Master of Data Science Unhas Holds Machine Learning Bootcamp for Data-Driven Governance
Makassar, May 18, 2026
The Master of Data Science Program, Department of Statistics, Faculty of Mathematics and Natural Sciences, Hasanuddin University organizes the Machine Learning Bootcamp for Data-Driven Governance. This activity is held on May 18-23, 2026 at the Ballroom of the Department of Statistics, FMIPA Unhas.
This bootcamp is organized as an effort to strengthen the competencies of Master of Data Science students in understanding and applying machine learning to support data-driven decision making. This activity includes strengthening basic machine learning concepts, data science workflow, regression, classification, clustering algorithms, explainable AI, as well as practical use of Python and the Scikit-learn library.
In addition, participants also receive materials related to using R for machine learning, data exploration, data visualization, statistical modeling, random forest, support vector machine, predictive modeling, clustering, and time series. These materials are designed so that participants not only understand the concepts but also are able to apply them through practical sessions and assignments.
In the following sessions, the activity continues with strengthening research and publication skills, including coaching clinics for scientific publications, responsible AI, research ethics, plagiarism, systematic literature reviews, and reference management using Zotero or Mendeley. Participants also receive briefings on capstone design, policy brief writing, identifying agency problems, drafting proposals, research clinics, and final presentations.
Through this activity, the Master of Data Science Program of the Department of Statistics, FMIPA Unhas hopes that students will be able to develop analytical, computational, and research skills relevant to the needs of data-based governance. This bootcamp is also a strategic step in strengthening the graduate profile to be adaptive, skilled, and ready to contribute to the use of data for more effective decision-making.
