May 25–29, 2026 | CST Laboratory, GSU Mosqueda Campus
The Data Science Mastery Path Training organized by the DICT–Guimaras Provincial Office was successfully conducted on May 25–29, 2026 at the CST Laboratory, GSU Mosqueda Campus. Organized by the DICT Guimaras in collaboration with the College of Science and Technology, the five-day intensive program gathered representatives from various Municipal LGUs, DepEd Guimaras, selected CST students, and GSU personnel.
Serving as the Resource Speaker, Prof. Adrian J. Forca, CST Dean, the training aimed to provide participants with foundational knowledge in data science and Python programming, promote the use of Python libraries for data-driven decision-making, bridge gaps in understanding machine learning concepts, and empower participants with practical skills applicable to real-world scenarios.
The sessions began with an introduction to data science and Python basics, including the installation and use of NumPy for data manipulation. On the second day, participants explored Pandas and the data science life cycle, learning techniques in data wrangling and visualization. The third day advanced into exploratory data analysis and machine learning, covering statistical exploration, preprocessing, regression, clustering, and model evaluation. The final two days were dedicated to capstone projects, where participants applied their learning to sector-specific challenges.
Capstone presentations showcased diverse applications of data science: DepEd Guimaras focused on predictive analysis of student academic performance and placement outcomes; LGU Nueva Valencia analyzed pension distribution gaps among senior citizens; LGU San Lorenzo worked on crop yield analysis; GSU students developed a fuel price prediction model with a five-year forecast; and LGU Buenavista examined brand loyalty through machine learning.
This training not only strengthened technical capacity but also fostered collaboration among government units, educators, and students. By equipping participants with essential data science and machine learning skills, the program contributes to evidence-based governance, educational innovation, and research advancement in Guimaras.
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