Carlos Navarrete teaches courses at the intersection of data science, artificial intelligence, and statistical analysis. His teaching philosophy emphasizes practical application and determining how advanced computational tools can solve complex real-world problems.
This course explores the foundations and applications of Generative Models, focusing on their architectural principles, fine-tuning techniques, and practical implementation to solve complex engineering and data challenges.
Focuses on the theory and practice of visual data communication. Students learn to design effective, interactive visualizations to uncover insights from high-dimensional datasets using modern web standards and libraries.
Covers fundamental statistical techniques for analyzing datasets. The course focuses on linear regressions, logistic regressions, and Principal Component Analysis (PCA), applying these methods to real-world industrial engineering scenarios.