Navigation
Select a link below to jump to that section:
Summary
Google Cloud Platform (GCP) provides MSU users with scalable, enterprise-grade infrastructure for cloud computing, data management, and AI development. Within GCP, Vertex AI offers a full suite of tools for building, training, deploying, and managing machine learning (ML) and artificial intelligence (AI) models. GCP Vertex AI is designed for research and institutional projects that require advanced data handling, model governance, and integration across Google’s cloud ecosystem.
Back to Top
Description
Google Cloud Platform (GCP) is Google’s comprehensive cloud computing service that provides access to a wide range of tools and APIs for data storage, computing, and AI development.
At the core of GCP’s AI capabilities is Vertex AI, an end-to-end machine learning and artificial intelligence platform that enables users to:
- Train and deploy custom models.
- Access pretrained large language models (LLMs) from Google’s Model Garden.
- Utilize AutoML, Search & Conversation, and Vertex AI Studio for model customization and workflow automation.
GCP with Vertex AI offers both no-code and low-code options for model creation, making it accessible to users with varying levels of technical experience. It is particularly suited for enterprise-scale research and academic projects requiring strong data governance and repeatable model deployment.
Back to Top
Data Classification and Acceptable Use
Use of Google Cloud Platform and Vertex AI must comply with Michigan State University’s data governance and acceptable use policies.
Back to Top
Common Use Cases
GCP with Vertex AI is ideal for large-scale research, analytics, and AI development projects. Examples include:
- Academic Research: Training domain-specific machine learning or language models on research datasets.
- Administrative Analytics: Automating reporting and insights from large institutional data sources.
- Data Science Workflows: Creating predictive models and dashboards for operations and planning.
- Conversational AI Applications: Building departmental chatbots or knowledge assistants using Vertex AI Search & Conversation.
- Interdisciplinary Research: Supporting computational science, bioinformatics, social science modeling, or environmental simulations.
For inspiration and Google case studies, visit: https://cloud.google.com/customers
Back to Top
Initial Purchase and Ongoing Costs
Google Cloud Platform with Vertex AI operates on a pay-as-you-go model at market-rate pricing.
Costs are based on computing usage, data storage, and API requests.
- Each project requires its own Google Cloud billing account linked to a departmental or research funding source.
- Departments are billed monthly by Google according to their project’s resource consumption.
- Budget controls and usage alerts can be configured directly within Google Cloud Platform.
For detailed pricing information, visit: https://cloud.google.com/pricing
Back to Top
How to Request Access
To request access to Google Cloud Platform and create a project with Vertex AI:
- Visit the MSU IT request form:
Create a Google Cloud Project – TeamDynamix Form
- Provide required project and billing information.
- Once approved, your Google Cloud project will be provisioned, and Vertex AI tools will be accessible through the GCP Console.
- Departments may configure access roles for additional project members.
Back to Top
How to Request Assistance
For technical help, billing questions, or general support:
Back to Top
Frequently Asked Questions (FAQs)
Who can use Google Cloud Platform with Vertex AI at MSU?
Access is available to MSU departments, research groups, and authorized faculty or staff requiring enterprise-level data processing or AI development environments.
Can students use GCP or Vertex AI?
Students may participate as collaborators on approved departmental or research projects but cannot independently create billing accounts or manage standalone GCP projects.
Does using Vertex AI require coding experience?
No. While advanced users can write custom code in Python or other languages, Vertex AI also includes no-code and low-code tools like AutoML, Vertex AI Search and Conversation and Vertex AI Studio for model building.
Is data stored in GCP secure?
Yes. GCP complies with industry standards for encryption and security. However, users are responsible for ensuring all data usage aligns with MSU’s data classification and compliance policies.
How are costs managed and billed?
Departments are billed monthly based on usage. GCP includes built-in budget alerts and quota tools to monitor and control expenses.
Where can I learn more about using Vertex AI?
Google offers extensive documentation and tutorials at https://cloud.google.com/vertex-ai. MSU IT also provides training resources at Technology at MSU - AI Training | Michigan State University.
Back to Top
Related Services / Offerings
Back to Top