Artificial Intelligence: From Concept to Product

From "Black Box" to "White Box": In standard AI-First courses, AI is perceived as a ready-made assistant or user tool (prompting, connecting APIs). In this course, students go "under the hood" of AI to understand the mathematical mechanisms (probability, gradient descent, vector spaces, distance metrics) upon which these models are built. 

Building and Training Models (Creating vs. Consuming): Instead of merely using AI created by others, students build ML models themselves, work on hyperparameter optimization, model evaluation metrics (Precision, Recall, F1-Score), and RAG (Retrieval-Augmented Generation) architecture. 

Mathematical and Technological Synergy: The course acts as a bridge between high school mathematics and modern Deep Learning / LLM technologies, endowing students with foundational engineering mindset.