Data scientists and machine learning engineers must demonstrate proficiency in leveraging SAS Viya 3.5 to construct advanced analytical pipelines incorporating natural language processing and computer vision. Candidates implement text analytics using SAS Visual Text Analytics to execute document parsing, sentiment analysis, and topic modeling within the CAS environment. The curriculum mandates architectural competency in deep learning, specifically employing convolutional neural networks and recurrent neural networks for image classification and feature extraction. Practitioners utilize Python and SAS programming interfaces to automate model deployment and hyperparameter tuning while validating model performance metrics across distributed computing infrastructures to ensure scalable, production-ready artificial intelligence solutions.