Understanding LookML in Looker
Earned apr 8, 2022 EDT
Prepare Data for Looker Dashboards and Reports
Earned apr 7, 2022 EDT
Monitor and Log with Google Cloud Observability
Earned apr 6, 2022 EDT
Questo corso adotta un approccio pratico reale al flusso di lavoro ML attraverso un case study. Un team ML è chiamato a rispondere a numerosi requisiti aziendali e ad affrontare vari casi d'uso ML. Deve comprendere gli strumenti necessari per la gestione e la governance dei dati e considerare l'approccio migliore per la pre-elaborazione dei dati.
Al team vengono presentate tre opzioni per creare modelli ML per due casi d'uso. Il corso spiega perché il team utilizzerà AutoML, BigQuery ML o l'addestramento personalizzato per raggiungere i propri obiettivi.
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In this course, you will learn about the various services Google Cloud offers for modernizing retail applications and infrastructure. Through a series of lecture content and hands-on labs, you will gain practical experience deploying cutting-edge retail and ecommerce solutions on Google Cloud.
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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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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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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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Questo corso introduce argomenti importanti relativi alla privacy e alla sicurezza dell'AI. Esplora metodi e strumenti pratici per implementare le pratiche consigliate per la privacy e la sicurezza dell'AI utilizzando gli strumenti open source e i prodotti Google Cloud.
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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.
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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.
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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.
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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps.
We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views.
After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.
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Complete the introductory Get Started with Sensitive Data Protection skill badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.
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Complete the intermediate Secure Software Delivery skill badge to demonstrate your proficiency in proactively integrating security into the software development lifecycle (SDLC) with DevSecOps principles. You'll learn how to utilize Google Kubernetes Engine (GKE) and Cloud Run for secure container image deployment, implement automated vulnerability scanning to proactively identify risks, and streamline application development with Artifact Registry while maintaining a focus on security. Additionally, you'll gain skills in integrating Cloud Build for robust development processes and implementing Admission Control Policies for fine-grained control over your environment.
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Complete the introductory Secure BigLake Data skill badge course to demonstrate skills with IAM, BigQuery, BigLake, and Data Catalog within Dataplex to create and secure BigLake tables.
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Earn a skill badge by completing the The Basics of Google Cloud Compute quest, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge 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. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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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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Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run.
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Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.
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Earn the Introductory skill badge by completing the Cloud Speech API: 3 Ways course, where you learn how to use speech related API tools to synthesise and transcribe speech.
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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Vertex AI platform.
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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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In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.
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Il corso Google Cloud Computing Foundations fornirà a chi ha poca o nessuna esperienza
di cloud computing una panoramica dettagliata dei concetti relativi alle nozioni di base
del cloud, ai big data e al machine learning, oltre che a dove e come Google Cloud si inserisce.
Alla fine del corso, i partecipanti saranno in grado di descrivere i concetti relativi al cloud computing,
ai big data e al machine learning e dimostrare delle competenze pratiche.
Questo corso fa parte della serie di corsi Google Cloud Computing Foundations.
I corsi dovrebbero essere completati nel seguente ordine:
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales
Questo terzo corso illustra come creare reti protette e stru…
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Il corso Google Cloud Computing Foundations fornirà a chi ha poca o nessuna esperienza
di cloud computing una panoramica dettagliata dei concetti relativi alle nozioni di base
del cloud, ai big data e al machine learning, oltre che a dove e come Google Cloud si inserisce.
Alla fine del corso, i partecipanti saranno in grado di descrivere i concetti relativi al cloud computing,
ai big data e al machine learning e dimostrare delle competenze pratiche.
Questo corso fa parte della serie di corsi Google Cloud Computing Foundations.
I corsi dovrebbero essere completati nel seguente ordine:
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales
Questo secondo corso esamina l'implementazione di modelli …
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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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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
Duet AI was renamed to Gemini, our next-generation model.
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Learn to secure your deployments on Google Cloud, including: how to use Cloud Armor bot management to mitigate bot risk and control access from automated clients; use Cloud Armor denylists to restrict or allow access to your HTTP(S) load balancer at the edge of the Google Cloud; apply Cloud Armor security policies to restrict access to cache objects on Cloud CDN and Google Cloud Storage; and mitigate common vulnerabilities using Cloud Armor WAF rules.
