Abstract: To foster the development of exceptional engineering and innovative talents, cater to the innovative practical training requirements across arts, sciences, engineering, and medicine, and address issues like monotonous learning approaches, repetitive project content, and fragmented experimental projects in current engineering training courses, we aim to establish a visual knowledge graph for engineering training and AI courses. By integrating industrial scenarios and tailoring practical projects to various majors, we will create a blended teaching model that combines AI-powered personalized learning with project-based practices. Additionally, we will implement a progressive training approach that encompasses AI-enhanced knowledge learning, comprehensive skill development, and innovative project practices, thereby facilitating personalized learning, engineering mindset, and differentiated innovation and practical skills for students. We will employ a comprehensive and diversified evaluation system throughout the entire process, documenting assessment scores, and leveraging AI big data and deep learning techniques to create visual profiles of our student users.