In this experience report, we describe an Artificial Intelligence (AI) Methods in Data Science (DS) curriculum and professional development (PD) program designed to prepare high school teachers with AI content knowledge and an understanding of the ethical issues posed by bias in AI to support their integration of AI methods into existing STEM classrooms. The curriculum consists of 5-day units on Data Analytics, Decision trees, Machine Learning, Neural Networks, and Transfer learning that follow a scaffolded learning progression consisting of introductions to concepts grounded in everyday experiences, hands-on activities, interactive web-based tools, and inspecting and modifying the code used to build, train and test AI models within Google Colab notebooks. The participants in the PD program were secondary school teachers from the Southwest and North-east regions of the United States who represented a variety of STEM disciplines: Biology, Chemistry, Physics, Engi-neering, and Mathematics. We share findings on teacher outcomes from the implementation of two one-week PD workshops during the summer of 2021 and share suggestions for improvements provided by teachers. We conclude with a discussion of affordances and challenges encountered in preparing teachers to integrate AI education into disciplinary classrooms.