A mini project for tracking student certification progress, extracting skills, and recommending suitable career opportunities.
Many students complete online certification courses but struggle to:
- Track their acquired skills
- Align skills with career opportunities
- Identify skill gaps for desired jobs
This system solves these problems by:
- Tracking student progress in certification courses
- Extracting and categorizing learned skills
- Matching students with suitable jobs/internships
- Identifying skill gaps and recommending learning paths
- β Student data collection and storage
- β Job posting database with required skills
- β Comprehensive skill dictionary (80+ skills)
- β Skill extraction from course names
- β Proficiency calculation (weighted by completion %, grade, time spent)
- β Student skill profile builder
- β Job matching algorithm using cosine similarity
- β Skill gap analysis
- β Data visualizations and reports
- 30 students with 80+ course enrollments
- 20 job postings from various companies
- 80+ technical skills tracked across 8 categories
- Average match accuracy: ~65%
- Student Skill Profile - Bar chart showing proficiency in each skill
- Job Recommendations - Top 5 matching jobs with match percentages
- Skill Gap Analysis - Skills needed vs skills possessed
- Overall Statistics - System-wide analytics
- Language: Python
- Libraries:
- Pandas, NumPy (data handling)
- Scikit-learn (TF-IDF, cosine similarity)
- Matplotlib, Seaborn (visualizations)
- Storage: CSV files
- Development: Jupyter Notebook
skill-career-recommendation-system/
βββ data/
β βββ student_data.csv
β βββ jobs_data.csv
β βββ student_data_with_skills.csv
βββ notebooks/
β βββ 01_data_creation.ipynb
βββ outputs/
β βββ student_profiles.csv
β βββ recommendations.csv
β βββ demo_summary.txt
β βββ *.png (visualizations)
βββ README.md
- Advanced NLP for better skill extraction
- Resume parsing capability
- Skill verification quiz system
- Interactive dashboard (Streamlit/Flask)
- Integration with learning platforms
- Real-time job scraping
- Machine learning-based recommendations
Team of 4 students - 5th Semester Mini Project
Academic project for educational purposes