[DEPRECATED] - Building Conversational Experiences with Dialogflow
Earned apr 3, 2022 EDT
Scientific Data Processing
Earned mag 14, 2020 EDT
DEPRECATED IoT in the Google Cloud
Earned apr 5, 2020 EDT
DEPRECATED Google Cloud's Operations Suite
Earned apr 3, 2020 EDT
Introduzione al ML: elaborazione del linguaggio
Earned mar 28, 2020 EDT
Cloud Hero Speedrun: Leap Day
Earned feb 29, 2020 EST
DevOps Essentials
Earned gen 19, 2020 EST
Advanced ML: ML Infrastructure
Earned gen 19, 2020 EST
Deployment Manager
Earned gen 12, 2020 EST
[DEPRECATED] Deploying Applications
Earned gen 8, 2020 EST
Progettazione cloud
Earned gen 5, 2020 EST
Kubernetes in Google Cloud
Earned gen 5, 2020 EST
Cloud Healthcare API
Earned dic 25, 2019 EST
DEPRECATED Websites and Web Applications
Earned dic 20, 2019 EST
Baseline: Deploy & Develop
Earned dic 4, 2019 EST
App Dev 30-Day Challenge
Earned nov 8, 2019 EST
Machine Learning APIs
Earned nov 4, 2019 EST
Intro to ML: Image Processing
Earned ott 31, 2019 EDT
Cloud Development
Earned ott 30, 2019 EDT
DEPRECATED Application Development - Python
Earned ott 30, 2019 EDT
DEPRECATED Cloud Architecture
Earned ott 27, 2019 EDT
Workspace: Add-ons
Earned ott 25, 2019 EDT
Security & Identity Fundamentals
Earned ott 5, 2019 EDT
DEPRECATED Exploring APIs
Earned ott 5, 2019 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned mag 27, 2019 EDT
Conoscenze di base: infrastruttura
Earned apr 7, 2019 EDT
Google Cloud Essentials
Earned mar 3, 2019 EST
This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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In this course, we introduce you to Google Chat, Google’s chat software included with Google Workspace.
You will learn about messaging individuals and groups in Google Chat. You will also discover customization options, collaboration features and how Google Chat integrates with other Google Workspace products.
We will explore the use of spaces in Google Chat, showing you how to create, manage, search, and join them. Additionally, you will understand the distinctions between using a space and a group chat.
You also explore Google Chat apps and learn how to search for and use apps within Google Chat.
Aside from course videos, you will complete hands-on activities to practice what you’ve learned. Consider inviting a colleague or two to interact with you in Google Chat as you complete the activities.
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Specifically designed for healthcare professionals, this course demystifies generative AI, the latest breakthrough in artificial intelligence, and the large language models (LLMs) that drive it. Discover real-world applications of generative AI in healthcare settings and master the art of crafting effective prompts tailored to your goals.
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Questo corso ti insegna come creare un modello per le didascalie delle immagini utilizzando il deep learning. Scoprirai i diversi componenti di un modello per le didascalie delle immagini, come l'encoder e il decoder, e imparerai ad addestrare e valutare il tuo modello. Alla fine di questo corso, sarai in grado di creare modelli personali per le didascalie delle immagini e utilizzarli per generare didascalie per le immagini.
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Questo corso ti introduce all'architettura Transformer e al modello BERT (Bidirectional Encoder Representations from Transformers). Scopri i componenti principali dell'architettura Transformer, come il meccanismo di auto-attenzione, e come viene utilizzata per creare il modello BERT. Imparerai anche le diverse attività per le quali può essere utilizzato il modello BERT, come la classificazione del testo, la risposta alle domande e l'inferenza del linguaggio naturale. Si stima che il completamento di questo corso richieda circa 45 minuti.
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Questo corso ti offre un riepilogo dell'architettura encoder-decoder, che è un'architettura di machine learning potente e diffusa per attività da sequenza a sequenza come traduzione automatica, riassunto del testo e risposta alle domande. Apprenderai i componenti principali dell'architettura encoder-decoder e come addestrare e fornire questi modelli. Nella procedura dettagliata del lab corrispondente, implementerai in TensorFlow dall'inizio un semplice codice dell'architettura encoder-decoder per la generazione di poesie da zero.
