Building a Career Recommendation System to Bridge the Skills Gap

Background

The rapid growth of technology in fields such as artificial intelligence and the Internet of Things has shifted the skills landscape. Future professions demand a mix of technical expertise and soft skills not always taught in traditional education systems. In Lagos State, many students struggle to identify the right career paths and acquire relevant skills, leading to rising unemployability among graduates due to poor career decisions and a lack of market-ready competencies.

Objective

• Develop a machine learning-based career recommendation system using publicly available datasets.
• Analyze the distribution of student populations in Lagos State to identify educational trends.
• Provide actionable recommendations for students to enhance their preparation for tertiary education and professional careers.

Approach

The team followed a structured approach to address the problem:

1. Research and Data Collection: Publicly available datasets were sourced to understand trends in education and career outcomes.
2. Exploratory Data Analysis (EDA): EDA techniques were used to uncover insights into students’ educational backgrounds and skill gaps.
3. Preprocessing and Model Development: Data preprocessing and augmentation techniques were applied to prepare the dataset. Machine learning algorithms were developed and trained to recommend suitable career paths.
4. App Development: A user-friendly application was built to make career suggestions accessible to students and educators.

Results and Impact

 The project successfully developed a career recommendation system capable of identifying gaps in students’ preparedness for tertiary education and professional careers. Key outcomes include:

• A detailed analysis of Lagos State’s student population distribution.
• Career recommendations tailored to individual skill sets and market demands.
• Insights for policymakers and educators to design better programs for skill development.

This system helps students make informed career decisions, reducing the mismatch between education and employment needs and addressing the issue of unemployable graduates in Lagos State.

Future Implications

This project sets the foundation for future initiatives in career guidance and education policy. The findings can influence:

• Development of targeted training programs to address identified skill gaps.
• Adoption of AI-driven career counseling tools in educational institutions.
• Expansion of the system to other regions facing similar challenges.

By refining the model and incorporating more diverse datasets, the career recommendation system could become a pivotal tool in shaping the workforce of tomorrow.