Through technologies such as ChatGPT, generative AI has become increasingly accessible over the past few years, which has sparked concerns regarding the role that generative AI will inevitably begin to play in education. Many scholars have explored the broad affordances and limitations of ChatGPT in teaching and learning: one of its key strengths is its personal and interactive nature, while one of its most significant shortcomings is its tendency to share inaccurate information. However, little research has been done on ChatGPT’s capabilities within specific fields, such as DH. This project explores the role that ChatGPT can or should play in Digital Humanities education, particularly in helping more traditionally trained humanists understand and utilize computational methods. We break down the curriculum in Carnegie Mellon University’s Computing for Humanists class and identify the key concepts covered, which include topics such as data preparation, feature counting, and the translation of humanistic research questions into computational steps. We then test ChatGPT’s mastery of these concepts by asking it to complete or assist with class assignments in various capacities. We find that ChatGPT excels at simple computational tasks and at suggesting ways in which specific humanistic research questions can be explored computationally. However, when writing more complex functions, ChatGPT often uses out-of-date libraries and struggles to properly connect different parts of the code. Based on these results, we present the baseline level of computational education that we believe digital humanists ought to possess prior to using ChatGPT as a research tool, while also highlighting the ways in which digital humanists can be taught to use ChatGPT to help implement computational methods.