Main Courses
- Information Theory (UPC: Bachelor’s degree in Data Science and Engineering, 2nd Year, Autumn Semester): This course has two main objectives: (1) to give the students a rigorous introduction to the main notions of Information Theory, including proofs of the fundamental theorems of source coding, noisy-channel coding and information secrecy; (2) to present several applications, including data compression, error correction codes and information measures estimators.
- Machine Learning (UPC: Master’s degree in Advanced Mathematics and Mathematical Engineering, Spring Semester): This is a basic course on machine learning topics covering unsupervised methods such as clustering and dimensionality reduction and supervised methods such as Bayesian regression , kernel methods, support vector machines and feedforward and recurrent neural networks.
- Biophysics I (UPC: Bachelor’s degree in Physics Engineering, 1st Year, Spring Semester): The goal of this course is to give the student a comprehension of the core physics concepts governing biological systems mainly based on the areas of biomechanics, applied fluid mechanics and thermodynamics.
- Physical Geodesy (UPC: Bachelor’s degree in Geoinformation and Geomatics Engineering, 2nd Year, Spring Semester): This course reviews the gravitational potential and introduces the concepts of geoid, reference ellipsoid, normal field, disturbing potential, gravity anomaly, as well as the decomposition of the Laplace equation into spherical harmonics. The course also presents gravimetry reductions including the concept of isostasy.