Welcome

This course on Advanced Machine Learning in Python for Applications in Oceanography and Climate offers practical, applied training in modern machine learning techniques, tailored to real-world problems in scientific contexts. Students will work with supervised and unsupervised Machine Learning models using scikit-learn, including SVMs, linear models, and ensemble methods such as bagging and boosting. Neural networks will be developed using PyTorch and scikit-learn, ranging from Multi-Layer Perceptrons to convolutional networks for image analysis, and the handling of time series data specific to the ocean and climate will also be addressed. In addition, the course covers techniques for processing scientific text, from classification to content generation using embeddings and RAG architectures, enabling students to integrate heterogeneous data into advanced research projects and practical applications.

Teaching Team

• Aina Tur

• Isaac Lera

• Miquel Mirò

• Gabriel Moyà

Schedule

Module	Teacher	Class Time
1. Machine Learning	Aina Maria Tur Serrano	5
2. Multi Layer Perceptron (MLP)	Aina Maria Tur Serrano & Gabriel Moyà Alcover	5
3. Temporal Series	Gabriel Moyà Alcover	5
4. Image Analysis	Miquel Miró Nicolau	6
5. Text	Isaac Lera Castro	6