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

    Duration

    4 Years

    Computer Science

    Maulana Azad University, Jodhpur
    Duration
    4 Years
    Computer Science UG OFFLINE

    Duration

    4 Years

    Computer Science

    Maulana Azad University, Jodhpur
    Duration
    Apply

    Fees

    ₹1,70,000

    Placement

    97.5%

    Avg Package

    ₹14,90,000

    Highest Package

    ₹27,20,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Computer Science
    UG
    OFFLINE

    Fees

    ₹1,70,000

    Placement

    97.5%

    Avg Package

    ₹14,90,000

    Highest Package

    ₹27,20,000

    Seats

    120

    Students

    250

    ApplyCollege

    Seats

    120

    Students

    250

    Curriculum

    Curriculum Overview

    The curriculum at Maulana Azad University Jodhpur for Computer Science is designed to provide a robust foundation in both theoretical and practical aspects of computing. It balances core disciplines with specialized electives, ensuring students are well-prepared for diverse career paths.

    The program spans eight semesters, each carefully structured to build upon previous knowledge while introducing new concepts. From foundational courses in mathematics and programming to advanced topics in artificial intelligence and cybersecurity, the curriculum reflects the latest trends in the field.

    Course Structure

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    ICS101Introduction to Programming3-0-2-4None
    IMA101Mathematics for Computer Science3-0-0-3None
    IPH101Physics for Engineers3-0-0-3None
    ICH101Chemistry for Engineers3-0-0-3None
    IEC101Electrical Circuits and Electronics3-0-0-3None
    IHS101English for Communication2-0-0-2None
    ICS102Programming Laboratory0-0-4-2CS101
    IMA102Discrete Mathematics3-0-0-3MA101
    IICS201Data Structures and Algorithms3-0-2-4CS101
    IIMA201Probability and Statistics3-0-0-3MA101
    IIPH201Modern Physics3-0-0-3PH101
    IICH201Organic Chemistry3-0-0-3CH101
    IIEC201Digital Electronics3-0-0-3EC101
    IIHS201Cultural Studies2-0-0-2None
    IICS202Lab: Data Structures and Algorithms0-0-4-2CS201
    IIICS301Database Management Systems3-0-2-4CS201
    IIIMA301Linear Algebra and Numerical Methods3-0-0-3MA102
    IIIPH301Optics and Thermodynamics3-0-0-3PH201
    IIICH301Inorganic Chemistry3-0-0-3CH201
    IIIEC301Signals and Systems3-0-0-3EC201
    IIICS302Operating Systems3-0-2-4CS201
    IIICS303Lab: Operating Systems0-0-4-2CS302
    IVCS401Computer Networks3-0-2-4CS302
    IVMA401Differential Equations3-0-0-3MA301
    IVPH401Quantum Physics3-0-0-3PH301
    IVCH401Physical Chemistry3-0-0-3CH301
    IVEC401Analog Electronics3-0-0-3EC301
    IVCS402Software Engineering3-0-2-4CS301
    IVCS403Lab: Software Engineering0-0-4-2CS402
    VCS501Artificial Intelligence3-0-2-4CS402
    VMA501Advanced Calculus3-0-0-3MA401
    VPH501Electromagnetism3-0-0-3PH401
    VCH501Chemistry of Materials3-0-0-3CH401
    VEC501Microprocessors and Microcontrollers3-0-0-3EC401
    VCS502Cybersecurity Fundamentals3-0-2-4CS401
    VCS503Lab: Cybersecurity0-0-4-2CS502
    VICS601Machine Learning3-0-2-4CS501
    VIMA601Stochastic Processes3-0-0-3MA501
    VIPH601Condensed Matter Physics3-0-0-3PH501
    VICH601Organometallic Chemistry3-0-0-3CH501
    VIEC601Control Systems3-0-0-3EC501
    VICS602Big Data Analytics3-0-2-4CS501
    VICS603Lab: Big Data Analytics0-0-4-2CS602
    VIICS701Advanced Computer Architecture3-0-2-4CS501
    VIIMA701Mathematical Modeling3-0-0-3MA601
    VIIPH701Nuclear Physics3-0-0-3PH601
    VIICH701Physical Organic Chemistry3-0-0-3CH601
    VIIEC701Communication Systems3-0-0-3EC601
    VIICS702Human Computer Interaction3-0-2-4CS601
    VIICS703Lab: Human Computer Interaction0-0-4-2CS702
    VIIICS801Capstone Project0-0-8-8All previous semesters
    VIIIMA801Research Methodology3-0-0-3None
    VIIIPH801Quantum Computing3-0-0-3PH701
    VIIICH801Chemical Biology3-0-0-3CH701
    VIIIEC801Signal Processing3-0-0-3EC701
    VIIICS802Entrepreneurship and Innovation2-0-0-2None
    VIIICS803Internship0-0-6-6None

    Advanced Departmental Electives

    The department offers a wide array of advanced elective courses designed to deepen students' understanding of specialized areas within Computer Science:

    • Deep Learning for Vision and Language: This course explores the architecture and implementation of neural networks for image recognition, natural language processing, and multimodal tasks. Students learn to build models using frameworks like TensorFlow and PyTorch, applying them to real-world datasets.
    • Advanced Cryptography and Network Security: Covering advanced topics in cryptography including elliptic curve encryption, hash functions, and secure protocols. The course also examines current threats and defensive strategies used by modern organizations.
    • Cloud Computing and DevOps: Students learn about cloud platforms like AWS, Azure, and GCP, along with automation tools such as Jenkins, Docker, and Kubernetes. The curriculum includes designing scalable architectures and implementing CI/CD pipelines.
    • Human-Computer Interaction Design: Focused on user-centered design principles, this course teaches students to create interfaces that are intuitive, accessible, and effective. It covers usability testing, prototyping techniques, and cognitive psychology aspects of interaction design.
    • Internet of Things (IoT) Systems: This course introduces students to sensor networks, embedded systems programming, and wireless communication protocols used in IoT applications. Practical labs involve building IoT prototypes using Raspberry Pi and Arduino boards.
    • Game Development Fundamentals: Students learn the entire game development lifecycle from concept creation to implementation using Unity and Unreal Engine. The course includes scripting, asset design, and performance optimization techniques.
    • Mobile Application Development: This course focuses on developing cross-platform mobile applications for iOS and Android using technologies like React Native and Flutter. It covers UI/UX design, backend integration, and app deployment strategies.
    • Data Mining and Knowledge Discovery: Students explore algorithms for extracting patterns from large datasets. Topics include clustering, classification, association rules, and anomaly detection, with practical applications in business intelligence and scientific research.
    • Quantum Computing Fundamentals: Introducing students to the principles of quantum mechanics and how they apply to computing. The course covers quantum gates, superposition, entanglement, and current developments in quantum algorithms and hardware.
    • Computational Biology: This interdisciplinary course combines computer science with biology, focusing on bioinformatics tools and computational methods used in genomics, proteomics, and drug discovery.

    Project-Based Learning Philosophy

    The department's philosophy on project-based learning emphasizes hands-on experience and real-world problem-solving. Mini-projects are assigned at the end of each semester, allowing students to apply theoretical knowledge to practical scenarios. These projects are evaluated based on innovation, implementation quality, and presentation skills.

    The final-year capstone project is a significant component of the curriculum, requiring students to work in teams on an industry-relevant problem. Students select their projects based on personal interest and faculty mentorship availability. The evaluation criteria include technical depth, originality, documentation, and oral defense. Projects are often presented at national and international conferences, providing exposure to real-world applications.