The Petroleum and Mining Engineering Department at Tishk International University successfully conducted a specialized nine-day training program entitled “Turning Data into Knowledge via Empirical Models.” The program took place from January 26 to February 5, 2026, at the TIU main campus and attracted participants from different academic backgrounds.
The department designed this training to strengthen practical data analysis skills. In particular, the program focused on transforming raw data into meaningful knowledge using empirical and regression-based modeling approaches. Moreover, the training addressed the growing need for data-driven decision-making in both academic research and professional practice.
Professor Dr. Tariq H. Karim delivered the training sessions and guided participants throughout the program. He presented theoretical concepts in a clear manner and directly linked them to practical applications, supporting participants with real examples to ensure better understanding and engagement.
Throughout the nine days, participants explored a wide range of topics related to empirical modeling, including linear and nonlinear regression models, curve fitting techniques, and model validation methods. The training also covered issues such as overfitting, underfitting, multicollinearity, and systematic outlier handling, helping participants develop a solid foundation in empirical data modeling.
The program emphasized hands-on practice using widely adopted analytical tools. Participants worked with Excel, SPSS, Minitab, Python, and R to analyze data and evaluate model performance, gaining practical experience applicable across engineering, environmental, medical, and social science fields.
The training welcomed academic staff, administrative staff, undergraduate students, and postgraduate students from various departments at Tishk International University. Participants showed strong interest and active involvement throughout the sessions, contributing significantly to the program’s success.
By the end of the training, participants demonstrated improved ability to analyze data, build empirical models, and interpret results effectively. The program achieved its objectives and reinforced the department’s commitment to capacity building and industry-relevant education.
Keywords: Empirical Modeling, Data Analysis, Regression Models, Tariq Karim, PAME Department, TIU, Excel, SPSS, Minitab, Python, R, Curve Fitting, Model Validation, Overfitting, Multicollinearity, Outlier Handling
