Recently, an innovative initiative at Umeå University in Sweden has attracted widespread attention in the field of machine learning (ML) education. The university has successfully paved a new path to the world of ML for non-technical students by introducing a no-code AI platform. This initiative not only breaks through traditional technical barriers but also sets a new benchmark for interdisciplinary education. According to reports, this project was implemented in the master's level Business Artificial Intelligence course at Umeå University, aiming to explore the effectiveness and challenges of using a no-code AI platform to teach ML to non-technical students. Through a series of case-based teaching methods and the utilization of the Peltarion no-code AI platform, students are able to create and deploy ML models without the need to deeply understand complex algorithms. "The emergence of the no-code AI platform has completely changed the face of ML education," said the project leader. "It not only simplifies the operational process of ML but also greatly reduces the technical barriers, allowing students from different disciplines to easily get started and experience the charm of ML." Research results show that the usability and affordability of the no-code AI platform are significant advantages. Students are able to collect data and train models smoothly without technical obstacles, thus gaining a deeper understanding of the role of ML in practical applications. In addition, by participating in group projects, students learn how to apply ML technology to solve real-world problems, further enhancing their practical skills and teamwork spirit. It is worth noting that although the no-code AI platform provides many conveniences for non-technical students, the research also points out the challenges it faces. How to ensure that students have a profound understanding of the underlying ML concepts while simplifying operations has become an urgent problem to be solved. To address this, the project team emphasizes the importance of problem-centered teaching methods and encourages students to explore the mysteries of ML through practice. "We believe that the no-code AI platform will become an important trend in future ML education," said the project leader. "It not only promotes the development of interdisciplinary education but also provides more students with opportunities to access and master ML technology. We look forward to seeing more universities and educational institutions join this trend and jointly promote the popularization and progress of ML education." With the widespread application of no-code AI platforms in ML education, more and more students will have the opportunity to overcome technical barriers and enter a new era of ML. This innovative initiative not only injects new vitality into the field of education but also provides strong support for cultivating talents with cross-disciplinary thinking and innovation capabilities.