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This study aimed to understand the relationship between course activities and learning progress among students enrolled in the MicroMasters certificate program offered in an affordable MOOC-based learning platform. To capture the relationship, the differences between the engagement patterns of learners in the MicroMasters program compared to a non-degree MOOC were examined by utilizing machine-learning (ML) techniques in the clickstream database. The ML analyses revealed discrepancies in activity patterns and student progress rates in MicroMaster and MOOC courses. The findings can further support optimizing the program’s design to enhance learners’ engagement and overall completion rates.