Learning resources
Explore DSLAB’s curated collection of open-access books, CRAN R packages, interactive web apps, and instructional materials designed to empower university students, researchers, and data science professionals.
Open-access books (10)
Peer-reviewed textbooks authored by DSLAB professors for statistical modeling, machine learning, and data analysis.
Modelos Estadísticos para la Predicción
Víctor Aceña & Isaac Martín
Provides a rigorous and practical introduction to statistical modeling techniques, especially regression models, aimed at helping students understand, apply, and critically evaluate predictive methods using real data and the R programming language.
Modelos de Regresión
Víctor Aceña, Carmen Lancho & Isaac Martín
An overview of regression models, including linear, variable selection, regularization, non-linear transformations, feature engineering, and generalized regression techniques, aimed at data science students.
Introducción al software estadístico R
Emilio L. Cano
This book provides practical guidance on using software for statistical data analysis, aimed at helping companies and institutions leverage their data to maintain competitiveness in the digital age.
Inferencia Estadística
Carmen Lancho, Víctor Aceña & Isaac Martín
An exploration of statistical inference, covering key concepts and practical applications essential for data science and engineering students, published open-access in BURJC.
Fundamentos de ciencia de datos con R
With contributions by Emilio L. Cano
This book guides readers through the complexities of data science, from understanding big data and ethical data governance to mastering statistical techniques and using R for practical applications.
Aprendizaje Automático
Carmen Lancho & Isaac Martín
An introduction to the fundamentals of Machine Learning, focusing on equipping students with skills to extract valuable insights from data and make informed decisions.
Estadística Aplicada a las Ciencias y la Ingeniería
Emilio L. Cano
This book covers the typical curriculum of Statistics and Probability courses for Science and Engineering degrees at Spanish universities, providing a comprehensive and accessible resource.
Matemáticas Discreta y Álgebra
With contributions by Marina Cuesta
A foundational synthesis of Discrete Mathematics and Linear Algebra as the bedrock for Computer Science and Cybersecurity, deposited at BURJC.
Ciencia de datos para la ciberseguridad
Alberto Fernández & Isaac Martín
This book presents Data Science as a tool for understanding, preventing, detecting, and addressing cybersecurity threats, aimed at professionals, students, engineers, and mathematicians.
Six Sigma with R
Emilio L. Cano, Javier M. Moguerza & Andrés Redchuk
A comprehensive Springer guide that integrates the Six Sigma methodology with the R programming language to improve processes and solve problems using statistical techniques.
R packages & toolboxes (10)
Open-source libraries and algorithms authored by our team published on CRAN, GitHub, and academic repositories.
Virtual Intelligent Tutor (ViLT)
ViLT is a comprehensive framework that integrates an intelligent chatbot to support virtual tutoring for students across various degree programs at ETSII, URJC. It leverages large language models, LangChain, and RAG techniques to optimize natural language queries.
AdvancedBasketballStats
This R package provides a range of functions and metrics commonly used in basketball analytics to evaluate player performance, team statistics, lineup efficiency, and play-by-play data based on Dean Oliver's concepts.
SixSigma
Functions and utilities to perform Statistical Analyses in the Six Sigma way, including DMAIC phases, process capability, control charts, and measurement system analysis.
CSViz method
Implementation of CSViz: Class Separability Visualization for High-Dimensional Datasets.
CPRViz method
Implementation of CPRViz: Consistent Probability Regions Visualization for model understanding.
KRAKEN-SND
Implementation of KRAKEN-SND: Knowledge Recovering Architecture based on Keywords Extraction from Narratives for Suspicious News Detection.
MOE
Implementation and validation of MOE, Minimally Overfitted Learners: A general framework for ensemble learning.
Hostility measure
Generator Python code for artificial datasets and results of the Hostility measure for multi-level study of data complexity.
Experts perception-based system for misinformation detection
Data and scripts used in the paper 'Experts perception-based system to detect misinformation in health websites'.
Explanation sets
Implementation and evaluation of 'Explanation sets: A general framework for machine learning explainability'.
Interactive dashboards & web apps
Web-based exploratory tools and decision-support apps developed for educational and practical applications.
Cybersecurity Risk Analysis and Simulation
Emilio L. Cano & Javier Sánchez
An evolution of the Open FAIR™ Risk Analysis Tool, redesigned as an interactive Shiny application to simplify and enhance Cyber Risk Simulation for cybersecurity students and professionals.
Data Explorer Assistant
Carmen Lancho & Isaac Martín
Interactive app developed so that readers of the book 'Aprendizaje Automático' can put their knowledge into practice with data enrichment, exploratory data analysis, and predictive model exploration.
Lecture slides & short courses
Slides and teaching repositories accompanying published books and specialized short courses.
Inferencia Estadística
Carmen Lancho, Víctor Aceña & Isaac Martín
Complete lecture slides accompanying the book 'Inferencia Estadística'.
Aprendizaje Automático
Carmen Lancho & Isaac Martín
Complete lecture slides accompanying the book 'Aprendizaje Automático'.
Introduction to Git (Seminar)
With contributions by Elena García-Morato & Felipe Ortega
Materials and practical walk-throughs for the teaching innovation seminar 'Introduction to Git' in the DSLAB-TI series.
Unsupervised Analysis (Short course)
Isaac Martín
Materials and code notebooks for the 'Unsupervised Analysis' short course covering hierarchical and non-hierarchical clustering.
Exploratory Data Analysis (Short course)
Isaac Martín
Materials and code notebooks for the 'Exploratory Data Analysis' short course.
Exercises & laboratories
Practical problem sets, interactive lab notebooks, and datasets.
Inferencia Estadística (Labs)
Carmen Lancho, Víctor Aceña & Isaac Martín
Laboratories for the book 'Inferencia Estadística', including both problem statements and complete solutions in HTML and PDF, accompanied by datasets and R code.
Inferencia Estadística (Exercises)
Carmen Lancho, Víctor Aceña & Isaac Martín
R scripts with exercises for the book 'Inferencia Estadística', including both theoretical/applied problems and their full solutions, archived on BURJC.
Aprendizaje Automático (Exercises)
Carmen Lancho & Isaac Martín
R scripts with machine learning exercises for the book 'Aprendizaje Automático', including problems, training tasks, and solutions.
Professional training courses
Master degrees, executive certifications, and university courses in data science and big data.