PRANEET PRAVIN

PRANEET PRAVIN

B.Tech Computer Science and Information Technology Student

Ghāziābād, IndiaSoftware and data technology
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About

B.Tech Computer Science and Information Technology student building full-stack applications, data analytics dashboards, and machine learning systems using Python and related technologies.

Education

Ajay Kumar Garg Engineering College

B.Tech, Computer Science and Information Technology

2023 – Present

Affiliated to Dr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow

Mayo International School, New Delhi

CBSE Class XII

2022

82.8%

Indirapuram Public School, Ghaziabad

CBSE Class X

2020

91%

Mayo International School - India

Higher Secondary School

2020 - 2022

Indirapuram Public School - Indirapuram

Secondary School

2008 - 2020

Skills

PythonC++CJavaScriptHTML5CSS3React.jsFlaskMySQLMongoDBSQLitePandasNumPyMatplotlibPlotlyTableauPower BIJupyter NotebookScikit-LearnSciPyGitGitHubGitHub ActionsDockerStreamlitVS CodeExcelFPDF2yfinanceBcryptREST APIsMachine LearningData AnalysisData ScienceObject-oriented LanguagesData AnalyticsPrompt EngineeringGitHub CopilotObject-Oriented Programming (OOP)Microsoft Visual Studio CodeC (Programming Language)Microsoft ExcelMicrosoft Power BIPandas (Software)Python (Programming Language)HTML

Projects

OptimaWealth – Personal Wealth & Portfolio Intelligence Dashboard

Built a full-stack personal finance analytics dashboard with transaction CRUD, CSV/PDF bank-statement import, budget monitoring, profile backup and restore, Dockerized deployment, and GitHub Actions CI. Implemented TF-IDF and Logistic Regression transaction auto-categorization with SQLite feedback retraining; SciPy portfolio optimization; live pricing with an offline synthetic fallback; risk analytics; net-worth forecasting; and a pytest suite.

Student Information Management System (SIMS)

Designed and developed a full-stack academic management portal with role-based access for administrators, faculty, and students. Implemented Flask REST APIs, student records and academic workflows, machine-learning student risk prediction with a rule-based fallback, Plotly analytics dashboards, automated PDF generation, Bcrypt hashing, rate limiting, and database migrations.