This chapter examines how the integration of computer science (CS) can support science teaching and learning, emphasizing its transformative role in enhancing scientific inquiry, data analysis, and developing digital skills among both learners and educators. As scientific research increasingly depends on advanced computational tools, it has become essential to incorporate CS into science education. The chapter explains how computational thinking—which includes pattern recognition, abstraction, decomposition, and algorithmic problem-solving—aligns with scientific inquiry methods, thereby promoting structured and analytical thinking in students. Key topics covered include the use of low-cost microcontrollers or simulations to facilitate authentic, inquiry-based learning, making advanced scientific investigations more accessible. The chapter also discusses the potential of Artificial Intelligence (AI), and big data analysis in enhancing scientific literacy. Furthermore, the importance of CS in fostering data literacy through self-written algorithms for data cleaning and visualization is highlighted. Finally, the chapter underscores the significance of teacher training in digital competencies, utilizing appropriate frameworks like DiKoLAN and DiKoLAN AI to prepare educators for the effective integration of CS tools. This integration is presented not only as a means to enhance science learning but also as a necessity for equipping students for the demands of modern scientific research and technological advancements.