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Interactive Chat for Applications using Gen AI Studio
Code:
GCP-ICA-GAIS
Duration:
1 Day
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$900
USD
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Generative AI is being used to develop new products and services across multiple industries, such as personalized marketing communications, chatbots for interacting with customers, and virtual assistants. For example, It can also be used to create chatbots that can answer customer questions and provide customer support.
In this course, you will explore the use of interactive multi-turn chat models using Gen AI Studio on Vertex AI and learn how to incorporate those models into your application using the PaLM API and client libraries. You will learn how to design and test chat prompts to ensure the best outputs for your applications and discuss how to choose parameters for the PaLM API to improve response quality for your use case.
This course is available in the following formats:
Duration: 1 Day
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Delivery Format: Virtual Classroom
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$ 900 |
- Understand Vertex AI generative AI options for your applications
- Explore Gen AI Studio to interact with foundation models
- Design and tune chat prompts for your Generative AI use cases
- Understand the effect of changing PaLM API parameters on model responses
- Implement the PaLM API into your applications using the Python SDK
Module 1 Generative AI on Vertex AI
- Vertex AI on Google Cloud
- Generative AI Options on Google Cloud
- Introduction to the Course Use Case (Interactive Chat)
Module 2 Gen AI Studio
- Introduction to GenAI Studio
- Available models and use cases
- Designing and testing prompts in the Cloud Console
- Data governance in GenAI Studio
- Lab: Getting started with Vertex AI Gen AI Studio's User Interface
Module 3 Prompt Design
- Why is prompt design so important?
- Zero-shot, one-shot and few-shot prompting
- Providing additional context and examples
- Best practices
- Lab: Prompt Design for Multi-turn Chat in Gen AI Studio
Module 4 Implementing the PaLM API
- Lab: Getting Started with the Vertex AI PaLM API & Python SDK
- Introduction to the PaLM API
- Utilizing generative models using the Python SDK
- Understanding model parameters for multi-turn chat
- Lab: Use the PaLM API to add a chatbot to your application
Module 5 Model Parameters and Output
- Revisit model parameters for chatbots
- Optimizing model parameters for different use cases
- Model output and Responsible AI
Application developers leverage Generative AI in their applications and machine learning practitioners supporting the development of GenAI-powered applications.