4:00 午後 - 5:00 午後 (UTC)

About this series: This series will cover the art of engineering prompts to enable users to use Azure Open AI Large Language Models to their maximum capabilities. The series consists of 3 sessions covering the basics of prompt engineering all the way to advanced prompt engineering techniques Who is it aimed at? If you're looking to start developing solutions using LLMs, or if you have been using LLMs for a while and are looking to maximize your LLMs capabilities, this series is for you. Why should I attend: The concept of AI-powered copilots is becoming a reality, and we're diving into a world where there will be a copilot for everything. As we sail down this path, more and more companies and brands exploring how to setup their own internal and customer facing copilots. With that said, this series will help you understand the art of the possible with LLMs using prompt engineering, which will be critical for when you are building copilots for your company or yourself. Learn more and improve your skills with prompt engineering with these two modules below: https://aka.ms/ApplyPromptEngineering1 https://aka.ms/DevelopGenAISolutions1 About this session: In this session, we will cover the basics of prompt engineering, enabling users to select their first Azure Open AI model and build good prompts to get them started with LLMs

4:00 午後 - 5:00 午後 (UTC)

About this series: This series will cover the art of engineering prompts to enable users to use Azure Open AI Large Language Models to their maximum capabilities. The series consists of 3 sessions covering the basics of prompt engineering all the way to advanced prompt engineering techniques Who is it aimed at? If you're looking to start developing solutions using LLMs, or if you have been using LLMs for a while and are looking to maximize your LLMs capabilities, this series is for you. Why should I attend: The concept of AI-powered copilots is becoming a reality, and we're diving into a world where there will be a copilot for everything. As we sail down this path, more and more companies and brands exploring how to setup their own internal and customer facing copilots. With that said, this series will help you understand the art of the possible with LLMs using prompt engineering, which will be critical for when you are building copilots for your company or yourself. Learn more and improve your skills with prompt engineering with these two modules below: https://aka.ms/ApplyPromptEngineering1 https://aka.ms/DevelopGenAISolutions1 About this session: In this session, we will dive into common prompt engineering techniques that are used today based on the latest research. These techniques will enable users to get more accurate responses from LLMs and experiment with different approaches to achieve desired outcomes

4:00 午後 - 5:00 午後 (UTC)

About this series: This series will cover the art of engineering prompts to enable users to use Azure Open AI Large Language Models to their maximum capabilities. The series consists of 3 sessions covering the basics of prompt engineering all the way to advanced prompt engineering techniques Who is it aimed at? If you're looking to start developing solutions using LLMs, or if you have been using LLMs for a while and are looking to maximize your LLMs capabilities, this series is for you. Why should I attend: The concept of AI-powered copilots is becoming a reality, and we're diving into a world where there will be a copilot for everything. As we sail down this path, more and more companies and brands exploring how to setup their own internal and customer facing copilots. With that said, this series will help you understand the art of the possible with LLMs using prompt engineering, which will be critical for when you are building copilots for your company or yourself. Learn more and improve your skills with prompt engineering with these two modules below: https://aka.ms/ApplyPromptEngineering1 https://aka.ms/DevelopGenAISolutions1 About this session: In this sessions, we will dive deeper into some of the previous techniques we discussed, and we will also focus on state-of-the-art techniques to achieve the most out of LLMs and push them to their limits.