Harnessing Google Vertex AI Online Course

Harnessing Google Vertex AI Online Course

This course provides a hands-on introduction to Google Vertex AI’s Text-Embeddings API, from environment setup to generating and applying embeddings in real-world scenarios. You’ll learn the fundamentals of embeddings, visualize and run similarity searches, and explore applications in Generative AI and LLMs. With guided exercises, you’ll build scalable solutions like RAG systems and apply embeddings for text generation, information extraction, and multimodal tasks. By the end, you’ll be proficient in leveraging Vertex AI for practical AI-driven applications.

Who should take this Course?

The Harnessing Google Vertex AI Online Course is ideal for data scientists, machine learning engineers, and AI developers who want to build, deploy, and scale ML models using Google Cloud’s Vertex AI platform. It is also suitable for students, researchers, and cloud professionals eager to gain hands-on experience with automated machine learning, model monitoring, and end-to-end AI workflows in a production-ready environment.

What you will learn

• Configure your environment for efficient Vertex AI usage
• Generate embeddings and visualize their relationships effectively
• Apply text generation for classification and summarization tasks
• Implement cosine similarity and search techniques with embeddings
• Build real-world AI solutions using Vertex AI capabilities
• Develop a RAG system and analyze StackOverflow data insights

Course Outline

Introduction

• Introduction and About the Course - Prerequisites
• Course Structure

Development Environment Setup & Google Cloud Platform Setup

• Development Environment Setup and API Costs - Overview
• Google Cloud Setup
• Hands-on: Testing the Vertex AI - Generated a Sentence Embedding

Vertex AI Text Embedding API and Embeddings Crash Course - Deep Dive

• Introduction to Vertex AI and Capabilities - Overview
• OPTIONAL: Embeddings Crash Course
• How are Embeddings Used in GenAI and LLMs and Use Cases
• The Embeddings API - Text vs Multimodal Embeddings - Overview
• Task Types and Benefits
• Multimodal Embeddings Diagram
• Hands-on: Embeddings Length - Dimension
• Hands-on: Run Cosine Similarity Search on Different Sentences
• Hands-on: Visualize Embeddings
• Summary

Text Generation with Vertex AI Text Embedding API

• TextGenerationModel - Generating Text Using Bison Model
• Hands-on: Text Generation - Classification Use Case
• Hands-on: Extract Information into Tables and JSON Formats
• Hands-on: Controlling Temperature for the Model
• Hands-on: TopK and TopP
• Hands-on: Transcript Summarization and Extraction

Hands-on: Application and Real-world Use Cases of Embeddings

• Cluster Visualization of StackOverflow Question and Answers in 2D
• Build Your RAG System with the StackOverflow Data
• Scale with the Approximate Nearest Neighbor Search: HNSW vs Cosine Similarity

Next Steps

• Course Summary and Next Steps