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Introduction to Image Classification

Discover how to perform image classification using a convolutional neural network (CNN) by building, training and evaluating a model with a real set of images.

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Fundamentals of Classification in Machine Learning

Explore key concepts in classification, including logistic regression, support vector machines (SVM), and neural networks, through hands-on exercises in Python.

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Large Language Models for Research

Use Large Language Models (LLMs) for reproducible workflows in literature review, data preparation, coding, analysis, and research writing.

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Decision Trees and Ensemble Methods in Machine Learning

Learn the theory behind decision trees, including how they split data, handle overfitting, and work with both classification and regression problems.

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Fundamentals of Regression in Machine Learning

Explore regression techniques in supervised machine learning, from simple and multiple linear models to regularisation and Bayesian approaches for predictive analysis.

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Clustering and Unsupervised Methods in Machine Learning

Discover unsupervised machine learning methods, including k-means, hierarchical, and density-based clustering, along with dimensionality reduction techniques.