Data Analyst and ML enthusiast with experience in analyzing vendor data, building predictive models, and generating insights. Skilled in Python, SQL, and data visualization. Completed AI and ML internship and Data Analys…
Data Analyst and ML enthusiast with experience in analyzing vendor data, building predictive models, and generating insights. Skilled in Python, SQL, and data visualization. Completed AI and ML internship and Data Analyst course on Cyber Success, gaining experience in EDA and predictive analytics. Seeking Data Analyst or ML Engineer roles to apply analytical and ML skills
Completed full Data Analyst course covering Python, SQL, Data Cleaning, EDA, and Data Visualization.
Gained hands-on experience in analyzing datasets and generating business insights.
Learned and implemented basic Machine Learning algorithms for predictive modeling.
Developed reports and visualizations to support data-driven decision-making.
Collected and cleaned vendor and stock datasets for analysis using Python and SQL.
Conducted exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
Built predictive models using regression and classification techniques to forecast performance metrics.
Generated actionable insights to improve vendor efficiency, optimize purchasing, and support business decisions.
Presented results using visualizations and reports to stakeholders for informed decision-making.
Completed full Data Analyst course covering Python, SQL, Data Cleaning, EDA, and Data Visualization., Gained hands-on experience in analyzing datasets and generating business insights., Learned and implemented basic Machine Learning algorithms for predictive modeling., Developed reports and visualizations to support data-driven decision-making.
Collected and cleaned vendor and stock datasets for analysis using Python and SQL., Conducted exploratory data analysis (EDA) to identify trends, patterns, and anomalies., Built predictive models using regression and classification techniques to forecast performance metrics., Generated actionable insights to improve vendor efficiency, optimize purchasing, and support business decisions., Presented results using visualizations and reports to stakeholders for informed decision-making.
Vendor Performance Data Analysis is a data analytics project where I analyzed vendor-related data to evaluate purchasing, sales, pricing, and profitability. Using Python (Pandas, NumPy) and SQL, I cleaned and processed large datasets to identify key performance indicators (KPIs) such as vendor efficiency, cost trends, and profit margins. I also created interactive dashboards to visualize vendor performance and highlight under-performing vendors. The insights from this project helped support data-driven decision-making for vendor optimization and improved business efficiency.
Stock Price Analysis – Car Quikr is a data analytics and machine learning project focused on analyzing car pricing data from the Quikr platform. The project involved collecting and cleaning used car data and performing exploratory data analysis using Python (Pandas, NumPy) to understand price trends based on factors such as brand, model, year, fuel type, and location. Machine learning techniques were applied to analyze patterns and predict car prices. The project provided valuable insights into market trends and helped in accurate car price estimation using data-driven methods.
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