Code: Student Mental Analysis[EDA + ML]
How do factors, such as CGPA , Course, Year of Study and Age together with other academic factors influence mental health outcomes of collage students?
Description: The transition from high school to university is a critical period in a student's life, often accompanied by significant emotional and mental challenges. This project aims to address the importance of mental health in college students by employing data analysis techniques, specifically focusing on EDA andd the implementation of a Random Forest model.
Objective: Develop and implement a ML Clasifier model to understand the corelation factors associated with mental health challenges among college students, achieving a minimum accuracy of 85% through comprehensive data analysis, with the goal of providing targeted support and actionable recommendations. Generate a classification report to assess the model's performance and create a visual representation of the confusion matrix.
Skills: LogisticRegression, EDA, Model Training, RandomForestClassifier, Aggregate Functions, Pandas Data Manipulation, Matplotlib
Technology: Python Notebook
Code: Udacity A/B Testing Experiment
Can asking students in advance about their time commitment reduce early course cancellations in online education??
Description: In the experiment, Udacity tested a change where if the student clicked "start free trial", they were asked how much time they had available to devote to the course. If the student indicated 5 or more hours per week, they would be taken through the checkout process as usual. If they indicated fewer than 5 hours per week, a message would appear indicating that Udacity courses usually require a greater time commitment for successful completion, and suggesting that the student might like to access the course materials for free. At this point, the student would have the option to continue enrolling in the free trial, or access the course materials for free instead. This screenshot shows what the experiment looks like.
Objective: Ivestigate if seting clearer expectations for students upfront, help in reducing the number of frustrated students who left the free trial because they didn't have enough time—without significantly reducing the number of students to continue past the free trial and eventually complete the course.
Skills: A/B Testing, EDA, scipy, Pandas, Math
Technology: Python Notebook