About
MCA graduate with a background in data analytics and software development, combining AI/ML internship experience with strong skills in Python, Java, SQL, and Power BI. Built data-driven dashboards, ML models, and full-stack applications across academic and internship projects.
Experience
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Data & AI/ML Analyst InternBETA TechnologiesJan 2025 – Jun 2025
Education
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MCAPES College of EngineeringMaster of Computer Applications · 2024 – 2026
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BCABGS CollegeBachelor of Computer Applications · 2021 – 2024
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II PUC (Science)JSS Women's CollegeScience · 2021
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X (SSLC)BGS Chunchanakatte2019
Skills
Projects
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Diabetes Risk Prediction Web AppJavaScript, HTML5, CSS3, Python, Flask, Scikit-learn
Full-stack diabetes risk prediction app with frontend form validation and a machine learning backend.
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Location-Based Waste Disposal AnalyticsPython, Django, MySQL, HTML/CSS, JavaScript
Web application for city-level waste disposal tracking across collection zones with routing logic and dashboards.
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Predictive Analytics Dashboard — Hospital OperationsPython, Power BI, PostgreSQL, Django REST API
Full-stack data pipeline and dashboard solution for hospital operations with role-based access and reporting.
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Abnormal Activity Detection in Crowded EnvironmentsPython, OpenCV, Scikit-learn, NumPy
Real-time multi-modal surveillance system detecting crowd fights, fire/smoke incidents, traffic signal violations, and crowd anomalies with optical flow and machine learning.
Courses & certifications
- Placement-Oriented Technical Skill Development Program · DLithe Consultancy Services, PES College of Engineering, Mandya · 2026
- Deep Learning with PyTorch · IBM · 2025
- Generative AI with Large Language Models · DeepLearning.AI & AWS · 2025
- Social Network Analysis · IIT Madras · 2025
- Machine Learning Specialization · Coursera
- Power BI Data Analyst · Microsoft
- Python for Everybody · Coursera
- Full Stack Java Development · Youth Employment Program, Infosys Foundation & Nirmaan.org, Bengaluru
🏆 Achievements & awards
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MCA CGPA 9.0
Maintained 9.0 CGPA in MCA and consistently ranked among top performers in the programme.
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Improved ML model accuracy and data quality
Improved prediction accuracy by 15% and resolved 89% of data-quality issues during internship.
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Real-time abnormal activity detection system
Built a system achieving 91.2% classification accuracy and AUC of 0.954 using optical flow and machine learning.
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Delivered end-to-end applications
Independently delivered four end-to-end data-backed and full-stack applications.