Use this module to build the skills for the job task Assemble an Analysis-Ready Table. You'll learn how to apply filtering and subsetting techniques to isolate the records you need in Python, and how to apply merging and joining operations in SQL to combine multiple datasets into a single analysis-ready table. Review the lessons that match the skills you want to strengthen before completing the related graded assessment.

Use this module to build the skills for the job task Engineer Clean Numeric Features. You'll learn how to apply data transformation operations to derive new columns from existing data and how to apply normalization techniques such as min-max scaling and z-score standardization to put numeric features on a comparable scale for machine learning. Review the lessons that match the skills you want to strengthen before completing the related graded assessment.

Use this module to build the skills for the job task Prepare a Modeling-Ready Feature Set. You'll learn how to develop and prepare a complete feature set for predictive modeling, including handling missing data, encoding categorical variables, scaling numeric features, and selecting or reducing features so that the final dataset is ready to train a model. Review the lessons that match the skills you want to strengthen before completing the related graded assessment.

Review the skills you practiced and demonstrated in this course, then prepare to describe them in career-relevant ways. You’ll also explore recommended skill paths that can help you continue building related job-ready skills.