Machine Learning (ML) is the convergence of different disciplines in science and technology. While it is conceived, ML is part of computer science however, in its essence, it borrows or utilizes methods from other classic disciplines and mature computing theories and technologies, such as statistics, computational algorithms, optimization, and data mining. In this paper, we explore how these disciplines and technologies work hand in hand to prepare a passionate researcher gains a comprehensive perspective for being an ML expert. We have proposed a roadmap to show how different disciplines and technologies contribute to the ML foundation and we discuss each part of the roadmap separately. Moreover, to apply the proposed roadmap in practical terms, we also present how to use the proposed roadmap in the context of IoT and Fog Computing. The main contribution of this paper is to provide a guideline by developing a roadmap for foundational requirements of being a Machine Learning subject matter expert for the researchers or industry experts.