Chinese traditional culture has rich cultural connotations, which has an important role in promoting the development of modern art and design education. The study examines the application of deep learning technology in art and design education through the analysis of several target design colleges and universities based on the background of deep learning. Then, it starts from the creation of art images based on traditional cultural style migration, constructs a style migration model based on a convolutional neural network, and evaluates the effect of style migration images of traditional cultural elements. Create teaching experiments to investigate the utilization of deep learning technology in art and design education. At present, teachers and students still need to improve their cognition of the use of deep learning technology in art design, and the use of deep learning technology in art design has been popularized to a certain extent, with computer vision technology (90.7%) and natural language understanding technology (71.2%) being the most used. The images generated by the style migration model integrating traditional cultural elements have high PSNR values (12~20) and SSIM values (0.375~0.633), and the performance of the students using the model is 6.98% higher than that of the control students, which reflects the validity and feasibility of the application of the model in the creation of art design. It is necessary to optimize the curriculum system, enrich the teaching mode, cultivate the appreciation ability, carry out practical activities and create a good atmosphere and other dimensions to promote the talent cultivation of traditional culture in art design.