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    Scholarships & exams

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

    Duration

    4 Years

    Computer Applications

    M S Ramaiah University of Applied Sciences Bangalore
    Duration
    4 Years
    Computer Applications UG OFFLINE

    Duration

    4 Years

    Computer Applications

    M S Ramaiah University of Applied Sciences Bangalore
    Duration
    Apply

    Fees

    N/A

    Placement

    92.0%

    Avg Package

    ₹5,20,000

    Highest Package

    ₹9,50,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Computer Applications
    UG
    OFFLINE

    Fees

    N/A

    Placement

    92.0%

    Avg Package

    ₹5,20,000

    Highest Package

    ₹9,50,000

    Seats

    150

    Students

    300

    ApplyCollege

    Seats

    150

    Students

    300

    Curriculum

    Comprehensive Course Listing by Semester

    SemesterCourse CodeCourse TitleCredit Structure (L-T-P-C)Prerequisites
    1CS101Engineering Mathematics I3-0-0-3-
    1CS102Physics for Engineers3-0-0-3-
    1CS103Introduction to Programming2-0-2-2-
    1CS104Computer Organization and Architecture3-0-0-3-
    1CS105English for Engineers2-0-0-2-
    1CS106Lab: Introduction to Programming0-0-3-1-
    2CS201Engineering Mathematics II3-0-0-3CS101
    2CS202Data Structures and Algorithms3-0-0-3CS103
    2CS203Object-Oriented Programming3-0-0-3CS103
    2CS204Digital Logic Design3-0-0-3-
    2CS205Electrical Circuits and Networks3-0-0-3-
    2CS206Lab: Data Structures and Algorithms0-0-3-1CS202
    3CS301Database Management Systems3-0-0-3CS202
    3CS302Software Engineering3-0-0-3CS203
    3CS303Computer Networks3-0-0-3CS204
    3CS304Operating Systems3-0-0-3CS203
    3CS305Probability and Statistics3-0-0-3CS101
    3CS306Lab: Database Management Systems0-0-3-1CS301
    4CS401Design and Analysis of Algorithms3-0-0-3CS202
    4CS402Web Technologies3-0-0-3CS203
    4CS403Computer Graphics and Multimedia3-0-0-3CS203
    4CS404Human Computer Interaction3-0-0-3-
    4CS405Mobile Computing3-0-0-3CS203
    4CS406Lab: Web Technologies0-0-3-1CS402
    5CS501Artificial Intelligence3-0-0-3CS202, CS301
    5CS502Cybersecurity Fundamentals3-0-0-3CS204
    5CS503Data Mining and Warehousing3-0-0-3CS301
    5CS504Cloud Computing3-0-0-3CS204
    5CS505Software Testing3-0-0-3CS302
    5CS506Lab: AI and Machine Learning0-0-3-1CS501
    6CS601Advanced Web Development3-0-0-3CS402
    6CS602DevOps and CI/CD3-0-0-3CS203
    6CS603Internet of Things (IoT)3-0-0-3CS204
    6CS604Mobile App Development3-0-0-3CS405
    6CS605Game Development3-0-0-3-
    6CS606Lab: Mobile App Development0-0-3-1CS604
    7CS701Research Methodology2-0-0-2-
    7CS702Capstone Project - I3-0-0-3CS501, CS601
    7CS703Internship Preparation2-0-0-2-
    7CS704Special Topics in Computer Applications3-0-0-3-
    8CS801Capstone Project - II6-0-0-6CS702
    8CS802Professional Practices2-0-0-2-
    8CS803Elective I: AI & ML3-0-0-3CS501
    8CS804Elective II: Cybersecurity3-0-0-3CS502
    8CS805Elective III: Data Science3-0-0-3CS301
    8CS806Lab: Specialized Electives0-0-3-1-

    Detailed Course Descriptions for Departmental Electives

    Artificial Intelligence and Machine Learning: This course introduces students to fundamental concepts in AI, including search algorithms, knowledge representation, reasoning, planning, and machine learning techniques. Students learn how to build intelligent systems using neural networks, decision trees, clustering, classification, and regression models. The course emphasizes practical implementation through Python-based labs and projects.

    Cybersecurity Fundamentals: This elective covers the principles of network security, cryptographic protocols, secure coding practices, risk management, and incident response strategies. Students gain hands-on experience with firewalls, intrusion detection systems, penetration testing tools, and compliance frameworks like ISO 27001 and NIST.

    Data Mining and Warehousing: Students explore techniques for extracting patterns from large datasets, including association rule mining, clustering, classification, and prediction. The course includes practical sessions on SQL, Python libraries like Pandas and Scikit-Learn, and data visualization tools such as Tableau.

    Cloud Computing: This course delves into cloud service models (IaaS, PaaS, SaaS), deployment architectures, virtualization technologies, and major platforms like AWS, Azure, and GCP. Practical labs involve deploying applications on these platforms and managing resources efficiently.

    Advanced Web Development: Building upon basic web technologies, this course explores modern frameworks like React, Angular, Node.js, and RESTful APIs. Students learn to develop scalable web applications with user authentication, database integration, and performance optimization techniques.

    DevOps and CI/CD: This elective focuses on automating software delivery processes through continuous integration and deployment practices. Topics include version control (Git), containerization (Docker), orchestration (Kubernetes), monitoring (Prometheus), and infrastructure as code (Terraform).

    Internet of Things (IoT): Students study sensor networks, embedded systems programming, communication protocols (WiFi, Bluetooth, Zigbee), and edge computing. Practical labs involve building IoT devices using Raspberry Pi, Arduino, and microcontrollers.

    Mobile App Development: This course covers both native and cross-platform mobile app development using technologies like Flutter, React Native, Swift, Kotlin, and Android Studio. Students learn to design user interfaces, integrate APIs, manage data persistence, and publish apps on app stores.

    Game Development: Using Unity 3D engine, students learn game architecture, scripting, animation, sound design, UI/UX principles, and multiplayer networking. Projects include building interactive games with physics engines, AI behaviors, and immersive environments.

    Human-Computer Interaction (HCI): This elective explores how users interact with computer systems and how to design interfaces that are intuitive, efficient, and accessible. Topics include usability testing, user research, prototyping, accessibility standards (WCAG), and cognitive load theory.

    Project-Based Learning Philosophy

    Our department strongly believes in project-based learning as a core component of the educational experience. The structure encourages students to engage with real-world challenges and develop practical solutions using their academic knowledge.

    The mandatory mini-projects span two semesters, starting from the third year. Each project team consists of 4-6 students, guided by faculty mentors. Projects are evaluated based on technical merit, creativity, presentation quality, and peer feedback. Students must submit progress reports, deliverables, and final presentations.

    The final-year thesis/capstone project is an individual or group endeavor that spans the entire eighth semester. It requires students to identify a relevant problem, propose a solution, implement it, and document the process in a comprehensive report. Faculty mentors guide teams throughout the research and development phases, ensuring alignment with industry standards.

    Project selection involves multiple rounds of proposal submission, faculty review, and stakeholder consultation. Students can choose from proposed projects by faculty members or submit their own ideas for approval. This approach fosters innovation, encourages collaboration, and ensures relevance to current technological trends.