- Google Cloud Fundamentals: Core Infrastructure
- Architecting with Google Compute Engine

- Developing Applications with Google Cloud Platform
- Application Development with Cloud Run
- Logging, Monitoring and Observability in Google Cloud

- Architecting with Google Kubernetes Engine
- Architecting Hybrid Cloud Infrastructure with Anthos

- From Data to Insights with Google Cloud Platform(1)
- Big Data & Machine Learning Fundamentals(2)
- Analyzing and Visualizing Data in Looker(3)
- Developing Data Models with LookML(4)

- Data Engineering on Google Cloud
- Serverless Data Processing with Dataflow

- Developing Applications on Google Cloud
- Enterprise Database Migration
- Migrating MySQL data to Cloud SQL using Database Migration Service

- Developing APIs with Google Cloud's Apigee API Platform

- Networking in Google Cloud

- Google Cloud Big Data & Machine Learning Fundamentals
- Machine Learning on Google Cloud
- Advanced Machine Learning with TensorFlow on Google Cloud Platform
- MLOps (Machine Learning Operations) Fundamentals
- ML Pipelines on Google Cloud

- Introduction to Digital Transformation with Google Cloud
- Innovating with Data and Google Cloud
- Infrastructure and Application Modernization with Google Cloud
- Understanding Google Cloud Security and Operations

Achieving Advanced Insights with BigQuery - [1.6]
Analyzing and Visualizing Data in Looker - [1.1]
Application Development with Cloud Run - [2.0]
Applying Machine Learning to your Data with GCP - [1.6]
Architecting Hybrid Cloud Infrastructure with Anthos - [2.0.1] Architecting Hybrid Infrastructure with Anthos Architecting with Google Cloud: Design and Process - [2.0]
Architecting with Google Compute Engine - [2.2]
Building conversational experiences with Dialogflow Building Solutions with Apigee X - [1.0]
Creating New BigQuery Datasets and Visualizing Insights - [1.6]
Customer Experiences with Contact Center AI - [1.1]
Customer Experiences with Contact Center AI - Dialogflow CX - [2.0]
Customer Experiences with Contact Center AI - Dialogflow ES - [2.0]
Data Engineering on Google Cloud - [2.5]
Data Integration with Cloud Data Fusion - [1.0]
Data Warehousing with BigQuery: Storage Design, Query Optimization, and Administration (ILT) - [1.0] Deploying and Managing Google Cloud VMware Engine - [2.7]
Deploying and Migrating to Google Cloud VMware Engine - [1.5]
Developing APIs with Google Cloud's Apigee API Platform - [3.0.0]
Developing Applications with Cloud Functions on Google Cloud - [1.0]
Developing Applications with Google Cloud - [1.4]
Developing Data Models with LookML - [1.1]
Enterprise Database Migration - [1.0]
Exploring ​and ​Preparing ​your ​Data with BigQuery
From Data to Insights with Google Cloud Platform - [1.6]
G Suite - Work transformation
GenAI Study Jam - Generative AI Explorer - [1.0]
Getting Started with FinOps on Google Cloud - [1.1]
Getting Started with Google Kubernetes Engine - [2.0]
Getting Started with Terraform for Google Cloud - [1.0]
Google Cloud Big Data & Machine Learning Fundamentals - [2.1]
Google Cloud Big Data and Machine Learning Fundamentals - [3.0]
Google Cloud Fundamentals for AWS Professionals Google Cloud Fundamentals for Azure Professionals Google Cloud Fundamentals for Researchers - [1.0]
Google Cloud Fundamentals: Core Infrastructure - [5.1] -
Google Cloud Platform Big Data and Machine Learning Fundamentals - [1.3]
Google Cloud Platform Fundamentals for AWS Professionals - [2]
Google Workspace - Work Transformation - [1.1]
Hybrid Infrastructure with Anthos for Partners - [1.74]
Installing and Managing Google Cloud's Apigee API Platform for Private Cloud - [2.0.0]
Interactive Chat for Applications using Generative AI Studio - [1.0] Introduction to AI and Machine Learning on Google Cloud - [v.1.0]
Introduction to Responsible AI in Practice - [1.0]
Introduction to Vertex Forecasting and Time Series in Practice - [v.1.0]
Launching into Machine Learning - [2.0] Logging, Monitoring and Observability in Google Cloud - [2.0]
Looker Developer Deep Dive - [1.0]
Machine Learning on Google Cloud - [3.5]
Machine Learning with TensorFlow on Google Cloud - [2.0]
Managing a Data Mesh with Dataplex - [1.0]
Managing Google Cloud's Apigee API Platform for Hybrid Cloud - [2.0]
Marketing Analytics Solutions for Partners - [1.2.2]
Migrating Amazon Redshift Users to BigQuery - [1.0]
Migrating Snowflake Users to BigQuery - [1.0]
Migrating Teradata Users to BigQuery - [1.0]
Networking in Google Cloud - [2.0]
roi-anthos-dev - [1.0]
Security in Google Cloud - [3.0] Serverless Data Processing with Dataflow (ILT) - [1.0]
Text Generation for Applications using Generative AI Studio - [1.0]
Understanding Cloud Spanner - [1.0]
Vertex AI Forecasting - [1.0] Vertex AI Model Garden - [1.0]
VM Migration for Partners - [1.60]