In the years following COVID-19, technological advances related to education have made significant progress, and many countries have prioritized online education over traditional education, as it allows students to progress at their own pace and with their own methodology. This results in a more dynamic and flexible education. However, it is more difficult to recognize students' specific needs. Therefore, the use of machine learning, artificial intelligence, and semantic ontology is suggested to improve the learning process for the benefit of students. In higher education, semantic ontology plays an important role in knowledge management and representation. It also helps formulate the representation of the learning domain through the comparison of knowledge and relationships between concepts, in order to enhance the learning process. The ontology represents a multidimensional map of learning domains, representing concepts and cognitive needs, which will allow students to delve deeper into the knowledge and additional skills expected, so that they can acquire the corresponding professional competencies that will enable them to solve real and complex problems. In the real world, higher education students face various complex processes and decisions. To address these challenges, they turn to online academic advising systems and tools to overcome factors such as uncertainty, utilizing systems such as fuzzy logic and ontological models, as well as semantic rules that can operate dynamically and fluidly. In conclusion, it is very important that online learning resources be geared toward achieving professional competencies. In health education in particular, there is evidence of the usefulness of Semantic Web platforms in the training of human resources, developing complex reasoning skills in students, enabling them to address real-world and complex problems for the benefit of patients.