🚀 Project Update: DataQuest — Phase 1 Complete Over the past few weeks, I've been working on DataQuest, a project focused on using data and machine learning to better understand educational inequality and student performance. Today, I'm happy to share that I've completed the first stage of the project: research and problem definition. So far, I've: - Reviewed literature on educational inequality, learning analytics, and student performance prediction. - Explored public educational datasets and identified potential data sources. - Refined the research question to focus on predicting students at risk of academic underperformance using educational and socioeconomic indicators. - Started documenting the project's methodology and future development roadmap. This is just the beginning. The next phase will focus on collecting and preparing data before moving on to building and evaluating machine learning models. I'm excited to see how this project develops and to continue learning about AI, data science, and their potential to create meaningful social impact. Documentation and technical progress from Phase 1 will be shared soon. On to Phase 2: data collection and preprocessing. #MachineLearning #AI #DataScience #EdTech #Research #StudentResearch #Python #LearningInPublic