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AI Research and Innovation Hub
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Learning Resources
Documentation, tutorials, and cloud guides for AI researchers.
Workshops and Tutorials
Introduction to Data Analytics & AI on Google Cloud
From Raw Data to Real Insights
by Paggie Chen and Chawki Tawbi
(Google Cloud)
PDF
Google BigQuery & AI Hands-On Demo
Practical guide to cloud-native data warehousing
by Paggie Chen
(Google Cloud)
PDF
100+ Ways to Use Gemini in Education
Gemini for Education, Google NotebookLM, and Gemini in Classroom
Google Cloud Training
(Google Cloud)
PDF
Google BigQuery & AI Hands-On Demo
Video Walkthrough: Mastering Cloud Analytics & AI Integration
by Paggie Chan
(Google Cloud)
MP4 Video
Stay tuned for more workshops and tutorials...
Documentation
Compute Engine
The researcher has the flexibility to install their software and tools and manage their VM alone. Full control over virtual machines with custom configurations, GPUs, and TPUs.
Google Cloud
Vertex AI
Fully managed AI platform. The researcher focuses on their code and skips the burden of managing the infrastructure. End-to-end ML workflow support.
Google Cloud
Cloud Storage
Scalable object storage for training data, models, and checkpoints. Storage classes, lifecycle management, and best practices.
Google Cloud
Databases
Fully managed database solutions including Cloud SQL, AlloyDB, Spanner, and Bigtable for structured and unstructured data storage.
Google Cloud