Nowadays, there is a need more than ever for personalized machine learning models that can learn efficiently from big data and handle challenges of emerging technologies as in smart healthcare and medicine. By personalized we mean the models that are expected to work well for each and every person, and not only the average population - as traditionally approached in machine learning. The Personalized Machine Learning course is designed to equip students with the tools and knowledge necessary for personalized human data analysis, with the focus on health and well-being. This course will provide students with an overview of the cutting-edge machine learning approaches (including Active Learning and Domain Adaptation techniques, with the focus on Deep Neural Networks and Gaussian Processes as modeling tools) that they can later use to build their own creative personalized applications. With the guidance of the instructors, you will learn how to use and manipulate these machine learning models to take the full benefits of the personalized learning in your projects. Each student (or a group) will be provided with a number of datasets, access to machine learning tools, and is expected to actively participate in group discussions in the class - leading to the identification and solving of the key challenges in personalized machine learning. Students are also expected to identify/design/implement their own project (with a guidance of the instructors), where they will get in-depth understanding of the personalized machine learning algorithms. Note that the class is originally intended for the Media Lab students, however, other interested students are also welcome!