This course introduces the fundamentals of AI agents and explores where agents add value in the real world. It provides a foundation for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior. Explore other content in the Gemini Agent Ready (GEAR) program.
Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.
Hey there! You're invited to game on with Skills Boost Arcade Trivia for October Week 1! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the October Trivia Week 1 badge!
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. Explore other content in the Gemini Agent Ready (GEAR) program.
This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.
This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
Earn the Introductory Skill Badge by completing the Implement Speech and Language Solutions with Pre-trained APIs course, where you learn how to use speech related API tools to synthesise and transcribe speech.
Earn a skill badge by completing the Build Google Cloud Infrastructure for AWS Professionals course, where you learn how to configure IAM permission, orchestrate workloads using Kubernetes, host a web application using compute engine, and configure load balancing.
Questo corso tratta la creazione di modelli ML con TensorFlow e Keras, il miglioramento dell'accuratezza dei modelli ML e la scrittura di modelli ML per l'uso su larga scala.
Ottieni il corso intermedio con badge delle competenze Prepara i dati per le API ML su Google Cloud per dimostrare le tue competenze nei seguenti ambiti: pulizia dei dati con Dataprep di Trifacta, esecuzione delle pipeline di dati in Dataflow, creazione dei cluster ed esecuzione dei job Apache Spark in Managed Service for Apache Spark e richiamo delle API ML tra cui l'API Cloud Natural Language, l'API Google Cloud Speech-to-Text e l'API Video Intelligence.
Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.
Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'AI generativa, come viene utilizzata e in che modo differisce dai tradizionali metodi di machine learning. Descrive inoltre gli strumenti Google che possono aiutarti a sviluppare le tue app Gen AI.
Questo corso illustra i vantaggi dell'utilizzo di Vertex AI Feature Store, come migliorare l'accuratezza dei modelli di ML e come trovare le colonne di dati che forniscono le caratteristiche più utili. Il corso include inoltre contenuti e lab sul feature engineering utilizzando BigQuery ML, Keras e TensorFlow.
Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
Questo corso presenta le offerte di intelligenza artificiale (AI) e machine learning (ML) su Google Cloud per la creazione di progetti di AI predittiva e generativa. Esplora le tecnologie, i prodotti e gli strumenti disponibili durante tutto il ciclo di vita data-to-AI, includendo le basi, lo sviluppo e le soluzioni di AI. Ha lo scopo di aiutare data scientist, sviluppatori di AI e ML engineer a migliorare le proprie abilità e conoscenze attraverso attività di apprendimento coinvolgenti ed esercizi pratici.