Transforming
Complex Data
Into Intelligence.

Data Science Intern

• Processed time series carbon emission and environmental sensor data from oil palm plantations.
• Detected anomalies across more than 3.289.751 rows of environmental sensor data using the Interquartile Range technique.
• Handled outlier values through the winsorizing method and linear interpolation to secure data trends without removing critical observations.
• Identified relationship patterns among sensor variables using Pearson correlation heatmap visualizations.
• Validated final data quality through line graph visualizations comparing raw data with imputed data.

Machine Learning Cohort

Participate in an intensive, self directed program focused on machine learning engineering and the fundamentals of data science. Implement machine learning workflows, including data preprocessing, model training, evaluation, and deployment. Develop projects using Python and modern machine learning tools in a collaborative environment.

Applied Mathematics

Focus on deep learning, large-scale ML systems, and probabilistic modeling.