Machine Learning Engineering with SAS

Organizations rely on data to predict trends and automate decisions, making machine learning a vital skill for modern analysts. This course guides you through the process of building robust machine learning pipelines using SAS, moving from fundamental statistics to advanced predictive modeling. You will gain the skills to move from raw data to production-ready models. Through reading and written exercises, you will learn to: - Understand core machine learning concepts and statistical foundations within the SAS environment - Prepare and clean complex datasets to ensure model accuracy and reliability - Apply supervised and unsupervised learning techniques to solve business problems - Evaluate model performance using industry-standard metrics and validation strategies - Implement model governance and basic MLOps workflows for sustainable deployment - Optimize predictive models through feature engineering and hyperparameter tuning The curriculum begins with essential terminology and foundational definitions before moving into practical implementation and model management. This course is designed specifically for beginners looking to enter the field of data science and requires no prior machine learning experience. Start your journey into machine learning engineering with SAS today.