Applying Machine Learning to Analyze the Effectiveness of Corporate Training Programs

The article examines the application of machine learning methods for evaluating the effectiveness of training programs in the corporate sector, driven by the fact that in a rapidly changing market, organizations face the need for objective assessments of their educational processes, requiring appropriate approaches.The purpose of the article is to review existing machine learning models that can identify relationships between employee training and performance metrics.To achieve this objective, the author analyzed classification methods, regression models, and neural networks to process data on training outcomes, employee performance, and engagement levels.The methodological foundation includes a comparative review of publicly available publications and practical examples from certain companies, which provide a comprehensive exploration of the topic.The findings presented in the article will be useful for training specialists, HR managers, and leaders interested in optimizing their training programs.The conclusions confirm the necessity of applying machine learning for evaluating and subsequently improving educational processes within organizations.