Text Generation for Applications using Gen AI Studio Training in France

• Programming in Python
• Leveraging APIs in applications
• Basic familiarity with Google Cloud and Vertex AI as covered in the "Google Cloud Big Data and Machine Learning Fundamentals" course

• Understand Vertex AI generative AI options for your applications
• Explore Gen AI Studio to interact with foundation models
• Design and tune 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

Module 1: Generative AI on Vertex AI

• Vertex AI on Google Cloud
• Generative AI Options on Google Cloud
• Introduction to the Course Use Case (Text Generation)

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

Module 3: Prompt Design

• Why is prompt design so important?
• Zero-shot vs. few-shot prompting
• Providing additional context and instruction-tuning
• Best practices

Module 4: Implementing the PaLM API

• Lab: Getting Started with the Vertex AI PaLM API & Python SDK
• Introduction to the PaLM API
• Utilising generative models using the Python SDK
• Understanding model parameters for text generation

Module 5: Fine-tuning Models

• 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