01
Multimodal Retrieval Augmented Generation (RAG) using the Gemini API in Vertex AI
In this lab, you learn how to perform multimodal retrieval augmented generation (RAG) using Gemini API in Vertex AI.
Google Cloud Next 2025
Get a head start on Google Cloud Next 2025 with a learning path designed for all skill levels. Explore core topics like data analytics, machine learning, and security through hands-on labs, building practical experience and confidence. A great path for developers looking to boost their skills before and after the event.
02
Custom Document Extraction with Document AI Workbench
In this lab, you will create and train a Custom Document Extractor that processes W-2 (US tax form) documents.
03
Get Started with Vertex AI Studio
In this lab, you will learn how to use Vertex AI Studio to create prompts and conversations with Gemini's multimodal capabilities.
04
Intro to Gemini 2.0 Flash
In this lab, you will learn how to use the Gemini API in Vertex AI and the Google Gen AI SDK for Python with the Gemini 2.0 Flash model.
05
Intro to Generating and Executing Python Code with Gemini 2.0
In this lab, you will learn how to generate and execute code using the Gemini API in Vertex AI and the Google Gen AI SDK for Python with the Gemini 2.0 Flash model.
06
Introduction to Vertex AI Embeddings: Text and Multimodal
In this lab, you will explore the Vertex AI Embeddings API for both Text and Multimodal (Images and Video) use cases.
07
Build a Chat Application using the Gemini API on Cloud Run
In this lab, you build and deploy an AI-based chat application on Cloud Run that utilizes a Gemini model.
08
Build a DIY Multimodal Question Answering System with Vertex AI
In this lab, you will learn how to build a question answering system that understands both text and images with Vertex AI.
09
Utilize the Streamlit Framework with Cloud Run and the Gemini API in Vertex AI
In this lab, you will learn how to deploy a Streamlit app integrated with Gemini Pro on Cloud Run.
10
Analyze Customer Reviews with Gemini Using SQL
Learn how to use BigQuery Machine Learning with remote models (Gemini) to analyze customer reviews using SQL.
11
Develop Code with Gemini in BigQuery
In this lab you learn how to use Gemini code generation, explanation and suggestions in BigQuery.
12
Explore Data with Gemini in BigQuery
In this lab you will learn how to use Table Explorer and Data Insights with Gemini in BigQuery.
13
Create a RAG Application with BigQuery
In this lab, you learn how to create a RAG pipeline from embeddings, vector search, to generation with Gemini in BigQuery.
14
Build a BI Dashboard Using Looker Studio and BigQuery
In this lab, you will learn how to build a BI dashboard with Looker Studio as the front end, powered by BigQuery on the back end.
15
Loading Data into Cloud SQL
In this lab, you import data from CSV text files into Cloud SQL and then carry out some basic data analysis using simple queries.
16
Cloud Spanner - Database Fundamentals
In this lab, you perform basic administrative tasks within a Cloud Spanner instance.
17
Migrating to AlloyDB from PostgreSQL Using Database Migration Service
In this lab, you migrate a stand-alone PostgreSQL database (running on a virtual machine) to AlloyDB for PostgreSQL using a continuous Database Migration Service job with VPC peering for connectivity.
18
Debugging Apps on Google Kubernetes Engine
This lab teaches you how logging works on GKE and some best practices for log collection by going through some common logging use cases.
19
Continuous Delivery with Google Cloud Deploy
Create a delivery pipeline using Google Cloud Deploy, create a release for a basic application, and promote the application through a series of Google Kubernetes Engine targets
20
Analyze BigQuery Usage with Log Analytics
Use Log Analytics for in-depth usage logs analysis through SQL querires from the Cloud Logging page.
21
Building a High-throughput VPN
In this lab you learn how to create a secure, high-throughput VPN and test the speed.
22
Orchestrating the Cloud with Kubernetes
In this lab, you learn how to provision a complete Kubernetes cluster using Google Kubernetes Engine, deploy and manage Docker containers using kubectl, and break an application into microservices using Kubernetes' Deployments and Services.
23
Creating Cross-region Load Balancing
This lab demonstrates how to create an HTTP(S) load balanced that forwards traffic to instances in two different regions.
24
Infrastructure as Code with Terraform
In this hands-on lab you will build, change, provision, and destroy infrastructure using Terraform in the cloud environment.
25
Networking 101
Learn how to set up a network, add 3 subnetworks, then apply firewall rules.
26
VPC Networking Fundamentals
In this lab you create an auto-mode VPC network with firewall rules and 2 VM instances, then explore the connectivity for the VM instances.
27
ETL Processing on Google Cloud Using Dataflow and BigQuery (Python)
In this lab, you build several data pipelines that ingest and transform data from a publicly available dataset into BigQuery.
28
Gmail Sentiment Analysis with Gemini and Vertex AI
In this lab you build a Google Workspace add-on that uses Gemini and Vertex AI to analyze Gmail sentiment, automatically labeling negative emails for prioritized handling.