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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Computer Applications

    Malwanchal University Indore
    Duration
    4 Years
    Computer Applications UG OFFLINE

    Duration

    4 Years

    Computer Applications

    Malwanchal University Indore
    Duration
    Apply

    Fees

    ₹16,04,000

    Placement

    92.0%

    Avg Package

    ₹8,00,000

    Highest Package

    ₹15,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Computer Applications
    UG
    OFFLINE

    Fees

    ₹16,04,000

    Placement

    92.0%

    Avg Package

    ₹8,00,000

    Highest Package

    ₹15,00,000

    Seats

    200

    Students

    2,000

    ApplyCollege

    Seats

    200

    Students

    2,000

    Curriculum

    Curriculum

    The Computer Applications program at Malwanchal University Indore is meticulously designed to provide students with a comprehensive understanding of modern computing principles and technologies. The curriculum spans eight semesters, integrating theoretical knowledge with practical applications through hands-on experiences and industry-relevant projects.

    SemesterCourse CodeCourse TitleCredit (L-T-P-C)Prerequisites
    1CS101Introduction to Programming3-0-0-3-
    1MA101Calculus I4-0-0-4-
    1PH101Physics for Computer Science3-0-0-3-
    1CH101Chemistry for Engineering3-0-0-3-
    1EC101Electrical and Electronics Fundamentals3-0-0-3-
    1HS101Communication Skills2-0-0-2-
    2CS201Data Structures and Algorithms4-0-0-4CS101
    2MA201Calculus II4-0-0-4MA101
    2PH201Modern Physics and Applications3-0-0-3PH101
    2CH201Organic Chemistry3-0-0-3CH101
    2EC201Digital Electronics3-0-0-3EC101
    2HS201English Literature2-0-0-2-
    3CS301Object-Oriented Programming4-0-0-4CS201
    3MA301Probability and Statistics3-0-0-3MA201
    3PH301Quantum Physics3-0-0-3PH201
    3CH301Inorganic Chemistry3-0-0-3CH201
    3EC301Signals and Systems3-0-0-3EC201
    3HS301Cultural Studies2-0-0-2-
    4CS401Database Management Systems3-0-0-3CS301
    4MA401Differential Equations3-0-0-3MA301
    4PH401Nuclear Physics3-0-0-3PH301
    4CH401Physical Chemistry3-0-0-3CH301
    4EC401Control Systems3-0-0-3EC301
    4HS401History of Science2-0-0-2-
    5CS501Software Engineering3-0-0-3CS401
    5MA501Linear Algebra3-0-0-3MA401
    5PH501Optics and Spectroscopy3-0-0-3PH401
    5CH501Chemistry Lab Practical0-0-2-1CH401
    5EC501Electromagnetic Fields3-0-0-3EC401
    5HS501Philosophy of Science2-0-0-2-
    6CS601Operating Systems3-0-0-3CS501
    6MA601Numerical Methods3-0-0-3MA501
    6PH601Atomic Physics3-0-0-3PH501
    6CH601Organic Chemistry Lab Practical0-0-2-1CH501
    6EC601Microprocessors and Microcontrollers3-0-0-3EC501
    6HS601Political Science2-0-0-2-
    7CS701Network Security3-0-0-3CS601
    7MA701Complex Analysis3-0-0-3MA601
    7PH701Relativity and Cosmology3-0-0-3PH601
    7CH701Inorganic Chemistry Lab Practical0-0-2-1CH601
    7EC701Antennas and Wave Propagation3-0-0-3EC601
    7HS701Sociology of Technology2-0-0-2-
    8CS801Advanced Topics in AI3-0-0-3CS701
    8MA801Advanced Calculus3-0-0-3MA701
    8PH801Quantum Mechanics3-0-0-3PH701
    8CH801Physical Chemistry Lab Practical0-0-2-1CH701
    8EC801Power Electronics3-0-0-3EC701
    8HS801Ethics in Computing2-0-0-2-
    1CS102Programming Lab0-0-2-1CS101
    2CS202Data Structures and Algorithms Lab0-0-2-1CS201
    3CS302Object-Oriented Programming Lab0-0-2-1CS301
    4CS402Database Management Systems Lab0-0-2-1CS401
    5CS502Software Engineering Lab0-0-2-1CS501
    6CS602Operating Systems Lab0-0-2-1CS601
    7CS702Network Security Lab0-0-2-1CS701
    8CS802Advanced AI Project Lab0-0-2-1CS801

    Advanced Departmental Electives:

    • Deep Learning with TensorFlow: This course explores advanced neural network architectures, including convolutional networks, recurrent networks, and transformers. Students implement models using TensorFlow 2.x and gain experience with real-world datasets in computer vision, natural language processing, and speech recognition.
    • Cloud Computing and DevOps: Designed to prepare students for cloud-native development, this course covers containerization with Docker, orchestration with Kubernetes, automation tools like Jenkins, and cloud platforms such as AWS, Azure, and Google Cloud. Practical labs involve deploying scalable applications on these platforms.
    • Cybersecurity and Ethical Hacking: Students learn about network security protocols, cryptography, penetration testing, incident response, and compliance frameworks. The course includes hands-on labs using tools like Wireshark, Metasploit, and Kali Linux to simulate real-world scenarios.
    • Web Technologies and Mobile Development: This elective covers modern web development frameworks (React.js, Node.js) and mobile app creation using cross-platform solutions like React Native and Flutter. Students build full-stack applications and deploy them on cloud servers.
    • Data Science and Machine Learning: Focusing on statistical modeling, data visualization, and predictive analytics, this course uses Python libraries such as scikit-learn, pandas, numpy, and matplotlib. Projects involve analyzing large datasets and building machine learning models for business applications.
    • Human-Computer Interaction: This track integrates psychology, design thinking, and interaction design principles to create intuitive user interfaces. Students study usability testing, prototyping, accessibility standards, and user-centered design methodologies through practical exercises.
    • Embedded Systems Design: Students explore microcontroller programming, sensor integration, real-time operating systems, and wireless communication protocols. The course includes building embedded systems using Raspberry Pi, Arduino, and FPGAs.
    • Game Development: Covering game design principles, 3D modeling, animation techniques, and scripting languages like C++ and Unity, this elective allows students to create interactive media projects and collaborate with industry partners on game prototypes.
    • Quantum Computing Fundamentals: Introducing quantum mechanics concepts and quantum algorithms, this course prepares students for future developments in quantum computing. Labs involve programming simple quantum circuits using Qiskit and simulating quantum phenomena.
    • Blockchain Technologies: This elective explores blockchain architecture, smart contracts, decentralized applications (dApps), and cryptocurrency systems. Students build blockchain-based projects using Ethereum and Hyperledger frameworks.

    The department's philosophy on project-based learning emphasizes experiential education, where students work on real-world challenges throughout their academic journey. Mini-projects are assigned in the third and fourth semesters, focusing on specific technologies or domains such as web development, mobile apps, data analysis, and cybersecurity.

    Final-year projects require students to propose and execute a comprehensive solution addressing a societal or industrial challenge. They select mentors from faculty members based on their research interests and project proposals. The evaluation criteria include innovation, technical implementation, documentation quality, presentation skills, and peer feedback.