The rapid advancement of technology has created a demand for tools that enable individuals without a computer science background to develop applications. This research focuses on leveraging no-code and low-code platforms, integrated with Google’s machine learning technologies, to empower non-computer science students to create functional and innovative applications. The goal is to democratize app development by providing accessible tools that allow students from various disciplines to harness the power of machine learning without extensive programming knowledge. No-code and low-code platforms offer intuitive development environments where users can design and deploy applications using drag-and-drop interfaces, pre-built components, and minimal coding. By incorporating Google’s machine learning capabilities, such as natural language processing, image recognition, and predictive analytics, these platforms enable students to create intelligent applications that solve real-world problems. This integration enhances learning experiences, fosters creativity, and broadens skill sets. The study examines the potential of these platforms in educational settings, exploring their ability to facilitate technically sophisticated yet easy-to-create applications. It also investigates the challenges and opportunities of teaching non-computer science students to use these tools, including the need for tailored instructional materials and support systems. Through case studies and user testing, the research evaluates the impact of no-code and low-code app development on student engagement, creativity, and integration of machine learning into diverse academic projects. By contributing to accessible technology education, this paper highlights how these platforms, combined with Google’s machine learning, can foster a new generation of developers from non-traditional backgrounds.