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    MCA Department

    About

    The Department of Computer Applications was started in the year 2006. The Department offers MCA 2 Years (4 Semesters) with intake of 60. The course offered by the department focuses on preparing students for a global career in computing by enriching the curriculum with the blend of theory and practice. In this era of technological explosion, the department is dedicated to maintaining a high standard of excellence through quality, technology and innovation. The MCA program seeks to prepare students for high level careers in the ever expanding field of Computer Applications.

     

    HOD Message

    faculty_img
    DR. VENKATESHWARLU PURUMULA

    HOD & PROFESSOR

    Welcome to the Department of Master of Computer Applications at Vaageswari College of Engineering. Our mission is to nurture technically skilled, innovative, and ethically strong professionals in the field of computer applications. With a curriculum focused on software development, data analytics, cloud computing, and emerging technologies, we prepare our students to meet the challenges of the ever-evolving IT industry. The department is backed by experienced faculty, modern infrastructure, and strong industry collaborations, ensuring holistic development and career readiness. I extend my heartfelt congratulations to the dedicated faculty and enthusiastic students for their continuous pursuit of excellence and success.

    Contact

    Mobile Number: 9848671900

    Email:mca.hod@vgsek.ac.in

    Laboratories

    Computer Laboratory - 1:

    Sl.No Name of the Equipment Specifications Quantity
      Desktop Computers Acer-Intel Pentium 3260 @3.30GHz,Intel  Chip Set,8GB RAM,500 GB-HDD, Acer ATX Cabinet, Acer LCD-Monitor, Acer Keyboard & Optical Mouse. 32
      System Software Microsoft Windows & GNU 01
      Application Software

    Turbo C, Python, Oracle, JDK

    Eclipse, VMware/Hadoop/Amazon EC2/AWS/My SQL

    01
      LCD - Projector View Sonic PJD5155 DLP Projector 01

     

    Computer Laboratory -2:

    Sl.No Name of the Equipment Specifications Quantity
      Desktop Computers Acer-Intel Pentium 3260 @3.30GHz,Intel  Chip Set,8GB RAM,500 GB-HDD, Acer ATX Cabinet, Acer LCD-Monitor, Acer Keyboard & Optical Mouse. 32
      System Software Microsoft Windows & GNU 01
      Application Software

    Turbo C, Python, Oracle, JDK

    Eclipse, VMware/Hadoop/Amazon EC2/AWS/My SQL

     

    01

     

     C Programming and Data Structures Lab 

    The C Programming and Data Structures Lab introduces students to foundational programming concepts and data structure implementation using the C language. Students gain hands-on experience with arrays, strings, pointers, structures, and functions, along with core data structures like stacks, queues, linked lists, trees, and sorting/searching algorithms. The lab emphasizes writing efficient, modular, and error-free code. Through practical problem-solving exercises, students develop algorithmic thinking and debugging skills. By the end of the course, students will be able to design, implement, and analyze basic data structures and algorithms, laying a solid foundation for advanced programming and computer science subjects.

     

    Java Programming Lab 

    The Java Programming Lab is designed to provide hands-on experience with core concepts of Java programming. This lab equips students with the skills to develop robust, efficient, and portable Java applications. Throughout the course, students engage in practical sessions covering object-oriented programming principles such as classes, objects, inheritance, polymorphism, and encapsulation. Additionally, the lab explores exception handling, file I/O, collections, multi-threading, and graphical user interface (GUI) development using AWT and Swing.

    Students will implement real-world applications to strengthen their problem-solving abilities and coding practices. The lab also introduces Java APIs and development tools like IDEs (e.g., Eclipse or IntelliJ IDEA) to enhance coding efficiency and project management. Emphasis is placed on writing clean, modular, and well-documented code. By the end of the lab, students will be capable of designing, implementing, and debugging Java programs independent.

     

     Machine Learning Lab

    The Machine Learning Lab provides students with practical exposure to fundamental and advanced machine learning techniques. It is designed to complement theoretical learning through hands-on experiments and projects using real-world datasets. Students implement algorithms such as linear regression, logistic regression, decision trees, support vector machines, k-means clustering, and principal component analysis using programming tools like Python and libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib.

    The lab encourages a deep understanding of concepts like model training, testing, validation, overfitting, underfitting, performance metrics, and hyperparameter tuning. Students will work on classification, regression, and clustering problems, gaining insights into selecting appropriate models for different data types and domains. The lab also emphasizes data preprocessing techniques including data cleaning, normalization, and feature engineering.

