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Year after year, computing systems continue to grow in complexity at an exponential rate. While this can have far-ranging positive impacts on society, it has become extremely difficult to ensure the security of these systems in the field. Hardware security - in conjunction with more traditional cybersecurity topics like software and network security - is critical for designing secure systems. Moving forward, hardware security education must ensure the next generation of engineers have the knowledge and tools to address this growing challenge. A good foundation in hardware security draws on concepts from several different fields, including fundamental hardware design principles, signal processing and statistics, and even machine learning for modeling complex physical processes. It can be difficult to convey the material in a manageable way, even to advanced undergraduate students. In this paper, we describe how we have leveraged Python, and its rich ecosystem of open-source libraries, and scaffolding with Jupyter notebooks, to bridge the gap between theory and implementation of hardware security topics, helping students learn through experience.