Now, more than ever, there is a need for computer scientists and data scientists to be socially responsible about the algorithms they design and the products they build. We all have to conscientiously analyze the impact of our work, particularly on historically marginalized communities. As we look towards creating a more just future, this means we also need to provide our students appropriate training, so that we can all address existing social inequities and prevent further social inequities from creeping into our work. Data science provides an ideal opportunity to train students to identify existing bias and explore ways to address it. This special session equips educators with tools to bring about this training. The presenters will share their experiences in incorporating data science for social justice in their courses, introducing CS through a social justice lens, and interrogating the collection and use of data. Through moderated group discussions, this special session will collate ideas and strategies from the participants of their respective experiences. The presenters will create and share a repository of the collated ideas to enable a broad swath of educators to incorporate data science for social justice in their respective courses to train the future generation.