Explores the impact of skipping activities on student success and the use of transition matrices and learning analytics cubes to predict student states.
Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.
Explores the history, principles, and critiques of evolutionary psychology, emphasizing the adaptive function of characteristics and the evolutionary approach to understanding human behavior.
