SV

Sahithya Samunnatha Vullanki

Data Science undergraduate · Python and Machine Learning enthusiast

Guntur, Andhra Pradesh, India

@sahithya_samunnatha_vullanki

0 followers

🎓 B.Tech in Computer Science and Engineering (Data Science) at R.V.R & J.C. College of Engineering · Graduating 2027

About

Data Science undergraduate with a strong foundation in Python, SQL, and machine learning. Has built web and AI/ML projects and is eager to grow in software development and data-driven roles.

Experience

  • Google Cloud Data Analytics Virtual Internship
    AICTE
    Apr 2026 – Jun 2026

    Completed an 8-week Data Analytics Virtual Internship under AICTE EduSkills, gaining practical exposure to industry-oriented data analytics concepts.

  • Data Science Master Virtual Internship
    Altair
    Jul 2025 – Sep 2025

    Worked on data analysis, machine learning, and model implementation using real-world datasets. Applied data preprocessing and problem-solving techniques in practical scenarios.

  • AI Azure Virtual Internship
    Microsoft, AICTE & Edunet Foundation
    Jun 2025 – Jul 2025

    Completed a 4-week virtual internship focused on Artificial Intelligence and Microsoft Azure cloud technologies. Gained practical exposure to AI concepts, Azure services, and cloud-based AI solution development.

  • AWS AI-ML Virtual Internship
    Eduskills
    Apr 2025 – Jun 2025

    Learned machine learning concepts, cloud-based AI services, and practical implementation of AI/ML solutions using AWS technologies.

Education

Skills

6 to 12 months 6 to 12 months Most of a year behind them.

Tools / apps / platforms

3 to 6 months 3 to 6 months A few months of practice with it.
Google Cloud Platform Amazon Web Services AWS
<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
Git GitHub SQLite VS Code Microsoft Azure Jupyter Notebook Microsoft Power BI

Projects

  • Feelings Behind Words
    NLP, Python, Scikit-learn, Streamlit

    NLP-based sentiment analysis system to classify text into positive, negative, and neutral sentiments using machine learning techniques. Built an interactive Streamlit application for real-time sentiment prediction and visualization.

  • AI Malware Classification System using CNN and Streamlit
    Python, TensorFlow/Keras, Streamlit

    AI-based malware classification system using CNN and the Malimg dataset to classify malware families from image-based inputs. Built a Streamlit interface for malware prediction and visualization; achieved approximately 96% model accuracy.

  • AI-Based Civic Complaint Management System
    Python, Flask, SQLite, HTML, CSS, JavaScript

    Web-based complaint management system with complaint submission, status tracking, department assignment, filtering, and priority prediction. Includes an admin dashboard for monitoring complaints.

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