Search with AI Applications
Earned juin 20, 2024 EDT
Vector Search and Embeddings
Earned juin 19, 2024 EDT
Generative AI Explorer : Vertex AI
Earned juin 2, 2024 EDT
Text Prompt Engineering Techniques
Earned juin 1, 2024 EDT
Generative AI for Business Leaders
Earned mai 30, 2024 EDT
Introduction to Vertex AI Studio
Earned mai 24, 2024 EDT
Introduction to Image Generation
Earned mai 23, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned mai 23, 2024 EDT
Introduction to Responsible AI
Earned mai 22, 2024 EDT
Introduction to Large Language Models
Earned mai 21, 2024 EDT
Introduction to Generative AI
Earned mai 21, 2024 EDT
(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine.
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This content is deprecated. Please see the latest version of the course, here.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
Search with AI Applications
Earned juin 20, 2024 EDT
Vector Search and Embeddings
Earned juin 19, 2024 EDT
Generative AI Explorer : Vertex AI
Earned juin 2, 2024 EDT
Text Prompt Engineering Techniques
Earned juin 1, 2024 EDT
Generative AI for Business Leaders
Earned mai 30, 2024 EDT
Introduction to Vertex AI Studio
Earned mai 24, 2024 EDT
Introduction to Image Generation
Earned mai 23, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned mai 23, 2024 EDT
Introduction to Responsible AI
Earned mai 22, 2024 EDT
Introduction to Large Language Models
Earned mai 21, 2024 EDT
Introduction to Generative AI
Earned mai 21, 2024 EDT