A collection of resources that helps everyone learn more about Google Generative AI offerings.
Please submit additional resources via a PR.
- Generative AI on Google Cloud
- Overview of Generative AI on Vertex AI
- Certifications and security controls
- Responsible AI best practices
- Quotas and Limits
- Pricing
- Use Vertex AI to interact with, customize, and embed foundation models into your applications
- Access foundation models on Model Garden
- Tune models via a simple UI on Vertex AI Studio
- Use Vertex AI Agent Builder, to build and deploy AI agents grounded in their data
- Google foundation models
- Gemini, a multimodal model from Google DeepMind, is capable of understanding virtually any input, combining different types of information, and generating almost any output.
- Prompt and test Gemini in Vertex AI using text, images, video, or code.
- Gemini Code Assist offers AI-powered assistance to help developers build applications with higher velocity, quality, and security in popular code editors like VS Code and JetBrains, and on developer platforms like Firebase.
- Gemini for Google Cloud offerings assist users in working and coding more effectively, gaining deeper data insights, navigating security challenges, and more.
- Quickstart tutorial using Vertex AI Studio or the Vertex AI API
- Explore pretrained models in Model Garden
- Tune a Foundation model
- Intro to Gen AI - Playlist
- Gen AI for Developers
- Gemini for Google Cloud - Playlist
- Gemini for Application Developers
- Gemini for Cloud Architects
- Gemini for Data Scientists and Analysts
- Gemini for Network Engineers
- Gemini for Security Engineers
- Gemini for Cloud DevOps Engineers
- Gemini end-to-end Software Development Lifecycle
- Technical training courses in Generative AI from Google Cloud
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Beginner: Introduction to Generative AI Learning Path: This learning path provides an overview of generative AI concepts, from the fundamentals of large language models to responsible AI principles. This learning path currently has several courses listed below:
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Intermediate: Gemini for Google Cloud Learning Path: The Gemini for Google Cloud learning path provides examples of how Gemini can help make engineers of all types more efficient in their daily activities.
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Advanced: Generative AI for Developers Learning Path: A Generative AI Learning Path with a technical focus, built for App Developers, Machine Learning Engineers, and Data Scientists. Recommended prerequisite: Introduction to Generative AI learning path.
- Introduction to Image Generation
- Attention Mechanism
- Encoder-Decoder Architecture
- Transformer Models and BERT Model
- Create Image Captioning Models
- Introduction to Vertex AI Studio
- Vector Search and Embeddings
- Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
- Responsible AI for Developers: Fairness and Bias
- Responsible AI for Developers: Interpretability & Transparency
- Machine Learning Operations (MLOps) for Generative AI