Profile picture of Alfredo Deza

Alfredo Deza

Cloud Advocate -
Microsoft

Alfredo Deza is a software engineer, speaker, author, and former Olympic athlete working as a Cloud Advocate for Microsoft. He has written several books about programming languages and artificial intelligence, and has created online courses about the cloud and machine learning.
He currently is an Adjunct Professor at Duke University, and as part of his role, works closely with universities around the world like Georgia Tech, Duke University, and Carnegie Mellon, where he often gives guest lectures about technology.

Sessions Presenting

Introducción a Azure OpenAI Assistants

Mexico City
Session Ended
Breakout
Tuesday, September 24
5:15 PM - 6:00 PM Greenwich Mean Time
Taller 4
BRK443-MX
Imagínese un sistema de inteligencia artificial que no solo brinde respuestas creativas y claras, sino que también tome decisiones y actúe. Adéntrese en el futuro de la inteligencia artificial y vea cómo puede aprovechar todo el poder de los LLM creando su agente de inteligencia artificial.
Tuesday, September 24
7:45 PM - 8:30 PM Greenwich Mean Time
Sala para sesión de subgrupo 2
BRK432-MX
En esta sesión se cubrirá el uso de GitHub Copilot para resolver un escenario real donde una aplicación de comercio electrónico tiene problemas de rendimiento. Se utilizará GitHub Copilot para entender la base de código desconocida y luego explorar y aplicar una solución.
Tuesday, December 3
4:15 PM - 5:00 PM Greenwich Mean Time
Workshop 1, North Room 202B, Level 200
BRK460-CA
Micrososft Fabric is changing data teams landscape by providing an integrated platform to enable collaboration among data, AI, BI and application development professionals. Join us to learn and see the latest announcements and what the future holds.
Tuesday, December 3
8:00 PM - 8:45 PM Greenwich Mean Time
Breakout 2, North Hall A, Level 300
BRK432-CA
This session will cover using GitHub Copilot to solve a real-world scenario where an ecommerce application is having performance issues. GitHub Copilot will be used to understand the unfamiliar codebase and then explore and apply a solution.