
This course will be exclusively quantitative and an application to business/management-related problems. It is connected with problem sets and real life cases to know the relevance of a particular problem and the decision-making thereof.

Explore random variables, probability distributions, and stochastic processes through intuitive explanations and practical applications in parameter estimation and noisy measurements.

Explore stochastic processes, Markov chains, risk modeling, and survival analysis in actuarial science. Learn key concepts and tackle past exam questions using R for practical applications.

Learn to leverage Python for hydrological and hydrogeological data analysis, including time series analysis, data visualization, and spatial data handling. Gain practical skills for automating tasks and creating impactful visualizations.

Explore the evolution of classical music narratives across five centuries, analyzing structural complexity, temporal directionality, and the concept of irreversibility in musical compositions.

Explore chaos detection in time series using persistent homology and process monitoring techniques, with applications in complex systems analysis and data-driven decision making.

Análisis de cambios en la autorregulación del clima terrestre mediante herramientas de sistemas complejos, comparando datos de temperatura global con el modelo Daisyworld.

Explore financial modeling with Federico Bandi, covering spectral factor models, consumption components, and predictability in stocks and bonds, with insights on aggregation and pricing.

Introduction to social sequence analysis: history, research applications, data sources, capabilities, limitations, and software options for analyzing event and state sequences.

This course will be exclusively quantitative and an application to business/management-related problems. It is connected with problem sets and real-life cases to know the relevance of a particular problem and the decision-making thereof.

Gain practical skills in statistical analysis and econometric modeling, enhancing your ability to interpret data and make informed economic decisions.

Explore advanced data mining techniques using Weka, covering time series forecasting, incremental learning, integration with R and Python, and distributed processing for big data analysis.

Embark on a comprehensive exploration of graph-based techniques for spatiotemporal analysis in this illuminating webinar from the IEEE Signal Processing Society's DEGAS series. Delve into the fascinating world of graph theory and its applications in anal…

Build a real-time anomaly detection system using streaming data engineering techniques. Learn end-to-end implementation for monitoring and identifying unusual patterns in data streams.

Explore Temporal Graph Networks for dynamic graph analysis, unlocking insights in evolving systems like social networks and financial transactions.

Explore new Dynatrace Dashboard App features through a live demo, including advanced threshold visualization, sparkline for timeseries, and enhanced unit formatting.

Explore deep end-to-end causal inference and discover its applications in data-driven decision-making across various domains. Learn about causal discovery, inference, and the Microsoft causal AI suite.

Explore time series machine learning applications in healthcare, focusing on ICU data analysis, explainability tools, and real-time evaluation for improved patient outcomes.

Explore Dynatrace's latest dashboarding innovations, compare classic and new Dashboard App, and learn migration strategies. Gain insights on choosing the right tool for your observability data visualization needs.

Explore ParadeDB's integration of search and analytics capabilities into PostgreSQL, enhancing database functionality for modern applications.

Explore temporal network embedding techniques using classical multidimensional scaling for advanced data analysis and visualization.