Introductory session on applying AI (ML life cycle) for cyber security use cases. It's very typical during Threat hunting to determine whether activities are suspicious, and recommend its suspicious level. In this session, audiences will learn how to use Watson Studio to train a ML model which does suspicious process classification. Using the data set provided, participants will learn how to run an Auto-AI pipeline selecting features that are important for the model. Participants will use Watson Studio to save and serve the ML model. Pre-requirement: Understanding of STIX, Python Environment: WatsonStudio, Jupyter Notebooks.