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
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Google Cloud Data Analytics Virtual InternshipAICTEApr 2026 – Jun 2026
Completed an 8-week Data Analytics Virtual Internship under AICTE EduSkills, gaining practical exposure to industry-oriented data analytics concepts.
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Data Science Master Virtual InternshipAltairJul 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.
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AI Azure Virtual InternshipMicrosoft, AICTE & Edunet FoundationJun 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.
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AWS AI-ML Virtual InternshipEduskillsApr 2025 – Jun 2025
Learned machine learning concepts, cloud-based AI services, and practical implementation of AI/ML solutions using AWS technologies.
Education
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2027
B.TechComputer science and engineering -Data science · Aug 2023 – May 2027
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High School
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High SchoolNarayana Kennedy Campus
Skills
Tools / apps / platforms
Projects
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Feelings Behind WordsNLP, 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.
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AI Malware Classification System using CNN and StreamlitPython, 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.
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AI-Based Civic Complaint Management SystemPython, 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.