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    Scholarships & exams

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

    Duration

    4 Years

    Computer Science

    Presidency University Bangalore
    Duration
    4 Years
    Computer Science UG OFFLINE

    Duration

    4 Years

    Computer Science

    Presidency University Bangalore
    Duration
    Apply

    Fees

    ₹5,00,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹9,50,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Computer Science
    UG
    OFFLINE

    Fees

    ₹5,00,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹9,50,000

    Seats

    200

    Students

    600

    ApplyCollege

    Seats

    200

    Students

    600

    Curriculum

    Comprehensive Curriculum Overview

    The Computer Science program at Presidency University Bangalore is designed to provide students with a well-rounded education that combines theoretical knowledge with practical application. The curriculum is structured across eight semesters, with each semester building upon the previous one to ensure a progressive learning experience.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1CS101Engineering Mathematics I3-1-0-4-
    1CS102Physics for Computer Science3-1-0-4-
    1CS103Introduction to Programming3-1-0-4-
    1CS104Computer Fundamentals2-0-0-2-
    1CS105English for Technical Communication2-0-0-2-
    2CS201Engineering Mathematics II3-1-0-4CS101
    2CS202Chemistry for Computer Science3-1-0-4-
    2CS203Data Structures and Algorithms3-1-0-4CS103
    2CS204Object Oriented Programming3-1-0-4CS103
    2CS205Computer Organization and Architecture3-1-0-4-
    3CS301Probability and Statistics3-1-0-4CS201
    3CS302Operating Systems3-1-0-4CS204, CS205
    3CS303Database Management Systems3-1-0-4CS204
    3CS304Software Engineering3-1-0-4CS204
    3CS305Microprocessors and Microcontrollers3-1-0-4CS205
    4CS401Design and Analysis of Algorithms3-1-0-4CS203
    4CS402Computer Networks3-1-0-4CS205, CS302
    4CS403Artificial Intelligence and Machine Learning3-1-0-4CS301, CS203
    4CS404Cybersecurity Fundamentals3-1-0-4CS205
    4CS405Data Mining and Big Data Analytics3-1-0-4CS301, CS303
    5CS501Advanced Algorithms3-1-0-4CS401
    5CS502Distributed Systems3-1-0-4CS402
    5CS503Human Computer Interaction3-1-0-4CS304
    5CS504Cloud Computing3-1-0-4CS402, CS302
    5CS505Internet of Things3-1-0-4CS305
    6CS601Research Methodology and Project Management2-0-0-2-
    6CS602Special Topics in Computer Science3-1-0-4-
    6CS603Capstone Project I2-0-0-2-
    6CS604Mini Project I2-0-0-2-
    7CS701Advanced Machine Learning3-1-0-4CS403
    7CS702Security Architecture and Cryptography3-1-0-4CS404
    7CS703Data Science and Visualization3-1-0-4CS501, CS405
    7CS704Embedded Systems3-1-0-4CS305
    7CS705Capstone Project II2-0-0-2-
    8CS801Final Year Thesis4-0-0-4-
    8CS802Internship4-0-0-4-

    Advanced Departmental Elective Courses

    The department offers a wide range of advanced departmental elective courses that allow students to specialize in their areas of interest while maintaining the flexibility to explore diverse computing domains.

    Deep Learning is one such course that provides students with an in-depth understanding of neural networks, convolutional networks, recurrent networks, and transformers. The course emphasizes practical implementation using frameworks like TensorFlow and PyTorch, preparing students for research and development roles in AI.

    Natural Language Processing (NLP) explores the intersection of computational linguistics and artificial intelligence, focusing on techniques such as sentiment analysis, language modeling, and machine translation. Students work on real-world datasets to build applications that understand and generate human language.

    Computer Vision is a course that delves into image processing, object detection, facial recognition, and image segmentation. Students learn to implement algorithms using libraries like OpenCV and use deep learning models for visual recognition tasks.

    Reinforcement Learning introduces students to the principles of decision-making in dynamic environments. The course covers Markov Decision Processes, Q-learning, policy gradients, and actor-critic methods, preparing students for careers in autonomous systems and game AI.

    Cryptography and Network Security covers both classical and modern cryptographic techniques, including symmetric and asymmetric encryption, hash functions, and digital signatures. Students learn to implement secure communication protocols and protect against various cyber threats.

    Software Architecture and Design Patterns explores the principles of designing scalable and maintainable software systems. Students study patterns such as MVC, MVVM, microservices architecture, and domain-driven design, preparing them for leadership roles in software development.

    Big Data Technologies introduces students to Hadoop, Spark, and other distributed computing frameworks. The course focuses on processing large datasets efficiently and building data pipelines that can handle real-time streaming data.

    Mobile Application Development covers the principles of designing and developing applications for iOS and Android platforms. Students learn to build cross-platform apps using frameworks like React Native and Flutter, preparing them for mobile development careers.

    Quantum Computing provides an introduction to quantum mechanics and its application in computing. The course covers quantum algorithms, quantum circuits, and simulation techniques, preparing students for the emerging field of quantum information science.

    Distributed Systems and Cloud Computing explores the design and implementation of systems that operate across multiple computers. Students study concepts such as consensus protocols, load balancing, and cloud deployment strategies, preparing them for roles in system architecture and DevOps.

    Project-Based Learning Philosophy

    The Computer Science department at Presidency University Bangalore is committed to project-based learning as a core pedagogical approach. This methodology emphasizes the development of practical skills through real-world problem-solving experiences.

    Mini Projects are introduced in the early semesters and gradually increase in complexity and scope. These projects are designed to help students apply theoretical concepts learned in class to practical scenarios, fostering creativity and innovation.

    The Final Year Thesis or Capstone Project is the culmination of the undergraduate experience. Students work under the guidance of faculty mentors on a substantial research or development project that addresses real-world challenges. This project allows students to demonstrate their mastery of the field and prepares them for post-graduation opportunities in academia or industry.

    Project selection is an important process where students can choose from a list of faculty-led projects or propose their own ideas. The department facilitates this by providing access to research facilities, mentorship, and funding for necessary resources.

    Evaluation criteria for projects are comprehensive, considering factors such as technical competency, innovation, documentation quality, presentation skills, and teamwork. This holistic approach ensures that students develop not just technical skills but also essential soft skills required in professional environments.