After completing the courses in the [Microsoft Professional Degree Data Science Curriculum](http://aka.ms/lexdsc), it’s time to put all that you have learned into practice. Before entering this competition, you should register for the [Data Science Professional Project](https://www.edx.org/course/data-science-professional-project-microsoft-dat102x) course on edX and review the detailed information there. This competition concerns loan data. When a customer applies for a loan, banks and other credit providers use statistical models to determine whether or not to grant the loan based on the likelihood of the loan being repaid. The factors involved in determining this likelihood are complex, and extensive statistical analysis and modelling are required to predict the outcome for each individual case. You must implement a model that predicts loan repayment or default based on the data provided. The dataset used in this competition consists of synthetic data that was generated specifically for use in this project. The data is designed to exhibit similar characteristics to genuine loan data. Students can't link competition scores to the edX course until the competition closes. At that point, we'll copy across the final score data and notify students telling them will enter their submission ID for their best model to be graded in the edX course. There is no requirement that students use the same user account in edX and the competition - only the submission ID is used to link the two.