This course focuses on reviewing concepts of data science, where participants will learn the stages of a data science project. Topics include using automated tools to prepare data for analysis, build models, evaluate models, and deploy models. To learn about these data science concepts and topics, participants will use IBM SPSS Modeler as a tool. 1: Introduction to data science and IBM SPSS Modeler Explain the stages in a data-science project, using the CRISP-DM methodology Create IBM SPSS Modeler streams Build and apply a machine learning model 2: Setting measurement levels Explain the concept of "field measurement level" Explain the consequences of incorrect measurement levels Modify a field's measurement level 3: Exploring the data Audit the data Check for invalid values Take action for invalid values Impute missing values Replace outliers and extremes<