Lo que todo el mundo en Ciencia de Datos debe saber sobre enseñar y aprender

Las personas que hacen ciencia de datos aprenden constantemente tecnologías nuevas y en rápida evolución. A menudo se encuentran en un papel de enseñanza, ya sea mentoreando, generando tutoriales, escribiendo artículos, dando charlas, o incluso enseñando más formalmente en universidades, sin estar formalmente preparados para ese papel. En esta charla, revisaremos estrategias prácticas, basadas en evidencia, para organizar y diseñar lecciones y materiales, explicar los conceptos al nivel de tus estudiantes, usar ejemplos relevantes, comprobar la comprensión y conectar con tus estudiantes, de modo que puedan ser más efectivos la próxima vez que debas enseñar

What Everyone In Data Science Should Know About Teaching And Learning

Data scientists, programmers, statisticians are constantly learning new and rapidly evolving technologies. They often find themselves in a teaching role, either as mentors, generating tutorials, writing blog posts, giving talks, or even teaching more formally at universities or boot camps, without being formally prepared for that role. In this talk, we will review practical, evidence-based strategies for organizing and designing your lessons and materials, explaining concepts at the level of your students, using relevant examples, checking understanding, and connecting with students so that you can be more effective the next time you find yourself in a teaching position.

Datos y digitalización del sector agropecuario

Episodio 67. Una conversación con Yanina Bellini

Building inclusive communities.

The idea of the panel was to share the experience of the growth of the R community in Latin America, so I made a time line with the last 5 years rescuing the most important milestones (of which I have been part as an organizer, as an assistant or enjoying them as a member of the community).

Gaps & Opportunities for Inclusive Multilingual Data Science

Panellists for this fireside chat come from diverse backgrounds and experiences across academia, industry and communities in research and data science where the translation aspect is one of their main focus areas. As members of multiple open sciences and research groups across the Global South and North, they will explore a range of questions and they will bring their combined perspectives as community builders, educators, trainers, researchers and engineers working on projects at both local and global scales.