Expert system is a computer that emulates the decision-making capacity of human experts. This paper highlights the components, the architecture, the role of knowledge base and pattern of knowledge representation in a typical expert system. MYCIN and its components are also analyzed in this paper. Fuzzy logic is a viable and practical form of machine intelligence that has been especially successful in designing expert systems dealing with imprecise data. Majority of the Unmanned Aerial Vehicles (UAVs) in operation today are dependent on a remote human pilot. Higher degree of autonomy provides savings in cost and operational resources and increases safety. However, the challenges involved in making such unique autonomous system, has reasoning and decision-making capabilities analogous to a human pilot. All this is acquired through the developments in fuzzy logic. Fuzzy logic has also penetrated the process of ensuring safety in exploration of crude oil and gas, in detecting the insulation pattern of electronic equipments, monitoring aircraft engine performance and in many such allied fields. The latest developments in expert systems and fuzzy logic have served in generating a billion-dollar business in Mobile learning world by using algorithms for recognizing patterns of learning speed and time. The system then regulates the Mobile learning content by providing needed information to learners. This in turn helps as a tool by teachers to form data driven decisions in response to student needs.