Jest członkiem od 2025
Create Generative AI Apps on Google Cloud
Earned lut 26, 2025 EST
Podstawy: dane, uczenie maszynowe, AI
Earned lut 25, 2025 EST
The Basics of Google Cloud Compute
Earned lut 23, 2025 EST
Integrating Applications with Gemini 1.0 Pro on Google Cloud
Earned lut 9, 2025 EST
Generative AI Explorer - Vertex AI
Earned lut 7, 2025 EST
Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud? In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application.
Big data, uczenie maszynowe i sztuczna inteligencja to najpopularniejsze tematy współczesnej informatyki, jednak to dość wyspecjalizowane dziedziny i trudno znaleźć materiały wprowadzające do nich. Na szczęście Google Cloud udostępnia przyjazne dla użytkownika usługi w tych obszarach, a dzięki temu kursowi dla początkujących możesz poznać podstawy narzędzi takich jak BigQuery, Cloud Speech API i Video Intelligence.
Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
This short course on integrating applications with Gemini 1.0 Pro models on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 1.0 Pro and Gemini 1.0 Pro Vision models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.
The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.