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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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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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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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Completa il corso intermedio con badge delle competenze Crea l'infrastruttura con Terraform su Google Cloud per dimostrare le tue competenze nei seguenti ambiti: principi di Infrastructure as Code (IaC) utilizzando Terraform, provisioning e gestione di risorse Google Cloud con configurazioni Terraform, gestione efficace dello stato (locale e remoto) e modularizzazione del codice Terraform per la riusabilità e l'organizzazione.
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Complete the intermediate Manage Kubernetes in Google Cloud skill badge to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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This challenge lab tests your skills and knowledge from the labs in the Monitor and Manage Google Cloud Resources quest. You should be familiar with the content of labs before attempting this lab.
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Complete the introductory Create and Manage AlloyDB Instances skill badge to demonstrate skills in the following: performing core AlloyDB operations and tasks, migrating to AlloyDB from PostgreSQL, administering an AlloyDB database, and accelerating analytical queries using the AlloyDB Columnar Engine.
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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.
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Earn a skill badge by completing the Detect Manufacturing Defects using Visual Inspection AI course, where you learn how to use Visual Inspection AI to deploy a solution artifact and test that it can successfully identify defects in a manufacturing process.
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Complete the introductory Build LookML Objects in Looker skill badge course to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.
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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.
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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.
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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.
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Il corso Viaggio nell'AI generativa - Vertex AI è una raccolta di lab su come utilizzare l'AI generativa su Google Cloud. Nei lab imparerai a utilizzare i modelli nella famiglia di API Vertex AI PaLM, tra cui text-bison, chat-bison, e textembedding-gecko. Acquisirai inoltre competenze su progettazione di prompt, best practice e modalità di utilizzo per l'ideazione, oltre che per la classificazione, l'estrazione e il riassunto di testi e altro ancora. Imparerai anche come ottimizzare un foundation model utilizzando l'addestramento personalizzato di Vertex AI ed eseguendone il deployment in un endpoint Vertex AI.
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Earn the intermediate skill badge by completing the Perform Predictive Data Analysis in BigQuery course, where you will gain practical experience on the fundamentals of sports data science using BigQuery, including how to create a soccer dataset in BigQuery by importing CSV and JSON files; harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data, and evaluate the impressiveness of World Cup goals.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
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In this course you will learn how to use several BigQuery ML features to improve retail use cases. Predict the demand for bike rentals in NYC with demand forecasting, and see how to use BigQuery ML for a classification task that predicts the likelihood of a website visitor making a purchase.
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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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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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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model.
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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, 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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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
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Earn a skill badge by completing the Automate Interactions with Contact Center AI quest, where you will learn about the features of Contact Center AI, including how to Build a virtual agent, Design conversation flows for your virtual agent; Add a phone gateway to your virtual agent; Use Dialogflow for troubleshooting; Review logs and debug your virtual agent. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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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.
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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. Un badge delle competenze è un badge digitale esclusivo rilasciato da Google Cloud come riconoscimento della tua competenza nell'uso di prodotti e servizi Google Cloud dopo aver messo alla prova la tua capacità di applicare le tue conoscenze in un ambiente interattivo pratico. Completa questo corso e il Challenge Lab conclusivo per ricevere un badge delle competenze da condividere con la tua rete.
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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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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. Un badge delle competenze è un badge digitale esclusivo rilasciato da Google Cloud come riconoscimento della tua competenza nell'uso di prodotti e servizi Google Cloud dopo aver messo alla prova la tua capacità di applicare le tue conoscenze in un ambiente interattivo pratico. Completa questo corso con badge delle competenze e il Challenge Lab finale di valutazione per ricevere un badge delle competenze da condividere con la tua rete.
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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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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.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge course, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn the intermediate skill badge by completing the Perform Predictive Data Analysis in BigQuery course, where you will gain practical experience on the fundamentals of sports data science using BigQuery, including how to create a soccer dataset in BigQuery by importing CSV and JSON files; harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data, and evaluate the impressiveness of World Cup goals.
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In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.
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In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.
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Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.
