This tutorial teaches the principles of various data mining approaches and explains application examples to illustrate how these approaches can be applied in solving design and test problems in practice. We will cover machine learning topics such classification, regression, novelty detection and rule learning, and explain their working principles. We will present examples of applying specific learning technique in design and test contexts. Experience of developing a practical data mining flow will be presented. Promises of applying data mining in practice will be demonstrated through positive experimental results based on industrial settings. The tutorial is intended for engineers, researchers, and managers who are interested in understanding data mining and machine learning and how they can be applied in design and test in practice. Tutorial will teach the knowledge for someone interested in pursuing a learning approach in their respective application context and/or interested in assessing the potential of data mining that can be brought to their research and development effort.