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Analyzed a Kaggle dataset on used cars to provide useful insights for first-time buyers. The analysis explored how different factors affect car prices, which is a key consideration for buyers in the used car market.

This Project was completed using Jupyter Notebook and leverages Python libraries such as NumPy, Pandas, Matplotlib and, Seaborn to perform exploratory data analysis (EDA) and visualizations.

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Developed a client tracker to help users manage potential client information in a table with CRUD functionality and a dashboard that dynamically reflects the same data. The table structures clients through a lead-to-deal pipeline, allowing users to prioritize based on status.

This project was completed using SQLite to store and manage client information and the Python Flask framework to build an interactive web application.

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Designed a client portal for Roya Designs to streamline client communication and improve operational efficiency. The final report included use case models, BPMN diagrams, and a database schema for the system.

UI prototype screenshots are shown below.

Completed Harvard's Introduction to Computer Science, covering computational thinking, algorithms, data structures, and full-stack fundamentals. Applied programming concepts using C, Python, SQL, and JavaScript.

Applied Python for data wrangling, aggregation, and visualization. Worked with DataFrames to clean and transform data, merge multiple datasets, build pivot tables, and generate visual insights using libraries such as NumPy, Pandas, Matplotlib, and Seaborn.

Applied R for data wrangling, exploratory analysis, and visualization. Performed data transformation, joins, and missing value handling, and developed a linear regression model to analyze structured datasets.

Applied SQL to query and analyze relational databases using SELECT, WHERE, GROUP BY, HAVING, and ORDER BY. Performed data extraction, aggregation, and transformation in a relational database environment using DBeaver.

Applied Power BI to clean, model, and visualize structured datasets through interactive dashboards. Built relational data models and applied DAX measures, calculated columns, and moving average analysis to evaluate financial performance and generate insights.

Applied Tableau to explore, clean, and visualize structured datasets through interactive dashboards. Built KPI dashboards and applied calculated fields, forecasting, parameterized controls, and multi-source data analysis to evaluate business performance and support decision-making.

Developed practical Excel skills in data analysis and visualization through hands-on business challenges. Built PivotTables and interactive dashboards, applied lookup functions, conditional logic, and data modeling techniques, with introductory exposure to Power Query, Power Pivot, and VBA.