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Questo corso ti introdurrà al meccanismo di attenzione, una potente tecnica che consente alle reti neurali di concentrarsi su parti specifiche di una sequenza di input. Imparerai come funziona l'attenzione e come può essere utilizzata per migliorare le prestazioni di molte attività di machine learning, come la traduzione automatica, il compendio di testi e la risposta alle domande.
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Questo corso introduce i modelli di diffusione, una famiglia di modelli di machine learning che recentemente si sono dimostrati promettenti nello spazio di generazione delle immagini. I modelli di diffusione traggono ispirazione dalla fisica, in particolare dalla termodinamica. Negli ultimi anni, i modelli di diffusione sono diventati popolari sia nella ricerca che nella produzione. I modelli di diffusione sono alla base di molti modelli e strumenti di generazione di immagini all'avanguardia su Google Cloud. Questo corso ti introduce alla teoria alla base dei modelli di diffusione e a come addestrarli ed eseguirne il deployment su Vertex AI.
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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.
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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.
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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.
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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 Dataproc e richiamo delle API ML tra cui l'API Cloud Natural Language, l'API Google Cloud Speech-to-Text e l'API Video Intelligence.
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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.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.
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This course equips full-stack mobile and web developers with the skills to integrate generative AI features into their applications using LangChain. You'll learn how to leverage LangChain’s capabilities for backend flows and seamless model execution, all within the familiar environment of Python. The course guides you through the entire process, from prototyping to production, ensuring a smooth journey in building next-generation AI-powered applications.
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Learn how Gemini can revolutionize your ability to develop applications! This course helps developers go beyond the basics and learn how to integrate Gemini into their workflows.
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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini.
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This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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This course explores Google Cloud technologies to create and generate embeddings. Embeddings are numerical representations of text, images, video and audio, and play a pivotal role in many tasks that involve the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions. Specifically, you’ll use embeddings for tasks like classification, outlier detection, clustering and semantic search.
You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) systems and question-answering solutions, on your own proprietary data using Google Cloud’s Vertex AI.
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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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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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Complete the intermediate Explore Generative AI with the Gemini API in Vertex AI skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects.
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Learn about new generative AI features in App Development, including Duet AI for VS Code, Cloud Workstations and Colab Enterprise, as well as application prototyping using natural language prompts in AppSheet.
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Earn a skill badge by completing the App Building with AppSheet course, where you learn how to build, configure, and publish apps using AppSheet.
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This course introduces you to the fundamentals of no-code application development and the capabilities offered by Google Cloud's AppSheet. AppSheet helps in digitizing and automating manual or paper-based business processes to turn them into mobile and web apps.
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Explore the fundamentals of Flutter application development in this hands-on quest! Within this quest, you will build a "Hello World" Flutter application, design a frontend for a shopping application, and learn how to connect your Flutter applications to backend services. Each lab in this quest utilizes a pre-provisioned development environment allowing minimal setup to get into the application code!
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In this course you will learn the fundamentals of no-code app development and recognize use cases for no-code apps. The course provides an overview of the AppSheet no-code app development platform and its capabilities. You learn how to create an app with data from spreadsheets, create the app’s user experience using AppSheet views and publish the app to end users.
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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.
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(This course was previously named Multimodal Prompt Engineering with Gemini and PaLM) This course teaches how to use Vertex AI Studio, a Google Cloud console tool for rapidly prototyping and testing generative AI models. You learn to test sample prompts, design your own prompts, and customize foundation models to handle tasks that meet your application's needs. Whether you are looking for text, chat, code, image or speech generative experiences Vertex AI Studio offers you an interface to work with and APIs to integrate your production application.
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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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Questo corso illustra Generative AI Studio, un prodotto su Vertex AI che ti aiuta a prototipare e personalizzare i modelli di AI generativa in modo da poterne utilizzare le capacità nelle tue applicazioni. In questo corso imparerai cos'è Generative AI Studio, le sue funzionalità e opzioni e come utilizzarlo, esaminando le demo del prodotto. Alla fine, troverai un laboratorio pratico per mettere in pratica ciò che hai imparato e un quiz per testare le tue conoscenze.
