Introduction: This workshop will provide a hands-on introduction to Machine & Deep Learning. Format: An introductory lecture on several supervised and unsupervised Machine Learning techniques followed by light introduction to Deep Learning. Both Apache Spark as well as TensorFlow will be introduced with relevant code samples that users can run in the cloud and explore. Objective: To provide a quick and short hands-on introduction to Machine Learning with Spark Machine Learning library (MLlib) and Deep Learning with TensorFlow. In the lab, you will use the following components: Apache Zeppelin and Jupyter notebooks with Apache Spark and TensorFlow processing engines (respectively). You will learn how to analyze and structure data, train Machine Learning models and apply them to answer real-world questions. You will also learn how to select, train, and test Deep Learning models. Prerequisites: Registrants must bring a laptop with a Chrome or Firefox web browser installed (with proxies disabled, i.e. must show venue IP to access cloud resources). These labs will be done in the cloud. At this Crash Course everyone will be assigned a cluster to try several workloads using Apache Spark and TensorFlow in Zeppelin and Jupyter notebooks (respectively) hosted in the cloud.