With the rapid advancement of artificial intelligence (AI), digital-intelligent technologies have become increasingly pivotal in landscape architecture education. Traditional pedagogical approaches within the discipline face challenges such as repetitive workflows, insufficient data support, and slow iteration cycles in design conceptualization, environmental analysis, and outcome delivery, which impede the discipline’s capacity to address the complex and swiftly evolving environmental challenges of the modern era. Overcoming these limitations and integrating novel digital-intelligent tools have become critical for establishing an interdisciplinary and multi-scalar innovative teaching paradigm, which has emerged as a key research focus in the discipline. This study, grounded in empirical evidence from Tongji University’s “Digital Landscape and Generative AI Design” course, proposes a novel pedagogical framework that synergizes traditional landscape design wisdom with modern digital technologies. By systematically integrating digital landscape analysis, big data mining, and generative AI techniques, the framework enables bidirectional interaction between theoretical heritage preservation and technological innovation. Empirical studies have demonstrated that experimental groups adopting this teaching model have exhibited significant improvements in key metrics, such as design innovation, technical application capabilities, and problem-solving proficiency, compared to traditional methods. The findings not only provide a replicable roadmap for the digital transformation of landscape architecture education but also cultivate interdisciplinary talents with advanced digital literacy and professional expertise. This research holds substantial reference value for advancing the innovation and development of landscape architecture education systems in China.