    Projects and mini-tasks are designed to simulate real-world scenarios, promoting critical thinking and problem-solving skills. The lab fosters collaboration, reproducibility, and best practices in machine learning workflows. By the end of the course, students will be equipped to build, evaluate, and deploy machine learning models effectively.

    This lab lays a strong foundation for advanced AI and data science courses, preparing students for careers in data analytics, AI development, and research roles in academia or industry.

     

    Computer Networks Lab

    The Computer Networks Lab provides students with practical experience in understanding and implementing key networking concepts. It complements theoretical learning by offering hands-on sessions that focus on network protocols, architecture, and communication models. Students explore the functioning of the OSI and TCP/IP models, IP addressing, subnetting, routing algorithms, and data transmission techniques.

    Using tools like Wireshark, Cisco Packet Tracer, and network simulators such as NS2/NS3, students analyze packet flows, configure network devices, and simulate various network scenarios. They gain experience in setting up LANs, configuring routers and switches, and implementing protocols like HTTP, FTP, TCP, UDP, and ICMP. The lab also introduces socket programming using languages such as Python or C to help students understand client-server architecture and develop basic network applications.

    The lab encourages logical thinking and troubleshooting skills as students monitor and debug network issues. It also emphasizes network security basics and efficient data communication techniques.

     

     

     

     

     

     

     

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    C Programming & Datastructures Lab

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    Python Programming Lab

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    Full Stack Development Lab

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    Enterprise Cloud Concepts Lab

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    Java Programming Lab

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    Computer Networks Lab

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    Machine Learning Lab

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    Operatings Systems Lab

    Syllabus

     

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    Faculty Achievements

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    Student Achievements

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    Faculty Profile

    S.No Name of the Faculty Qualification Designation Photo
    DR. VENKATESHWARLU PURUMULA MCA, Ph.D ASSOCIATE PROFESSOR DR. VENKATESHWARLU PURUMULA
    MR. P.SADASHIVA REDDY MCA ASSISTANT PROFESSOR MR. P.SADASHIVA REDDY
    MRS.BANDARI.SWARNALATHA MCA ASSISTANT PROFESSOR MRS.BANDARI.SWARNALATHA
    MRS.GANTYALA ARUNA MCA ASSISTANT PROFESSOR MRS.GANTYALA ARUNA
    MRS.THALLAPALLI MOUNIKA MCA ASSISTANT PROFESSOR MRS.THALLAPALLI MOUNIKA
    MRS. SARITHA PALLE MCA ASSISTANT PROFESSOR MRS. SARITHA PALLE
    MR.K. NAGENDRA PRASAD MCA ASSISTANT PROFESSOR MR.K. NAGENDRA PRASAD
    MISS.SOLLETI TEJASHWINI MCA ASSISTANT PROFESSOR MISS.SOLLETI TEJASHWINI
    MRS. HARITHA VEMULAVADA MCA ASSISTANT PROFESSOR MRS. HARITHA VEMULAVADA
    MRS. ANUGU PAVANI MCA ASSISTANT PROFESSOR MRS. ANUGU PAVANI
    MRS. NOMULA POOJA MCA ASSISTANT PROFESSOR MRS. NOMULA POOJA
    MR. THANNIRU RAMAKRISHNA MCA ASSISTANT PROFESSOR MR. THANNIRU RAMAKRISHNA

    Events

    • Regular participation in International Conferences, Webinars, Seminars, ATAL FDPs, Workshops, organized by reputed Universities and Institutions, etc.
    • Publication of research papers in Scopus, UGC listed Journals
    • Publication of papers in Conference proceeding of reputed Universities and Institutions, etc.
    • Completed multiple number of courses (MOOCs), NPTEL, ICT Academy IIT Kanpur, Swayam, edx, Coursera, IBM Academy, Google, TCSION Digital Learning Hub, Great learning, and many more.
    • Reviewer of Journals Scopus/UGC Care list and other International/National journals
    • Association with Institution’s innovation council, Government of India to establish an ‘Innovation cell’ with a purpose of systematically fostering the culture of Innovation in all Higher Education Institutions (HEIs) across the country.
    • Enrolled in Pedagogy for Online and Blended Teaching-Learning Process
    • Successfully completed an AICTE approved Faculty Development Programme (FDP) by faculty member on Foundation Program in ICT for Education by various Indian Institute of Technological institutions.
    • Delivered expert talks in various Colleges.
    • Developed Case Studies and teaching notes published by Case Center and other reputed publishers
    • Filed Patents to Government of India.
    • Submitted Ph.D’s to the Universities for the award of Degree.
    • Faculties Qualified NET/SET Entrance Examinations.

