This paper examines the implementation of Python programming in teaching financial analytics to graduate accounting students. The growing influence of Big Data has reshaped accounting practices and created a need for curricula that go beyond traditional Excel-based analysis. Most existing teaching cases focus on data interpretation, overlooking essential stages such as extraction, cleaning, and preparation. To address this gap, we develop and implement a Python-based learning module within a graduate accounting program. The module introduces students (many with little or no coding background) to key data analytics concepts through practical coding exercises. We discuss effective teaching strategies, classroom challenges, and student feedback. Findings suggest that integrating Python into financial analytics education enhances students’ analytical capabilities and provides a more comprehensive understanding of the data analytics process.