Introduction to AI and machine learning on Google Cloud

Overview

This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.

Products covered:

• Vertex AI
• Gemini multimodal
• AutoML
• BigQuery ML
• Vertex AI Pipelines
• TensorFlow
• Model Garden
• Vertex AI Studio
• Natural Language API
• Contact Center AI (CCAI)

Prerequisites

Having one or more of the following:

• Basic knowledge of machine learning concepts
• Prior experience with programming languages such as SQL and Python

Who this course is for?

Professional AI developers, data scientists, and ML engineers who want to build predictive and generative AI projects on Google Cloud.

Objectives

• Recognize the data-to-AI technologies and tools provided by Google Cloud.
• Build generative AI projects by using Gemini multimodal, efficient prompts, and model tuning.
• Explore various options for developing an AI project on Google Cloud.
• Create an ML model from end-to-end by using Vertex AI.

Outline

Module 1: AI Foundations

Topics

Why AI?

• AI/ML framework on Google Cloud
• Google Cloud infrastructure
• Data and AI products
• ML model categories
• BigQuery ML
• Lab introduction: BigQuery ML

Activities

• Lab: Predicting Visitor Purchases with BigQuery ML
• Quiz
• Reading

Module 2: AI Development Option

Topics

• AI development options
• Pre-trained APIs
• Vertex AI
• AutoML
• Custom training
• Lab introduction: Natural Language API

Module 3: AI Development Workflow

Topics

• ML workflow
• Data preparation
• Model development
• Model serving
• MLOps and workflow automation
• Lab introduction: AutoML
• How a machine learn

Activities

• Lab: Vertex AI: Predicting Loan Risk with AutoML
• Quiz
• Reading

Module 4: Generative AI

Topics

• Generative AI and workflow
• Gemini multimodal
• Prompt design
• Model tuning
• Model Garden
• AI solutions
• Lab introduction: Vertex AI Studio

Activities

• Lab: Getting Started with Vertex AI Studio
• Quiz
• Reading

Module 5: Course Summary

• Recognize the primary concepts, tools, technologies, and products learned in the course