J. Linear and Logistic Regression

The Linear and Logistic Regression course aims to enhance understanding and skills in data analysis and predictive modeling using Linear and Logistic Regression methods. Students will learn the fundamental principles of Linear Regression, how to build and fine-tune models, analyze linear equations, and utilize models for predictions while evaluating their effectiveness.

Additionally, the course covers the application of Logistic Regression for analyzing data with classification characteristics. Learners will study how to construct Logistic Regression models, interpret the results, and apply these concepts in real-world scenarios, such as handling imbalanced datasets and selecting suitable features for model use.

By the end of the course, participants will gain deep insights and practical skills that they can apply in data analysis and the development of predictive models in real-world environments.