The first objective of the project was to determine the knowledge gap of current or recent graduates of the fields that are not traditionally connected to the data science and artificial intelligence - such as medicine, economics or engineering, in regards to that area. Then, the second objective was to create a set of classes, to be integrated into a short-cycle course that will serve to directly address the determined knowledge gaps. The course was designed as a short-cycle course split into mandatory and elective parts. Allowing the participants to cover what were determined as basic, fundamental knowledge points, in the field of data science and artificial intelligence and then select additional courses to address their specific upskilling needs - whether it is additional knowledge in fundamental structures of data science and artificial intelligence (such as mathematics, big data), or domain specific knowledge that may be helpful for them personally.
The primary objective of this project was to effectively respond to the continuously increasing demand for additional data science and artificial intelligence (AI) competencies in professional fields that have not been traditionally or directly associated with these disciplines. In today's rapidly evolving technological landscape, data science and AI are being increasingly integrated into a wide range of industries, including but not limited to medicine, healthcare, traditional engineering, and economics. As a result, there exists a growing knowledge gap among both recent graduates and current professionals in these and other domains, where foundational and applied knowledge in data science and AI is becoming an essential asset rather than an optional skill. With this in mind, the project aimed to bridge this knowledge gap by providing opportunities for individuals working in these fields to acquire a fundamental understanding of key concepts, methodologies, and applications of data science and artificial intelligence. The intention was not only to help professionals and graduates develop a clearer comprehension of the digital and data-driven environment in which they operate but also to facilitate their professional growth.