Math, Data & Computing has been essential for evaluating, validating and guiding my design and research activities during my education. In B1, Data Analytics (2IAB1) gave me a foundation in statistical thinking, Python and visualisation. I was already familiar with coding from high school, and Creative Programming (DBB100) strengthened this in a creative context. I am comfortable with properly annotated and structured code (Figures 4 and 5), and value open-source approaches because they align with accessible knowledge. I can code and document my work, but still want to contribute more public work related to social initiatives in the future. In Design <> Research (DDB100), I worked with design probe kits (Gaver et al., 1999), thematic analysis and design research methods. This made me understand that data is not neutral, especially in social projects. What we collect, how we collect it, interpret it and visualise it are all connected to values and power. Digital Craftsmanship (Figure 2) shifted this further: weather data became a creative tool for designing a bag that felt like “Safety” and “Protection.” During my FBP, I also explored semantic differentials (Figure 3) as a data analysis and visualisation method not previously introduced in curricular Data Analytics courses. I expect my future projects to involve social contexts, user/community insights, a combination of quantitative and qualitative data, and the need to communicate evidence clearly, so the knowledge and skills I gained in data collection, analysis, synthesis and visualization during my education are very valuable to me.