Building Career Skill Platforms

Python
# Core platform structure
class SkillSeekersSystem:
    def __init__(self):
        self.users = {}
        self.skills_database = self.load_skills()
        self.job_matcher = JobMatcher()
        self.portfolio_manager = PortfolioManager()
    
    def register_user(self, user_data):
        profile = {
            'id': generate_id(),
            'skills': [],
            'experience_level': user_data.get('level', 'beginner'),
            'career_goals': user_data.get('goals', []),
            'portfolio': [],
            'certifications': []
        }
        return self.create_learning_path(profile)

Example 1: Skill Assessment Input: User profile (React developer, 2 years experience, wants to become full-stack) Output:

JSON
{
  "current_skills": ["React", "JavaScript", "CSS"],
  "skill_gaps": ["Node.js", "Database Design", "System Architecture"],
  "recommended_path": [
    {"skill": "Node.js", "priority": "high", "estimated_time": "4 weeks"},
    {"skill": "MongoDB", "priority": "medium", "estimated_time": "3 weeks"}
  ]
}

Example 2: Job Matching Input: User skills array + job requirements Output: Match percentage with gap analysis and improvement suggestions