Exploratory analysis of HC Corpora dataset for JHU Data Science Capstone

This project deals with a storm dataset from the U.S. National Oceanic and Atmospheric Administration (NOAA). It makes use of the disaster type, the population health impact, and economic damage impact variables from the dataset. We address two questions: 1. Across the United States, which types of events (as indicated in the EVTYPE variable) are most harmful with respect to population health? 2. Across the United States, which types of events have the greatest economic consequences? For population health, tornadoes have the highest amount of damage. For economic impact, floods have the highest amount of damage.

Simulación probabilística basada en una distribución normal N(9, 0.5) para proyectar el flujo de entrada a planta de reciclaje de las baterías de los vehículos vendidos durante el año 2026 en España. Permite planificar los picos de capacidad operativa e industrial entre los años 2034 y 2036.

Approximately nine in ten organisations report using AI after the emergence of Generative AI but training, policy and public confidence are moving very slowly in comparison. The increasing gap is raising public concerns. Gaps exists in multiple fronts and we cannot afford to leave those gaps open as AI is not just a technology in today's world, it is becoming a political lever. Understanding these multi-frontal gaps is essential in overcoming the fear of AI and to effectively leverage its advances.