Corona Virus Analysis: Analyzed COVID-19 data using SQL to derive insights into the pandemic's impact.NREGA Data Analysis: Investigated the implementation and outcomes of the NREGA program, focusing on employment generation and budget utilization. Conducted detailed analysis and visualization of NREGA dataset, identifying patterns and informing policy decisions.A project demonstrating inner SQL join techniques, showcasing proficiency in database management and querying.

During my Unified Mentor Data Analyst Internship, I completed two key projects:Developed a Power BI Dashboard for Heart Disease Prediction Analysis, focusing on metrics like average age and cholesterol levels to aid healthcare decisions.Analyzed revenue and cancellations for Atliq Hospitality, identifying trends and providing strategic recommendations for revenue stability and booking management.These projects enhanced my skills in data analysis, visualization, and strategic decision-making, preparing me for roles in data analytics and healthcare analytics.

PwC Switzerland Power BI Job Simulation on Forage - May 2024Completed a job simulation where I strengthened my PowerBI skills to better understand clients and their data visualisation needs.Demonstrated expertise in data visualization through the creation of Power BI dashboards that effectively conveyed KPIs, showcasing the ability to respond to client requests with well-designed solutions.Strong communication skills reflected in the concise and informative email communication with engagement partners, delivering valuable insights and actionable suggestions based on data analysis.Leveraged analytical problem-solving skills to examine HR data, particularly focusing on gender-related KPIs, and identified root causes for gender balance issues at the executive management level, highlighting a commitment to data-driven decision-making.

During my one-month Data Science Internship at CodersCave, I gained hands-on experience by working on several key projects. I developed a House Price Prediction model involving data cleaning, feature engineering, outlier removal, model building and Additionally, I conducted an in-depth analysis of IMDb movie data using a Kaggle dataset, writing and uploading the code to GitHub. I also worked on projects like Speech Emotion Recognition and Diabetes Prediction, enhancing my skills in machine learning, data analysis, and end-to-end project development.

During my five-month virtual internship, I engaged in diverse projects and hands-on tasks that honed my expertise in data analysis, machine learning, and signal processing. Key activities included:Developing and Evaluating Machine Learning Models: Applied supervised and unsupervised learning techniques using MATLAB, enhancing my proficiency in feature engineering, classification, and clustering.Implementing Deep Learning Techniques: Trained and evaluated neural networks, including CNNs and RNNs, for various applications such as image processing and natural language processing.Signal Processing Applications: Designed and analyzed digital filters, conducted time and frequency domain analysis, and developed algorithms for noise and echo cancellation.Image Processing Projects: Conducted image enhancement, restoration, and feature extraction tasks using MATLAB, improving the quality and interpretability of digital images.MATLAB Programming and Data Visualization: Utilized MATLAB for complex mathematical computations, created dynamic visualizations, and automated data analysis processes, contributing to efficient data-driven decision-making.This internship provided a comprehensive foundation in advanced data analysis, machine learning, and MATLAB programming, preparing me for challenging roles in these domains.