This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI...
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to...
Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini...
In this course, you will learn about the various services Google Cloud offers for modernizing retail applications and infrastructure. Through a series of lecture content and hands-on labs, you will gain practical experience deploying cutting-edge retail and ecommerce solutions on...
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on...
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache...
This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.
This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps...
This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in...
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In this lab, you use BigQuery for data processing and exploratory data analysis, and the Vertex AI platform to train and deploy a custom TensorFlow Regressor model to predict customer lifetime value (CLV). The goal of the lab is to...
In this lab, you will learn how to use Vertex AI Studio to create prompts and conversations with Gemini's multimodal capabilities.
In this lab, you will learn how to use the Gemini API in Vertex AI.
This challenge lab tests your skills and knowledge from the labs in the Explore Generative AI with the Gemini API in Vertex AI course. You should be familiar with the content of the prior labs before attempting this lab.
This challenge lab tests your skills and knowledge from the labs in the Prompt Design in Vertex AI course. You should be familiar with the content of the prior labs before attempting this lab.
In this challenge lab you will train, deploy, and create a model pipeline using Vertex AI.
In this lab, you learn how to perform multimodal retrieval augmented generation (RAG) using Gemini API in Vertex AI.
Learn how to use grounding in Vertex AI to generate content grounded in your own documents and data.
This lab is part of a series designed to provide hands-on experience with Generative AI on Google Cloud.
This challenge lab evaluates your understanding of Google's Vertex AI SDK for integrating generative AI models to build an Image generator app, and an app which enables you to ask questions about images and receive insightful text-based responses.