Career Guidance & Entrepreneurial Development

Dataset Overview:
Total Records: 1000 university students
Purpose: The dataset aims to assist in predictive modeling for career and entrepreneurial guidance, providing insights into how machine learning models can improve career planning and entrepreneurial success among students.
Key Components:
Demographic Information:

Student ID: A unique identifier for each student.
Age: The age of the student.
Gender: The student's gender (Male, Female, Other).
Field of Study: The student's primary academic discipline (Engineering, Business, Arts, etc.).
Year of Study: The student's current year in university (1st, 2nd, etc.).
University Location: The geographical location or region of the university.
Academic Performance:

GPA: The student's cumulative grade point average (GPA).
Relevant Coursework: Indicates whether the student has completed courses relevant to career development or entrepreneurship (Yes/No).
Employment & Entrepreneurial Experience:

Prior Employment: Whether the student has had any prior employment (Yes/No).
Type of Employment: The nature of employment, such as part-time, full-time, or internships.
Entrepreneurial Experience: Whether the student has prior entrepreneurial experience (Yes/No).
Start-up Participation: Whether the student has been involved in any start-up ventures (Yes/No).
Survey and Questionnaire Data:

Career Interests: The student's interest in specific career paths (e.g., Tech, Business, Design, etc.).
Entrepreneurial Aspirations: The student's desire or aspiration to become an entrepreneur (Low, Medium, High).
Career Guidance Satisfaction: A satisfaction rating (1-10 scale) based on the student's experience with career guidance services.
Model Predictions:

Recommended Career Path: Career paths.
Entrepreneurship Suitability Score: A numerical score predicting the student's suitability for entrepreneurship (0-100).
Top Recommended Industries: Suggested industries for career focus (e.g., Tech, Finance, etc.).
Predicted Job Success Probability: A probability score (0-100) predicting the student's likelihood of success in their recommended career.
Outcome Variables:

User Satisfaction: A satisfaction rating (1-10) indicating how well the students feel the recommendations align with their career goals.
Followed Recommendations: Whether the student followed the recommended career/entrepreneurial path (Yes/No).
Employment Status Post-Graduation: The student’s employment status after completing their studies (Employed, Self-employed, Unemployed).