A framework for predicting course time duration using mapreduce and K-means

With the upcoming of new innovations, new developed patterns are brought into the educational framework which brings about enormous information which is unordered, and it is likewise, a test for understudies to allude to those scholastic courses which are useful in their modern preparation and expands their vocation possibilities. Another test will help to change over the unregulated information into organized and significant data there is a requirement for Data Mining Techniques. The appropriate file system is utilized to hold a large amount of information and allows to reduce the over storage of unregulated data. Information extricated utilizing MapReduce is useful in decision making for understudies for deciding courses picked to undergo modern preparation. In this paper, with the help of MapReduce and K-means algorithms we sort the data into their respective time durations from which the users can choose their courses based on the required time duration in which they are willing to complete the courses. Here, utilizing Distributed File System (DFS), errands run over MapReduce, and the result is obtained after aggregation. Our implementation allows users to choose their subject of interest with the best possible time duration they require to complete the course.