Notes

Fundamental concepts and algorithms in reinforcement learning, focusing on sequential decision-making and control.

Advanced treatment of core topics in computational linguistics, including morphology, syntax, and semantics.

Probability distributions, estimation, hypothesis testing, confidence intervals, and likelihood-based methods.

Psychological and linguistic approaches to language comprehension, production, and acquisition.

Directed research and advanced instruction in Basque linguistics, grammar, and cultural context.

Corpus-based methods for linguistic analysis, including frequency, dispersion, and distributional approaches.

Computational approaches to natural language processing, including parsing, semantics, and language models.

Supervised and unsupervised learning, neural networks, and practical machine learning techniques.

Generative modeling techniques including VAEs, GANs, and diffusion-based models.

Introduction to the Basque language, with focus on grammar, vocabulary, and linguistic structure.