This course equips working professionals from any field — business, finance, law, pharmacy, healthcare, and beyond — with the practical fluency to understand, evaluate, and deploy modern artificial intelligence. Moving beyond classical machine learning, the course centers on the generative AI revolution: large language models, advanced prompt engineering, AI ethics and global regulation, foundational machine learning and deep learning, AI-assisted software development (“vibe coding”), autonomous AI agents and workflow automation, and the integration, API use, and deployment of real AI solutions. The emphasis throughout is on hands-on, low-code and no-code application to each student’s own professional domain, culminating in a deployed capstone AI solution and business case.
- Teacher: Rodolfo Capdevilla
This course delves into fundamental algorithmic and statistical concepts in machine learning, which are essential for understanding and applying machine learning techniques effectively. Machine learning tools have become pervasive across various scientific disciplines, including engineering, computer vision, and biology. This class introduces key mathematical models, algorithms, and statistical tools necessary for performing fundamental tasks in machine learning. Programming examples on diverse datasets are used to illustrate the practical applications of these concepts.