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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Computer Applications

    Shridhar University Pilani
    Duration
    4 Years
    Computer Applications UG OFFLINE

    Duration

    4 Years

    Computer Applications

    Shridhar University Pilani
    Duration
    Apply

    Fees

    ₹3,50,000

    Placement

    92.0%

    Avg Package

    ₹5,00,000

    Highest Package

    ₹8,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Computer Applications
    UG
    OFFLINE

    Fees

    ₹3,50,000

    Placement

    92.0%

    Avg Package

    ₹5,00,000

    Highest Package

    ₹8,00,000

    Seats

    350

    Students

    350

    ApplyCollege

    Seats

    350

    Students

    350

    Curriculum

    Comprehensive Course Structure

    The Computer Applications program at Shridhar University Pilani is structured to provide a well-rounded and progressive learning experience over four years. The curriculum is divided into eight semesters, with a blend of core subjects, departmental electives, science electives, and laboratory sessions. The program emphasizes both theoretical knowledge and practical application, ensuring students are well-prepared for industry demands.

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Pre-requisites
    1CS101Introduction to Programming3-0-0-3None
    1CS102Mathematics for Computer Science3-0-0-3None
    1CS103Physics for Computer Applications3-0-0-3None
    1CS104Chemistry for Computer Science3-0-0-3None
    1CS105English for Technical Communication3-0-0-3None
    1CS106Computer Fundamentals and Programming Lab0-0-3-1None
    2CS201Data Structures and Algorithms3-0-0-3CS101
    2CS202Object-Oriented Programming3-0-0-3CS101
    2CS203Discrete Mathematics3-0-0-3CS102
    2CS204Digital Logic and Computer Organization3-0-0-3CS103
    2CS205Database Management Systems3-0-0-3CS201
    2CS206Data Structures and Algorithms Lab0-0-3-1CS201
    3CS301Operating Systems3-0-0-3CS204
    3CS302Computer Networks3-0-0-3CS204
    3CS303Software Engineering3-0-0-3CS202
    3CS304Design and Analysis of Algorithms3-0-0-3CS201
    3CS305Web Technologies3-0-0-3CS202
    3CS306Software Engineering Lab0-0-3-1CS303
    4CS401Artificial Intelligence3-0-0-3CS304
    4CS402Machine Learning3-0-0-3CS304
    4CS403Cybersecurity3-0-0-3CS302
    4CS404Big Data Analytics3-0-0-3CS305
    4CS405Cloud Computing3-0-0-3CS301
    4CS406AI and ML Lab0-0-3-1CS401
    5CS501Advanced Computer Architecture3-0-0-3CS304
    5CS502Human-Computer Interaction3-0-0-3CS305
    5CS503Mobile Application Development3-0-0-3CS305
    5CS504Internet of Things3-0-0-3CS302
    5CS505Quantitative Finance3-0-0-3CS203
    5CS506Embedded Systems Lab0-0-3-1CS504
    6CS601Research Methodology3-0-0-3CS501
    6CS602Capstone Project3-0-0-3CS501
    6CS603Special Topics in Computer Science3-0-0-3CS501
    6CS604Internship0-0-0-6CS501
    6CS605Final Year Thesis0-0-0-6CS601
    6CS606Capstone Project Lab0-0-3-1CS602

    Advanced Departmental Electives

    The program offers a range of advanced departmental electives designed to provide students with specialized knowledge and skills in emerging areas of computer science. These courses are taught by leading faculty members and are aligned with industry trends and requirements.

    One of the most popular electives is Artificial Intelligence and Machine Learning, which covers topics such as neural networks, deep learning, natural language processing, and computer vision. Students engage in hands-on projects involving real-world datasets and applications in various domains.

    Cybersecurity and Network Defense is another advanced elective that focuses on protecting digital assets and infrastructure from cyber threats. The course covers network security, cryptography, ethical hacking, and risk management, with practical sessions involving simulations and real-world case studies.

    Data Science and Big Data Analytics introduces students to statistical modeling, data visualization, predictive analytics, and machine learning algorithms. Students work on projects involving real-world data from industries such as healthcare, finance, and marketing.

    Web and Mobile Application Development focuses on the design and development of user-friendly applications for web and mobile platforms. Students learn modern frameworks and tools such as React, Angular, Flutter, and Swift, gaining experience in building scalable and secure applications.

    Software Engineering and DevOps covers software architecture, testing, deployment, and continuous integration. Students learn to work in agile environments and collaborate with cross-functional teams.

    Human-Computer Interaction and User Experience Design focuses on creating intuitive and accessible interfaces for digital products. Students study user research, usability testing, and interaction design principles, working on projects that involve designing interfaces for various platforms and technologies.

    Embedded Systems and Internet of Things combines hardware and software to create smart devices and systems. Students explore topics such as microcontrollers, sensors, and real-time systems, preparing them for careers in IoT development and embedded software engineering.

    Quantitative Finance and Computational Modeling is designed for students interested in financial markets and quantitative analysis. The curriculum covers financial modeling, algorithmic trading, risk management, and computational methods in finance, with practical experience through projects involving financial data and market analysis.

    Cloud Computing and Distributed Systems focuses on cloud platforms, virtualization, containerization, and distributed algorithms. Students work on projects involving cloud deployment and system optimization.

    Computer Graphics and Visualization introduces students to 3D modeling, animation, and rendering techniques. The course covers topics such as graphics pipelines, lighting, shading, and real-time rendering, with practical sessions involving industry-standard software tools.

    Project-Based Learning Philosophy

    The department's philosophy on project-based learning is rooted in the belief that practical experience is essential for developing problem-solving skills and real-world competence. The curriculum is designed to provide students with opportunities for hands-on learning and collaborative work throughout their academic journey.

    Mini-projects are introduced in the second year, allowing students to apply theoretical knowledge to practical problems. These projects are typically completed in groups and are evaluated based on technical execution, teamwork, and presentation skills.

    The final-year thesis or capstone project is a significant component of the program, providing students with the opportunity to work on a comprehensive project under the guidance of a faculty mentor. The project is designed to be innovative and impactful, often addressing real-world challenges and contributing to the field of computer science.

    Students are encouraged to select projects that align with their interests and career goals, and they are provided with support and resources to ensure successful completion. The selection process involves discussions with faculty mentors, who help students identify suitable projects and provide guidance throughout the process.

    Evaluation criteria for projects include technical proficiency, creativity, documentation, and presentation. The department also emphasizes the importance of ethical considerations and professional standards in all project work, ensuring that students develop a strong foundation in responsible computing practices.