The technology company IBM, founded in the early 20th century, cites more than 150 zettabytes of data will require analysis by 2025. With the abundance of data, artificial intelligence (AI) like machine learning (ML) is essential to solving some of the most challenging problems. In this course, students will gain exposure to the core mathematics behind basic ML-powered solutions in data analysis and become empowered in the critical field of AI. The curriculum includes an introduction to Bayesian decision theory, parametric estimation (e.g. maximum likelihood estimation) and dimensionality reduction, coupling theoretical lessons with hands-on exercises to enforce learning. We look forward to meeting you!
