Foundations of Applied Artificial Intelligence

The course will begin with a thorough examination of Artificial Intelligence (AI) evolution - from the Dartmouth Conference through the expert systems era, the subsequent "AI winters," and the recent deep learning renaissance - providing students with essential context for understanding the field's current trajectory. It will then systematically cover machine learning principles and neural network architectures, ensuring students grasp the mathematical and computational foundations underlying modern AI systems. The course will include coverage of large language models (LLMs), examining their transformer architectures, capabilities, limitations, and broader societal implications. Finally, we will explore AI agents and autonomous systems, preparing students to critically evaluate emerging technologies.