    Publications

    1. Dr. V.Bapuji.V.Harshith,Ch.Siri and Neeraj B. “Artificial Intelligence Paradigms In Cybersecurity”, Journal of Systems Engineering and Electronics (ISSN NO: 1671-1793) Vol.34 Issue. 5, Pp.508-513. https://jseepublisher.com/wp-content/uploads/49-JSEE2274.pdf   

     

    1. V. Bapuji, G. Suhasini and R. Siddanth, “Deep Learning techniques to Identify Mosquito Disease Spreading”, VDI-Z Integriete Produktion, Vol. 10, No. 9,Pages: 64-70, ISSN: 0042-1766,https://vzipjournal.com/volume-10-issue-9-2023/ , 2023.

     

    1. Dr. V.Bapuji and Sathish Polu. “Analysis of DDOS Attack Detection In Cloud Computing Using Machine Learning Algorithm”, Tuijin Jishu/Journal of Propulsion Technology, Vol. 44, No.5, Pages: 2410-2418, ISSN: 1001-4055, https://www.propulsiontechjournal.com/index.php/journal/article/view/2978/2042, December 2023.

     

    1. Dr. V.Bapuji and Boddupalli Anvesh Kumar. “Secure And Lightweight Authentication Protocols for Devices in Internet of Things”, Tuijin Jishu/Journal of Propulsion Technology, Vol. 44, No.5, Pages: 2419-2427, ISSN: 1001-4055, https://www.propulsiontechjournal.com/index.php/journal/article/view/2979/2043 , December 2023.

     

    1. V.Bapuji, R. Naveen Kumar, A. Govardhan, SSVN. Sarma, “An Improvement to Trust Based Cross-Layer Security Protocol Against Sybil Attacks (DAS) ”, Journal of Computer Engineering and Intelligent Systems (CEIS), ISSN: 2222 – 1719 (Print), ISSN: 2222–2863 (Online), Volume 3, No. 6, pp. 62-70, 2012,https://iiste.org/Journals/index.php/CEIS/article/view/2166/2178. (SCI-E& Scopus Index)

     

    1. V.Bapuji,D.Srinivas Reddy,A.Govardhan and SSVN. Sarma, "Sybil Attack Detection Technique Using Session Key Certificate in Vehicular Ad Hoc Networks”, International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies, ICAMMAET 2017-January, Page: 1–5.

    https://ieeexplore.ieee.org/document/8186733 

     

    1. Dr. V.Bapuji, D.Srinivas Reddy, Prof. A. Govardhan, “k – Means Clustering Algorithms for Vehicular Ad Hoc Networks using Certificate Revocation List Validation Scheme”, Aryabhatta Journal of Mathematics and Informatics, Impact Factor- 5.856 , ISSN: 2394-9309 (E) / 0975-7139 (P), Vol.09 Issue- 01, January - June, 2017, pp. 876-886.(Scopus ID: AJMI C73 6081431192E4BF)

    https://www.ijmr.net.in/current/2017/Jan-June,-2017/w7ogBanfZUVERTA.pdf

    Newsletter

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    Faculty Innovations

    • Regular participation in International Conferences, Webinars, Seminars, ATAL FDPs, Workshops, organized by reputed Universities and Institutions, etc.
    • Publication of research papers in Scopus, UGC listed Journals
    • Publication of papers in Conference proceeding of reputed Universities and Institutions, etc.
    • Completed multiple number of courses (MOOCs), NPTEL, ICT Academy IIT Kanpur, Swayam, edx, Coursera, IBM Academy, Google, TCSION Digital Learning Hub, Great learning, and many more.
    • Reviewer of Journals Scopus/UGC Care list and other International/National journals
    • Association with Institution’s innovation council, Government of India to establish an ‘Innovation cell’ with a purpose of systematically fostering the culture of Innovation in all Higher Education Institutions (HEIs) across the country.
    • Enrolled in Pedagogy for Online and Blended Teaching-Learning Process
    • Successfully completed an AICTE approved Faculty Development Programme (FDP) by faculty member on Foundation Program in ICT for Education by various Indian Institute of Technological institutions.
    • Delivered expert talks in various Colleges.
    • Developed Case Studies and teaching notes published by Case Center and other reputed publishers
    • Filed Patents to Government of India.
    • Submitted Ph.D’s to the Universities for the award of Degree.
    • Faculties Qualified NET/SET Entrance Examinations.