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skills-gap-analysis

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edwardnhw / Data-Driven-Data-Science-Curriculum-Design

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A data-driven approach to designing an optimal Data Science curriculum. This project extracts skills from job postings, applies NLP and clustering techniques (K-Means, Hierarchical, DBSCAN), and maps industry demands to educational recommendations. Uses Python, Scikit-learn, OpenAI embeddings, and Seaborn for visualization.

python nlp machine-learning scikit-learn data-visualization seaborn edtech dbscan hierarchical-clustering k-means-clustering data-science-education clustering-algorithms openai-embeddings data-driven-decision-making skills-gap-analysis
  • Updated Mar 5, 2025
  • Python

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