Edge AI, also known as AI at the edge, refers to the implementation of artificial intelligence in an edge computing environment. It combines Edge Computing and AI to run ML tasks directly at the edge without relying on centralized cloud servers. Edge AI is used in various domains: healthcare (wearable devices), manufacturing (predictive maintenance), smart cities (traffic management), and more. This paper proposes an Edge AI course to prepare students for careers in the coming market. The proposed course takes Top-Down and Bottom-Up approaches concurrently. The lecture component uses the Top-Down approach. It starts from the market end and walks learners through career opportunities, required skill sets, and Deep Learning knowledge (YOLOv8, LLaMA-2). The activity component uses the Bottom-Up approach and starts from an inexpensive AI inference board (RK3588-based) that executes YOLOv8 and small LLM (lama 7.4 B) pre-trained modes to implement real-world applications.