Career Guidance & Entrepreneurial Development
Predictive Career Guidance and Entrepreneurial Development Using AI and ML
@kaggle.ziya07_career_guidance_and_entrepreneurial_development
Career Guidance Dataset
@kaggle.ziya07_career_guidance_and_entrepreneurial_development.career_guidance_dataset
- 31.82 KB
- 1000 rows
- 22 columns
student_idStudent ID | ageAge | genderGender | field_of_studyField Of Study | year_of_studyYear Of Study | university_locationUniversity Location | gpaGPA | relevant_courseworkRelevant Coursework | prior_employmentPrior Employment | employment_typeEmployment Type | entrepreneurial_experienceEntrepreneurial Experience | startup_participationStartup Participation | career_interestsCareer Interests | entrepreneurial_aspirationsEntrepreneurial Aspirations | career_guidance_satisfactionCareer Guidance Satisfaction | recommended_career_pathRecommended Career Path | entrepreneurship_suitability_scoreEntrepreneurship Suitability Score | top_recommended_industriesTop Recommended Industries | predicted_job_success_probabilityPredicted Job Success Probability | user_satisfactionUser Satisfaction | followed_recommendationsFollowed Recommendations | employment_status_post_graduationEmployment Status Post Graduation |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| S0001 | 24 | Female | Science | 4 | Region A | 3.64 | 1 | Full-time | 1 | 1 | Design | High | 7 | Healthcare | 11 | Tech | 13 | 4 | 1 | Unemployed | |
| S0002 | 21 | Female | Engineering | 5 | Region C | 2.88 | 1 | Internship | 1 | Tech | Low | 1 | Design | 34 | Healthcare | 20 | 6 | 1 | Self-employed | ||
| S0003 | 28 | Male | Business | 3 | Region A | 2.26 | 1 | 1 | Full-time | 1 | Design | High | 6 | Tech | 69 | Tech | 42 | 10 | Employed | ||
| S0004 | 25 | Female | Business | 5 | Region B | 2.76 | 1 | Internship | 1 | 1 | Finance | Low | 6 | Finance | 71 | Finance | 27 | 9 | Unemployed | ||
| S0005 | 22 | Male | Law | 2 | Region A | 3.24 | 1 | 1 | Part-time | 1 | 1 | Finance | Low | 5 | Business | 20 | Education | 20 | 5 | 1 | Self-employed |
| S0006 | 24 | Female | Arts | 3 | Region C | 2.91 | 1 | Internship | 1 | 1 | Business | Medium | 2 | Healthcare | 60 | Finance | 35 | 7 | 1 | Employed | |
| S0007 | 27 | Male | Business | 4 | Region C | 3.56 | 1 | Part-time | 1 | 1 | Business | Low | 2 | Tech | 34 | Design | 23 | 1 | 1 | Self-employed | |
| S0008 | 20 | Male | Arts | 3 | Region B | 4 | 1 | 1 | Part-time | 1 | 1 | Healthcare | Medium | 9 | Healthcare | 47 | Finance | 53 | 9 | 1 | Self-employed |
| S0009 | 24 | Female | Science | 5 | Region C | 2.38 | 1 | Part-time | 1 | Design | Medium | 5 | Design | 14 | Healthcare | 37 | 6 | Self-employed | |||
| S0010 | 28 | Other | Engineering | 1 | Region B | 2.92 | 1 | Part-time | 1 | Healthcare | High | 5 | Tech | 70 | Healthcare | 16 | 4 | Employed |
CREATE TABLE career_guidance_dataset (
"student_id" VARCHAR,
"age" BIGINT,
"gender" VARCHAR,
"field_of_study" VARCHAR,
"year_of_study" BIGINT,
"university_location" VARCHAR,
"gpa" DOUBLE,
"relevant_coursework" BIGINT,
"prior_employment" BIGINT,
"employment_type" VARCHAR,
"entrepreneurial_experience" BIGINT,
"startup_participation" BIGINT,
"career_interests" VARCHAR,
"entrepreneurial_aspirations" VARCHAR,
"career_guidance_satisfaction" BIGINT,
"recommended_career_path" VARCHAR,
"entrepreneurship_suitability_score" BIGINT,
"top_recommended_industries" VARCHAR,
"predicted_job_success_probability" BIGINT,
"user_satisfaction" BIGINT,
"followed_recommendations" BIGINT,
"employment_status_post_graduation" VARCHAR
);