The goal of this project was to analyze students’ learning habits and map them to their performance in an introductory computer science course. As far as we know, there is no concrete data or analysis for students at Penn in introductory computer science courses that predicts how a student is going to perform based on their current behavior, or provides suggestions, based on a student’s current habits, for improvement. Using the unique opportunity of an online semester with data that normally is not available in an in-person classroom, we collected students’ learning data and analyzed it to determine optimal learning trajectories that correspond to success in the course. After conducting our analysis, we developed an interactive website that takes in a student's self-inputted data and outputs personalized insights for the student regarding more effective study habits. Our website also has information presented in the format of frequently asked questions, with detailed answers backed by our analysis. This project addresses the need for a comprehensive toolkit regarding computer science education that provides necessary resources to students in an understandable and constructive way.