The development of digital intelligence technology is a powerful driving force for breaking down professional barriers and cross-fertilization among multiple disciplines. This paper takes the talent cultivation of art and design majors as the research objective, and explores the optimization and improvement of students’ learning methods as well as instructional design respectively. In the recommendation of learning resources, a feature matrix of art education information technology assessment resources is established to realize the cluster analysis of assessment art resource themes. And the four common problems of learners in personalized e-learning are constructed as multi-objective optimization problems to build a personalized e-learning resource recommendation problem model. Combined with the multi-objective particle swarm optimization algorithm (NEMOPSO), the recommendation model of art and design professional learning resources is constructed. With the assistance of the proposed recommendation model and the professional course design method, the performance of students in the experimental group reaches 4.00 and above in 10 creative force indicators, which verifies the high feasibility and reliability of the designed talent cultivation program.
