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The advancements in Internet of Things applications has seen a tremendous growth with 5G and later technologies. The industry 4.0 revolution of digital automation should not exempt education, especially with the ravaging COVID-19 pandemic. The sudden spread of the virus has necessitated a policy direction in online teaching and learning for most academic institutions. The traditional classroom, which has its positives, is minimal in the educational space since distance has become primary in COVID protocols. To wholly integrate traditional classroom merits in online learning, we propose an intelligent online learning system that discovers hidden learner behaviour, and improves personal learning using supervised, unsupervised, and Reinforcement Learning (RL) algorithms. The designed framework automates the online learning space and aids the instructor with lesson planning, delivery approaches, and learner groupings. The learner also constructs knowledge and discovers learning styles through a RL software agent that continuously interacts with the online system using exploration and exploitation mechanisms.