What Should Data Science Education Do With Large Language Models?

The rapid advances of large language models (LLMs), such as ChatGPT, are revolutionizing data science and statistics. These state-of-the-art tools can streamline complex processes such as data cleaning, model building, interpretation, and report writing. As a result, it reshapes the role of data scientists. We argue that LLMs are transforming the responsibilities of data scientists, shifting their focus from hands-on coding, data-wrangling and conducting standard analyses to assessing and managing analyses performed by these automated AIs. This evolution of roles is reminiscent of the transition from a software engineer to a product manager, where strategic planning, coordinating resources, and overseeing the overall product life cycle supersede the task of writing code. We illustrate this transition with concrete data science case studies using LLMs in this paper. These developments necessitate a meaningful evolution in data science education. Pedagogy must now place greater emphasis on cultivating diverse skillsets among students, such as LLM-informed creativity, critical thinking, AI-guided programming, and interdisciplinary knowledge. LLMs can also play a significant role in the classroom as interactive teaching and learning tools, contributing to personalized education and enriched learning experiences. This paper discusses the opportunities, resources and open challenges for each of these directions. As with any transformative technology, integrating LLMs into education calls for careful consideration; we also discuss the limitations and failure cases of LLM. While LLMs can perform repetitive tasks efficiently, it’s crucial to remember that its role is to supplement human intelligence and creativity, not to replace it. Therefore, the new era of data science education should balance the benefits of LLMs while fostering complementary human expertise and innovations. As the rise of LLMs transforms data science and its education, this paper sheds light on the emerging trends, potential opportunities, and challenges accompanying this paradigm shift, hoping to spark further discourse and investigation into this exciting new territory