Design and Implementation of a Vocational Education Course Recommendation System Based on Deep Learning

The accuracy and personalization of vocational education course recommendation systems are key factors in improving the effectiveness of online vocational education. This paper designs a vocational education course recommendation system based on deep learning, adopting a front-end and back-end separated microservice architecture. A dual-tower deep neural network model is constructed, where user behavior sequence analysis and course feature extraction are used to build user profiles and course feature vectors, enabling intelligent course recommendations. Experimental results show that the system outperforms traditional recommendation methods in terms of recommendation accuracy, user satisfaction, and system response time, significantly improving user learning outcomes and platform activity. This provides a new solution for vocational education course recommendations.