Increasing empirical evidence suggests that credit units are an insufficient proxy for student workload in higher education. Course load analytics (CLA) could support course selection and academic advising by offering a more accurate prediction of course load based on data from a learning management system and historical enrollments. We describe the development of a CLA platform for academic advising. The CLA platform surpasses time-bound credit hour metrics by predicting cognitive demand and psychological stress associated with courses while identifying workload spikes throughout the semester on a weekly basis. We describe how the platform enables students and advisors to plan semesters using a course catalog tool, allowing them to explore alternative semester workload scenarios. We contribute generalizable knowledge and procedures for instrumenting similar platforms that support students in managing and preparing for their academic course workload. We also contribute open-source code for researchers and practitioners to adopt and deploy our CLA platform.