Intro to Generative AI training with GCP

Description:

Several students think that understanding and using Generative AI requires and in-depth knowledge of AI and Machine Learning – that is absolutely false. This introductory level course is designed to introduce you to the world of Generative AI using the Google Cloud Platform. You will learn the fundamentals of generative AI, explore key GCP tools and services, and gain hands-on experience in using Vertex AI (flagship service on GCP) tools. We will discuss several Generative AI Services: Brad, PaLM (Prompt Assisted Language Model) API, Generative AI Studio, MakerSuite and lot more. At the end of this course, you will have the knowledge and skills to kickstart your journey into Generative AI on GCP.

Duration: 1 Day

Course Code: BDT305

Learning Objectives:

After this course, you will be able to:

• Understand the basics of generative AI and its applications
• Generative AI on GCP
• Create prompt designs for generative AI tasks
• Implement PaLM API for generating text
• Working with embedding to enhance model performance

• Basic knowledge of GCP and Python

• Intro to Generative AI training with GCP is designed anyone interested in Generative AI and GCP including Data scientists, developers, business analysts, AI enthusiasts who want to get started using Generative AI tools provided on Google Cloud Platform

• Intro to Generative AI training with GCP is designed anyone interested in Generative AI and GCP including Data scientists, developers, business analysts, AI enthusiasts who want to get started using Generative AI tools provided on Google Cloud Platform

Topic Outline:

1. Understanding the basics of generative AI and its applications

• Core concepts of Generative AI
• AI vs ML vs Generative AI
• Generative AI – self supervised learning
• Lab Demo: Exploring GCP ecosystem and AI services highlighting their relevance to generative AI

2. Generative AI on GCP

• Explore Generative AI foundation models
• Exploring Text features: Summarization, Classification
• Exploring Text features: Extraction, Ideation
• Lab: Using Generative AI Studio

3. Prompt Design

• Getting started with prompt design
• Using zero shot, one shot and few shot prompts
• Exploring prompt frameworks such as RTF, CTF, RASCEF
• Understanding parameters
• Lab: Using Generative AI with Vertex AI workbench

4. Implement the PaLM API for text generation

• Explore PaLM API and its capabilities
• Using Vertex AI PaLM API for Text
• Exploring Chat model
• Exploring Code model
• Exploring Speech model
• Demo: Using PaLM API with Vertex AI

5. Working with Embeddings

• What are embeddings?
• Using embeddings for text similarity
• Basics of LangChain
• Tuning Large Language Models
• Labs: Embedding Similarity

Training material provided: Yes (Digital format)

Hands-on Lab: Students should create a “Qwiklabs” Account using the following link: https://www.cloudskillsboost.google/, instructions will be sent out prior to the class.