Student Intern
Highlights
Explored methods and algorithms to develop a model to detect objects and activities.
Built a heart disease prediction model - applied logistic regression and performed data cleaning on healthcare datasets, identifying key medical risk factors.
Contributor
Highlights
Conducted multilingual research to identify translation imbalances across Wikipedia pages.
Collaborated with a global team, conducted user research, and proposed actionable solutions to improve content parity.
National Service Scheme(NSS)
Highlights
Led 3 surveys and spread awareness of education and health in slum areas.
Udacity
Selected among 1,000 scholars for AWS training, mastering machine learning via Udacity.
WECode
Earned the prestigious WE Amplify scholarship to attend Harvard's WECode, engaging with 1500+ peers and industry leaders.
Attended the world's largest women's tech conference, networking with experts and exploring emerging tech opportunities.
C, C++, Python, SQL, HTML, CSS, JS.
MS Excel(Pivot table, formulas, dashboarding), MS Word, Google-Sheets, PowerPoint, Power BI (basic).
Data Cleaning, Exploratory Data Analysis(EDA), Dashboarding, Visualization, Reporting.
Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn (for analytics, Machine learning).
Leadership, Collaboration, Communication, Attention to detail, Problem solving.
Data Structures and Algorithms, OOP, Database Management System, SDLC, Operating Systems.
Member: Attended events, navigated available opportunities, networked with peers and mentors
Summary
Analysed the relationship between CO emissions and global temperature anomalies using 5+ statistical techniques, including correlation analysis and regression modelling, leveraging Python, SciPy, Statsmodels, and Scikit-learn.
Summary
Analysed 10,000+ pizza sales records using SQL and Excel to identify revenue trends, peak sales hours, and customer preferences.
Summary
Developed a web-based AI tool using the Hugging Face API, capable of generating 1000+ high-quality images from text prompts.
Summary
Conducted data preprocessing, cleaning, and clustering on customer data using K-Means to extract actionable marketing insights.