integrates mini-projects throughout the curriculum, starting from the second year. These projects are designed to reinforce concepts learned in lectures and labs while encouraging creativity and teamwork. Students select their own project topics under faculty guidance, ensuring that they align with both personal interests and industry needs.

    The final-year capstone project is a comprehensive endeavor that spans two semesters. Students work closely with faculty mentors to develop innovative solutions to real-world problems. The projects often lead to patents, publications, or startup ventures. Evaluation criteria include technical depth, innovation, presentation skills, and impact on society.

    Faculty members play a pivotal role in guiding students through their projects. Each student is assigned a mentor who provides academic support, helps with research, and connects them with industry professionals when needed. This personalized approach ensures that every student gets the attention required to excel academically and professionally.