Machine learning in azienda
Earned mar 24, 2025 EDT
Modernizing Retail and Ecommerce Solutions with Google Cloud
Earned mar 24, 2025 EDT
Advanced ML: ML Infrastructure
Earned mar 24, 2025 EDT
Workspace: Add-ons
Earned mar 16, 2025 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned mar 16, 2025 EDT
AI responsabile per sviluppatori: privacy e sicurezza
Earned mar 16, 2025 EDT
Work with Gemini Models in BigQuery
Earned mar 16, 2025 EDT
Google Developer Essentials
Earned mar 15, 2025 EDT
Boost Productivity with Gemini in BigQuery
Earned mar 15, 2025 EDT
Achieving Advanced Insights with BigQuery
Earned mar 15, 2025 EDT
Get Started with Sensitive Data Protection
Earned mar 14, 2025 EDT
Secure Software Delivery
Earned mar 14, 2025 EDT
Secure BigLake Data
Earned mar 13, 2025 EDT
The Basics of Google Cloud Compute
Earned mar 13, 2025 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned mar 13, 2025 EDT
Explore Generative AI with the Gemini API in Vertex AI
Earned mar 13, 2025 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned mar 13, 2025 EDT
Build Custom Processors with Document AI
Earned mar 12, 2025 EDT
Cloud Speech API: 3 Ways
Earned mar 11, 2025 EDT
Build Real World AI Applications with Gemini and Imagen
Earned feb 27, 2025 EST
Prompt Design in Vertex AI
Earned feb 27, 2025 EST
Mitigating Security Vulnerabilities on Google Cloud
Earned giu 1, 2024 EDT
[DEPRECATED] - Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Earned giu 1, 2024 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Earned giu 1, 2024 EDT
Introduzione all'AI e al machine learning su Google Cloud
Earned mag 31, 2024 EDT
Gemini for Data Scientists and Analysts
Earned mag 31, 2024 EDT
Securing your Network with Cloud Armor
Earned mag 29, 2024 EDT
Conoscenze di base: infrastruttura
Earned mag 28, 2024 EDT
Intro to ML: Image Processing
Earned mag 28, 2024 EDT
Introduzione al ML: elaborazione del linguaggio
Earned mag 28, 2024 EDT
Crea l'infrastruttura con Terraform su Google Cloud
Earned mag 26, 2024 EDT
Manage Kubernetes in Google Cloud
Earned mag 26, 2024 EDT
Monitor and Manage Google Cloud Resources
Earned mag 26, 2024 EDT
Create and Manage AlloyDB Instances
Earned mag 26, 2024 EDT
Analyze Speech and Language with Google APIs
Earned mag 25, 2024 EDT
Detect Manufacturing Defects Using Visual Inspection AI
Earned mag 25, 2024 EDT
Build LookML Objects in Looker
Earned mag 24, 2024 EDT
Classify Images with TensorFlow on Google Cloud
Earned mag 24, 2024 EDT
Analyze Sentiment with Natural Language API
Earned mag 24, 2024 EDT
Analyze Images with the Cloud Vision API
Earned mag 24, 2024 EDT
Viaggio nell'AI generativa - Vertex AI
Earned mag 24, 2024 EDT
Perform Predictive Data Analysis in BigQuery
Earned mag 24, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned ott 12, 2022 EDT
DEPRECATED Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications
Earned ott 11, 2022 EDT
Baseline: dati, ML, AI
Earned ott 11, 2022 EDT
Machine Learning APIs
Earned ott 11, 2022 EDT
BigQuery for Machine Learning
Earned ott 11, 2022 EDT
DEPRECATED BigQuery for Data Warehousing
Earned ott 11, 2022 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned ott 10, 2022 EDT
Automate Interactions with Contact Center AI
Earned ott 10, 2022 EDT
Use Machine Learning APIs on Google Cloud
Earned ott 9, 2022 EDT
Genera insight dai dati BigQuery
Earned ott 9, 2022 EDT
Build and Deploy Machine Learning Solutions on Vertex AI
Earned ott 8, 2022 EDT
Prepara i dati per le API ML su Google Cloud
Earned ott 8, 2022 EDT
Create ML Models with BigQuery ML
Earned ott 8, 2022 EDT
Automate Data Capture at Scale with Document AI
Earned ott 7, 2022 EDT
Build a Data Warehouse with BigQuery
Earned ott 7, 2022 EDT
Perform Predictive Data Analysis in BigQuery
Earned ott 6, 2022 EDT
Applying Advanced LookML Concepts in Looker
Earned apr 8, 2022 EDT
Understanding LookML in Looker
Earned apr 8, 2022 EDT
Prepare Data for Looker Dashboards and Reports
Earned apr 7, 2022 EDT
Monitor and Log with Google Cloud Observability
Earned apr 6, 2022 EDT