1 day course 
Supporting material 
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Generative AI is being used to develop new products and services – such as personalized marketing communications, chatbots for interacting with customers, and virtual assistants – across multiple industries.
On this course, you’ll explore the use of text generation 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’ll learn how to design and tune prompts to ensure the best outputs for your applications and discuss how to fine-tune foundational models to improve model output quality.
This Text Generation for Applications Using Gen AI Studio course is available as a private training session that can be delivered via Virtual Classroom or at a location of your choice in South Africa.
Course overview
Who should attend:
This course is for developers looking to leverage Generative AI in their applications, and machine learning practitioners who are supporting the development of GenAI-powered applications.
What you'll learn:
By the end of this course, you will be able to:
- 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
- Implement the PaLM API into your applications using the Python SDK
- Fine-tune foundation model weights to improve model output quality
Prerequisites
To get the most out of this course, you should have a basic understanding of either programming in Python or leveraging APIs in applications.
Basic familiarity with Google Cloud and Vertex AI as covered in the Google Cloud Fundamentals: Big Data and Machine Learning course is also required.
Course agenda
- Vertex AI on Google Cloud
- Generative AI options on Google Cloud
- Introduction to the course use case (text generation)
- Introduction to Gen AI Studio
- Available models and use cases
- Designing and testing prompts in the Cloud Console
- Data governance in Gen AI Studio
- Lab: Getting started with Vertex AI, Gen AI Studio's User Interface
- Why is prompt design so important?
- Zero-shot vs. few-shot prompting
- Providing additional context and instruction-tuning
- Best practices
- Lab: Question Answering with Generative Models on Vertex AI
- 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 text generation
- Lab: Use the PaLM API to integrate GenAI into Applications
- Scenarios to use model tuning
- Workflow for model tuning
- Preparing your model tuning dataset
- Create a model tuning job
- Loading a tuned model
- Demo: Fine-tuning models for your specific use case