Course Overview
In this course, you explore tools and APIs available on Google Cloud for integrating large language models (LLMs) into your application. After exploring generative AI options on Google Cloud, next you explore LLMs and prompt design in Vertex AI Studio. Then you learn about LangChain, an open-source framework for developing applications powered by language models. After a discussion around more advanced prompt engineering techniques, you put it all together to build a multi-turn chat application by using LangChain and the Vertex AI PaLM API.
Moyens d'évaluation :
- Quiz pré-formation de vérification des connaissances (si applicable)
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
- Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences
Who should attend
Application developers and others who wish to leverage LLMs in applications.
Prerequisites
Completion of Introduction to Developer Efficiency with Gemini on Google Cloud (IDEGC) or equivalent knowledge.
Course Objectives
- Explore the different options available for using generative AI on Google Cloud.
- Use Vertex AI Studio to test prompts for large language models.
- Develop LLM-powered applications using LangChain and LLM models on Vertex AI.
- Apply prompt engineering techniques to improve the output from LLMs.
- Build a multi-turn chat application using the PaLM API and LangChain.
Moyens Pédagogiques :