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Dal momento che l'uso dell'intelligenza artificiale e del machine learning nelle aziende continua a crescere, cresce anche l'importanza di realizzarli in modo responsabile. Molti sono scoraggiati dal fatto che parlare di IA responsabile può essere più facile che metterla in pratica. Se vuoi imparare come operativizzare l'IA responsabile nella tua organizzazione, questo corso fa per te.
In questo corso scoprirai come Google Cloud ci riesce attualmente, oltre alle best practice e alle lezioni apprese, per fungere da framework per costruire il tuo approccio all'IA responsabile.
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This content is deprecated. Please see the latest version of the course, here.
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'IA responsabile, perché è importante e in che modo Google implementa l'IA responsabile nei propri prodotti. Introduce anche i 7 principi dell'IA di Google.
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Questo è un corso di microlearning di livello introduttivo che esplora cosa sono i modelli linguistici di grandi dimensioni (LLM), i casi d'uso in cui possono essere utilizzati e come è possibile utilizzare l'ottimizzazione dei prompt per migliorare le prestazioni dei modelli LLM. Descrive inoltre gli strumenti Google per aiutarti a sviluppare le tue app Gen AI.
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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.
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(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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Completa il corso introduttivo con badge delle competenze Implementazione di Cloud Load Balancing per Compute Engine per dimostrare le tue competenze nei seguenti ambiti: creazione ed esecuzione del deployment di macchine virtuali in Compute Engine e configurazione di bilanciatori del carico di rete e delle applicazioni.
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Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura completa e flessibile e i servizi di piattaforma forniti da Google Cloud. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui interconnessione sicura delle reti, bilanciamento del carico, scalabilità automatica, automazione dell'infrastruttura e servizi gestiti.
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Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura e i servizi di piattaforma flessibili e completi di Google Cloud con particolare attenzione a Compute Engine. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui i componenti dell'infrastruttura come reti, macchine virtuali e servizi per applicazioni, ed eseguirne il deployment. Imparerai a utilizzare Google Cloud mediante la console e Cloud Shell. Scoprirai inoltre il ruolo del Cloud Architect, gli approcci alla progettazione dell'infrastruttura e la configurazione del networking virtuale con VPC (Virtual Private Cloud), progetti, reti, subnet, indirizzi IP, route e regole firewall.
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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task.
Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences.
“Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible.
Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Welcome to "CCAI Virtual Agent Development in Dialogflow ES for Software Developers", the third course in the "Customer Experiences with Contact Center AI" series.
In this course, learn to use additional features of Dialogflow ES for your virtual agent, create a Firestore instance to store customer data, and implement cloud functions that access the data. With the ability to read and write customer data, learner’s virtual agents are conversationally dynamic and able to defer contact center volume from human agents. You'll be introduced to methods for testing your virtual agent and logs which can be useful for understanding issues that arise. Lastly, learn about connectivity protocols, APIs, and platforms for integrating your virtual agent with services already established for your business.
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Il corso inizia con una discussione sui dati: come migliorare la qualità dei dati ed eseguire analisi esplorative dei dati. Descriveremo Vertex AI AutoML e come creare, addestrare ed eseguire il deployment di un modello di ML senza scrivere una sola riga di codice. Comprenderai i vantaggi di Big Query ML. Discuteremo quindi di come ottimizzare un modello di machine learning (ML) e di come la generalizzazione e il campionamento possano aiutare a valutare la qualità dei modelli di ML per l'addestramento personalizzato.
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Questo corso presenta i prodotti e i servizi per big data e di machine learning di Google Cloud che supportano il ciclo di vita dai dati all'IA. Esplora i processi, le sfide e i vantaggi della creazione di una pipeline di big data e di modelli di machine learning con Vertex AI su Google Cloud.
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Good news! There’s a new updated version of this learning path available for you!Open the new Professional Machine Learning Engineer Certification Learning Path to begin, once you’ve selected the new path all your current progress will be reflected in the new version.
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There's much excitement about cloud technology and digital transformation, but often many unanswered questions.
