Nowadays machine learning has become a powerful tool for social science studies. Various libraries and APIs make it easy for researchers to create and utilize machine learning models. This course introduces supervised machine learning algorithms and its practice especially for the data type heavily used in social science studies, text and images. As for programming languages, we use R for data wrangling and Python for machine learning. The course starts with a basic introduction of R and Python programming. After the introduction of machine learning algorithms including deep learning, students will learn how to implement the algorithms in Python. Along with modeling machine learning by yourself, how to use various machine learning APIs (e.g., Google’s Machine Learning APIs) will be introduced as well. The course is held in English. It is designed for students at various levels with a general interest in machine learning focusing on social science context. Previous experience in R/Python is not required.