FCIS–MSIT and Research, Innovation and Publication Services Conduct 3-Day Machine Learning and Deep Learning Training Workshop

The Faculty of Computing and Information Sciences (FCIS) – Master of Science in Information Technology (MSIT) Program, in partnership with the Office of Research, Innovation and Publication Services of Southern Leyte State University (SLSU) Main Campus, successfully conducts the three-day Machine Learning and Deep Learning Training Workshop on June 8–10, 2026, at Lecture Room ICT 3, FCIS Building.

Carrying the theme “From Data to Insights and Intelligent Decisions,” the workshop aims to equip faculty members, students, researchers, and staff with foundational and practical knowledge in machine learning, deep learning, data analytics, and research development.

Dr. Rhoderick D. Malangsa serves as the resource speaker, guiding participants through lectures, demonstrations, and hands-on activities. During the first day, participants explore the fundamentals of machine learning, data preprocessing, unsupervised learning, clustering techniques, frequent pattern mining, the Apriori algorithm, and Naïve Bayes classification. These sessions provide participants with a solid understanding of how data can be transformed into meaningful insights through machine learning techniques.

The second day focuses on practical applications using the WEKA data mining platform. Participants gain hands-on experience in implementing classification techniques, analyzing datasets, and interpreting machine learning results. The afternoon session further strengthens participants' analytical skills through association rule mining and data-driven research exploration.

On the final day, participants install and configure Python development environments, including Jupyter Notebook and essential machine learning libraries, in preparation for practical coding activities. Participants learn about Python-based data analysis, machine learning model development, and YOLO-based computer vision applications. Some participants successfully train machine learning and object detection models using their own datasets, while others conduct data analysis using Python and WEKA.

Beyond technical training, participants also learn about Information Technology Research Structures and Methods, including the Results-First Scientific Writing Framework (RFSWF), which emphasizes developing research manuscripts by focusing on results and discussion prior to drafting other sections of a paper. This session highlights the integration of machine learning outputs into publishable research studies.

A major outcome of the workshop is the development and presentation of participant-generated research outputs. Through dataset exploration and machine learning applications, participants identify several potential research directions and present studies with strong potential for publication. The workshop generates an estimated 15 prospective research outputs, reflecting the participants' ability to translate data-driven insights into meaningful research initiatives.

The workshop concludes with participant reflections and the sharing of experiences, where attendees express appreciation for the practical, research-oriented, and hands-on approach of the training.

The FCIS–MSIT Program extends its sincere gratitude to the Research, Innovation and Publication Services (RIPE) for its invaluable support and commitment to fostering research, innovation, and lifelong learning within the university community. The success of the workshop demonstrates SLSU's continuing dedication to developing competencies in emerging technologies and advancing data-driven research and innovation.