For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin?
If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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Flutter is Google's UI toolkit for building beautiful, natively compiled applications for mobile, web, and desktop from a single codebase. In this quest you will learn how to create a Flutter app using generated template code. Be sure to tag #flutterfestival in your social posts!
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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.
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Big data, machine learning e intelligenza artificiale sono i principali argomenti di computing trattati attualmente, ma questi campi sono piuttosto specializzati ed è complicato reperire materiale introduttivo. Fortunatamente, Google Cloud offre servizi facili da usare in queste aree e con questo corso di livello introduttivo, in modo da poter fare i primi passi con strumenti come BigQuery, API Cloud Speech e Video Intelligence.
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Completa il corso introduttivo con badge delle competenze Genera insight dai dati BigQuery per dimostrare le tue competenze nei seguenti ambiti: scrivere query SQL, eseguire query su tabelle pubbliche, caricare dati di esempio in BigQuery, risolvere i problemi di sintassi comuni con lo strumento di convalida query in BigQuery e creare report in Looker Studio collegando ai dati di BigQuery.
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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.
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Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will use Dialogflow ES to create virtual agents and test them using the Dialogflow ES simulator. This course also provides best practices on developing virtual agents. You will also be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations. Through a combination of presentations, demos, and hands-on labs, participants learn how to create virtual agents.
This is an intermediate course, intended for learners with the following types of roles:
Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows.
Citizen developers: Creates new business applications fo…
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Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.
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This course provides a deep dive into how to create a chatbot using Dialogflow, augment it with Cloud Natural Language API and operationalize it using Google Cloud tools.
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Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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In this quest, you will learn about Google Cloud’s IoT Core service and its integration with other services like GCS, Dataprep, Stackdriver and Firestore. The labs in this quest use simulator code to mimic IOT devices and the learning here should empower you to implement the same streaming pipeline with real world IoT devices.
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Learn the ins and outs of Google Cloud's operations suite, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. These labs will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.
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Non è un segreto che il machine learning sia uno dei campi in più rapida crescita nel settore tecnologico e la piattaforma Google Cloud è stata fondamentale per promuoverne lo sviluppo. Con le numerose API, Google Cloud dispone di uno strumento adeguato praticamente per qualsiasi job di machine learning. In questo corso introduttivo, farai pratica con il machine learning applicato all'elaborazione del linguaggio naturale partecipando ai lab che ti consentiranno di estrarre entità da un testo ed eseguire analisi del sentiment e della sintassi, nonché utilizzare l'API Speech-to-Text per la trascrizione.
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Welcome Gamers!
Are you a developer? Get hands-on practice with the state-of-the-art tools for developing applications in Google Cloud. The skills you learn align with the Professional Cloud Developer Certification exam. You will work with two different languages, Java and Python, and get 4 labs closer to earning the Cloud Development badge. Complete the game labs one by one to score points. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. Ready to play?
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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this course you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out!
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Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on Google Cloud.
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If you’re looking to take your Google Cloud application to the next level, look no further than Deployment Manager. By automating the creation of GCP resources and services, Deployment Manager lets you focus on developing rather than maintaining. In this advanced-level quest, you will get hands on practice with Deployment Manager by building custom templates, automating Python and Jinja application instances, and scaling custom networks.
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The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with Google Cloud.
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Questo corso introduttivo è unico tra le altre offerte di corsi. I lab sono stati selezionati per offrire ai professionisti IT la possibilità di fare pratica su argomenti e servizi che compaiono nell'esame di certificazione Google Cloud - Associate Cloud Engineer. Da IAM al networking, al deployment di Kubernetes Engine, questo corso si compone di lab specifici che metteranno alla prova le tue conoscenze su Google Cloud. Tieni presente che, sebbene la pratica con questi lab ti aiuterà a migliorare le tue competenze e capacità, ti consigliamo di rivedere anche la guida all'esame e altre risorse di preparazione disponibili.
