Google Cloud Skills
Google Cloud training
Browse learning paths, courses, labs, and skill badges across Google Cloud topics.
Browse Google Cloud trainingGCP
Google Cloud (GCP)
Learn Google Cloud foundations, Vertex AI and Gemini application patterns, data grounding, deployment, and reliable operations.
Start with the first guideYour outcome
Build and explain a secure, evaluated AI application on Google Cloud.
Core curriculum
The skills to practice
Projects and IAM
Gemini and managed AI platforms
Model evaluation
Grounded generation
Cloud Run deployment
Monitoring and cost
Guided path
Google Cloud AI application builder
Move from Google Cloud foundations to a grounded, evaluated AI application with a deployable service and an operations plan.
Suggested pace: 5 weeks · Capstone: A grounded Gemini application on Google Cloud
0 of 5 complete
- 01
Map Google Cloud foundations
Identify the project, billing, IAM, APIs, and environment boundaries your workload needs.
- 02
Study the generative AI developer path
Compare model options and define a small task-specific evaluation set before choosing a model.
- 03
Design the application lifecycle
Write the use case, model choice, grounding strategy, evaluation criteria, and deployment constraints.
- 04
Explore Google's managed AI platform
Prototype one application flow and record quality, latency, and safety observations.
- 05
Review architecture and operations
Document identity, reliability, monitoring, cost controls, and a rollback or shutdown plan.
Provider learning materials
Learn from official training and documentation.
Migo Mind's sequence is an independent study map. These links open the provider's own courses and technical references; availability, account requirements, and pricing can change.
Google Skills
Generative AI for developers
A technical learning path for developers, machine-learning engineers, and data scientists working with generative AI on Google Cloud.
Open the developer learning pathGoogle Cloud documentation
Develop a generative AI application
Follow the application lifecycle from selecting a model through customization, evaluation, and deployment.
Read the application guideGoogle Cloud documentation
Gemini Enterprise Agent Platform guide
Use the current platform documentation to study model access, application development, and managed AI capabilities.
Explore the AI platform guideGoogle Cloud Architecture Center
Google Cloud Well-Architected Framework
Review architecture principles for security, reliability, operations, performance, and cost.
Read the architecture framework