Timetable preparation is a tedious and challenging task in the educational area. In this work, hence proposed to exhibit a hybrid web-based automated timetable generation system based on genetic algorithms (GA), performed with Python and Streamlit. Also, the construction of schedules for educational institutions is a complex task involving constraints of teachers, rooms, subjects, and non-conflicts such as duplication or overlapping of assignments. Conventional methods of scheduling oftentimes do not meet such a requirement, especially when there is a variety in constraints or when the constraints vary with time. In this case, the GA is employed on account of its versatility in searching the solution space while enforcing multiple constraints so as to quickly crawl to satisfactory solutions. The genetic algorithm model starts with generating an initial population of timetables that includes among 3other assignments of teachers, subjects, and it sets the number of hours to be assigned per day and sections. Crossover, mutation, and selection of timetables are the three operator functions that the algorithm uses to increase the chances of getting timetables that minimize the number of conflicts, such as assigning more than one teacher to a single time slot.