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Kubernetes è il sistema di orchestrazione dei container più diffuso e Google Kubernetes Engine è stato progettato specificamente per supportare i deployment Kubernetes gestiti in Google Cloud. In questo corso di livello avanzato, potrai esercitarti nella configurazione di immagini e container Docker e nel deployment di applicazioni Kubernetes Engine complete. Grazie a questo corso, apprenderai le competenze pratiche necessarie per integrare l'orchestrazione dei container nel tuo workflow. Stai cercando un Challenge Lab pratico per dimostrare le tue abilità e convalidare le tue conoscenze? Dopo aver completato questo corso, termina il Challenge Lab aggiuntivo alla fine del corso Esegui il deployment di applicazioni Kubernetes su Google Cloud per ricevere un esclusivo badge digitale Google Cloud.
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Cloud Healthcare API bridges the gap between care systems and applications built on Google Cloud. By supporting standards-based data formats and protocols of existing healthcare technologies, Cloud Healthcare API connects your data to advanced Google Cloud capabilities, including streaming data processing with Cloud Dataflow, scalable analytics with BigQuery, and machine learning with Cloud Machine Learning Engine. In this Quest you will use the Cloud Healthcare API to ingest and process data in the industry standard FHIR, HL7v2 and DICOM formats, train a TensorFlow model for prediction with FHIR data, and also gain practice with de-identification of datasets.
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When it comes to hosting websites and web applications, you want a framework that’s robust, fast, and secure. By choosing the Google Cloud Platform, you will have all of those needs covered. In this fundamental-level quest, you will get hands-on practice with GCPs key infrastructure and computing services for the web. From deploying your first web app, to integrating Cloud SQL with Ruby on Rails, to mapping the NYC subway system on App Engine, you will learn all the skills needed to harness GCPs web hosting power.
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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
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We hope you enjoyed the App Dev Challenge. Now it is Game Time! You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.
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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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This course demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.
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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.
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Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.
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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.
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Se sei uno sviluppatore cloud principiante che vuole fare ancora pratica Google Cloud Essentials, questo corso fa al caso tuo. Acquisirai esperienza pratica attraverso lab specifici su Cloud Storage e altri servizi per applicazioni chiave come Monitoring e Cloud Functions. Svilupperai competenze preziose applicabili a qualsiasi iniziativa Google Cloud.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
Machine Learning Operations (MLOps) for Generative AI
Earned gen 19, 2025 EST
Google Chat
Earned gen 17, 2025 EST
Generative AI for Healthcare
Earned gen 10, 2025 EST
Create Image Captioning Models - Italiano
Earned gen 5, 2025 EST
Transformer Models and BERT Model - Italiano
Earned gen 4, 2025 EST
Encoder-Decoder Architecture - Italiano
Earned gen 4, 2025 EST
Attention Mechanism - Italiano
Earned dic 28, 2024 EST
Introduction to Image Generation - Italiano
Earned dic 27, 2024 EST
Prompt Design in Vertex AI
Earned dic 25, 2024 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned dic 15, 2024 EST
Create ML Models with BigQuery ML
Earned dic 11, 2024 EST
Prepara i dati per le API ML su Google Cloud
Earned dic 7, 2024 EST
Introduzione all'AI e al machine learning su Google Cloud
Earned nov 30, 2024 EST
Build a Certification Study Guide: PMLE
Earned nov 11, 2024 EST
