Project 2 - Gender Bias in Science and Technical field

Great experience creating the dasboard to Analyse the Gender Bias in Science and Technical field. 

The project involves:

Data Collection: Gathering information from academic studies, industry reports, and surveys to assess the representation of women in STEM fields.

Data Analysis: Using statistical methods, visualization tools, and machine learning models to uncover trends, identify biases, and pinpoint systemic barriers contributing to gender disparities.

Insights & Strategy Development: Identifying key factors such as unconscious bias, stereotypes, and institutional challenges that limit opportunities for women. Proposing data-backed strategies to promote diversity, mentorship, and policy changes for gender equity.

By applying data analytics to social issues, I aim to contribute to evidence-based decision-making that drives inclusivity in STEM fields. This project reflects my commitment to harnessing data for impactful change and my broader interest in exploring the intersection of data science, social research, and business intelligence.