Orchestrating Gen AI Applications with LangChain
Earned ott 30, 2024 EDT
Improving developer velocity with Gemini Code Assist
Earned ott 20, 2024 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned ott 17, 2024 EDT
Working with Notebooks in Vertex AI
Earned ott 17, 2024 EDT
Custom Search with Embeddings in Vertex AI
Earned ott 16, 2024 EDT
Generative AI for Business Leaders
Earned ott 16, 2024 EDT
Vector Search and Embeddings
Earned set 26, 2024 EDT
Explore Generative AI with the Gemini API in Vertex AI
Earned set 22, 2024 EDT
New Generative AI features in App Development
Earned feb 18, 2024 EST
App Building with AppSheet
Earned feb 4, 2024 EST
Building No-Code AppSheet Apps
Earned gen 26, 2024 EST
Flutter Development
Earned gen 25, 2024 EST
Building No-Code Apps with AppSheet: Foundations
Earned gen 18, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned gen 6, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned gen 3, 2024 EST
Text Prompt Engineering Techniques
Earned dic 25, 2023 EST
Introduction to Generative AI Studio - Italiano
Earned dic 22, 2023 EST
Responsible AI: Applying AI Principles with Google Cloud - Italiano
Earned dic 20, 2023 EST
Generative AI Explorer : Vertex AI
Earned nov 30, 2023 EST
Generative AI Fundamentals
Earned nov 20, 2023 EST
Introduction to Responsible AI - Italiano
Earned nov 20, 2023 EST
Introduction to Large Language Models - Italiano
Earned nov 20, 2023 EST
Introduction to Generative AI - Italiano
Earned nov 8, 2023 EST
Search with AI Applications
Earned nov 7, 2023 EST
Implementazione di Cloud Load Balancing per Compute Engine
Earned set 15, 2023 EDT
Infrastruttura Google Cloud elastica: scalabilità e automazione
Earned set 3, 2023 EDT
Infrastruttura Google Cloud di base: fondamenti
Earned giu 20, 2023 EDT
Scaling with Google Cloud Operations
Earned ott 26, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned ott 21, 2022 EDT
Exploring Data Transformation with Google Cloud
Earned ott 15, 2022 EDT
Virtual Agent Development in Dialogflow ES for Software Devs
Earned set 25, 2022 EDT
Launching into Machine Learning - Italiano
Earned set 15, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals - Italiano
Earned ago 22, 2022 EDT
Certification Learning Path: Professional Machine Learning Engineer
Earned ago 21, 2022 EDT
Digital Transformation with Google Cloud
Earned ago 11, 2022 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned lug 27, 2022 EDT
Flutter Essentials
Earned lug 3, 2022 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned giu 29, 2022 EDT
Baseline: dati, ML, AI
Earned giu 19, 2022 EDT
Genera insight dai dati BigQuery
Earned giu 18, 2022 EDT
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI
Earned giu 9, 2022 EDT
Virtual Agent Development in Dialogflow ES for Citizen Devs
Earned mag 20, 2022 EDT
Contact Center AI: Conversational Design Fundamentals
Earned mag 6, 2022 EDT
[DEPRECATED] - Building Conversational Experiences with Dialogflow
Earned apr 3, 2022 EDT
Scientific Data Processing
Earned mag 14, 2020 EDT
DEPRECATED IoT in the Google Cloud
Earned apr 5, 2020 EDT
DEPRECATED Google Cloud's Operations Suite
Earned apr 3, 2020 EDT
Introduzione al ML: elaborazione del linguaggio
Earned mar 28, 2020 EDT
Cloud Hero Speedrun: Leap Day
Earned feb 29, 2020 EST
DevOps Essentials
Earned gen 19, 2020 EST
Advanced ML: ML Infrastructure
Earned gen 19, 2020 EST
Deployment Manager
Earned gen 12, 2020 EST
[DEPRECATED] Deploying Applications
Earned gen 8, 2020 EST
Progettazione cloud
Earned gen 5, 2020 EST
Kubernetes in Google Cloud
Earned gen 5, 2020 EST
Cloud Healthcare API
Earned dic 25, 2019 EST
DEPRECATED Websites and Web Applications
Earned dic 20, 2019 EST
Baseline: Deploy & Develop
Earned dic 4, 2019 EST
App Dev 30-Day Challenge
Earned nov 8, 2019 EST
Machine Learning APIs
Earned nov 4, 2019 EST
Intro to ML: Image Processing
Earned ott 31, 2019 EDT
Cloud Development
Earned ott 30, 2019 EDT
DEPRECATED Application Development - Python
Earned ott 30, 2019 EDT
DEPRECATED Cloud Architecture
Earned ott 27, 2019 EDT
Workspace: Add-ons
Earned ott 25, 2019 EDT
Security & Identity Fundamentals
Earned ott 5, 2019 EDT
DEPRECATED Exploring APIs
Earned ott 5, 2019 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned mag 27, 2019 EDT
Conoscenze di base: infrastruttura
Earned apr 7, 2019 EDT
Google Cloud Essentials
Earned mar 3, 2019 EST