Transformer Models and BERT Model - Italiano
Earned giu 11, 2023 EDT
Encoder-Decoder Architecture - Italiano
Earned giu 11, 2023 EDT
Attention Mechanism - Italiano
Earned giu 11, 2023 EDT
Introduction to Image Generation - Italiano
Earned giu 11, 2023 EDT
Generative AI Fundamentals - Italiano
Earned giu 9, 2023 EDT
Introduction to Responsible AI - Italiano
Earned giu 9, 2023 EDT
Introduction to Large Language Models - Italiano
Earned giu 9, 2023 EDT
Introduction to Generative AI - Italiano
Earned giu 9, 2023 EDT
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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Model tuning is an effective way to customize large models to your tasks. It's a key step to improve the model's quality and efficiency. Model tuning provides benefits such as higher quality results for your specific tasks and increased model robustness. You learn some of the tuning options available in Vertex AI and when to use them.
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Model Garden is a model library that helps you discover, test, and deploy models from Google and Google partners. Learn how to explore the available models and select the right ones for your use case. And how to deploy and interact with Model Garden models through the Google Cloud console and APIs.
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This video covers how to create a 'project notebook' in NotebookLM by adding all relevant sources to build a central, searchable knowledge hub for your team.
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This video covers how to use NotebookLM for common marketing tasks like
analyzing customer feedback, conducting market research, and generating
content ideas.
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This video covers how to use the Video Overviews feature in NotebookLM to automatically generate a short explainer video based on your source documents.
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This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.
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This video covers how to use the Mind Maps feature in NotebookLM to automatically create a visual representation of your sources, helping you understand connections and key concepts.
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This video covers how to use NotebookLM as a personal research
assistant by adding sources, asking questions, and generating new content
formats based on your documents.
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This video covers how to use Gemini in Gmail to draft new emails,
refine their tone, respond with context from Drive files, and use smart
reply suggestions.
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This video covers how to use the 'Help me create' feature in Google Docs to generate a complete, formatted document by referencing content from other files in your Drive.
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This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.
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This video covers how to use Gemini in Gmail to summarize emails, find information, and draft replies, helping you manage your inbox more efficiently.
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This video covers how to use Gemini in Slides to automatically generate
meeting recaps and draft follow-up emails, which can streamline your
post-meeting workflow and save you time.
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This video covers how you can leverage Gemini's advanced AI capabilities within Google Sheets to effortlessly pull data and generate insights in minutes, all without the need for any technical or coding background.
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This video will cover how to leverage Gemini Gems to create authentic
social media posts in your leader's unique voice. Learn to overcome the
challenge of scaling executive social presence by training a Gem with
writing samples and clear instructions. Discover how to generate engaging
posts quickly, saving time while amplifying thought leadership and
ensuring authenticity.
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This video covers how you can create your own Brevity Gem to summarize and transform messy notes or long documents into clear, concise, executive-ready summaries.
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This video covers how to use Gemini and Apps Script to automate manual tasks across Google Workspace. You'll learn to prompt Gemini to generate Apps Script code that automatically drafts email reminders in Google Sheets for tasks not marked 'Complete.' Automate your workflow with little to no technical expertise, freeing up time for more important work and eliminating manual follow-ups.
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This video covers how you can leverage Notebook LM to "eat the frog" on your to-do list by automating complex tasks like summarizing legislation and mapping services, saving you hours of work.
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This video covers how to eliminate tedious manual data entry using Gemini. Learn how to take a picture or screenshot of data (from PDFs, paper, or images) and prompt Gemini to instantly convert it into a structured Google Sheet. Discover this simple hack to save countless hours transcribing data, turning Gemini into your personal data entry assistant. Just snap, prompt, and export!
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AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.
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This video will cover how to use NotebookLM to gather and analyze
publicly available information, combine it with internal documents, and
extract key competitive insights.
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This video covers how to personalize your Gemini results in Google
Workspace. Learn to incorporate documents and research papers directly
into your prompts using the "@" symbol to get more targeted and relevant
AI output tailored to your needs.
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This video covers how you can use Gemini to summarize long documents in Google Workspace, so you can quickly get the information you need and save time. You'll learn how to use Gemini to summarize entire documents or just selected text, as well as how to use Gemini in Drive to summarize across multiple files.
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This video covers prompt engineering fundamentals for effective AI communication. Learn a simple framework (Persona, Task, Context, Format) to craft clear prompts, getting better, faster results from Gemini in Google Workspace. Discover how to use natural language, be specific, and iterate for optimal AI assistance.
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This video will cover how you can leverage Gemini's advanced AI capabilities in Google Docs to brainstorm ideas, draft various marketing content, and collaborate with your team.
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This video covers how NotebookLM can revolutionize customer insight gathering from call or chat transcripts. You'll learn to upload PDF transcripts of hundreds of conversations (even multilingual ones!) and quickly extract key themes, trending topics, and actionable insights without listening for hours. Discover how to save findings, share notebooks, and even generate interactive podcast summaries of your data.
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This video covers how to create your own Gemini Gems, advanced AI capabilities that can automate repetitive tasks and supercharge your productivity.
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Complete the Build search and recommendations AI Applications skill badge to demonstrate your proficiency in deploying search and recommendation applications through AI Applications. Additionally, emphasis is placed on constructing a tailored Q&A system utilizing data stores.
Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content.
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 assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
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This lab tests your ability to develop a real-world Generative AI Q&A solution using a RAG framework. You will use Firestore as a vector database and deploy a Flask app as a user interface to query a food safety knowledge base.
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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts.
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 assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
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In this skill bagde, you will demonstrate your ability to use and compare models available in the Vertex AI Model Garden. You'll deploy a model to a Vertex AI Endpoint, query other models via their API, and use Vertex AI's Gen AI evaluation service to measure the performance of multiple models.
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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email.
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 assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!"
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In this course, you learn how to develop an app using Flutter, Google's portable UI toolkit, and integrate the app with Gemini, Google's family of generative AI models. You also use Vertex AI Agent Builder, Google's platform for building and managing AI Agents and applications.
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Enhance the navigation experience of your website by using generative AI to provide a better search experience for your users. In this course, you learn how to use Vertex AI Search to provide your website users a generative search experience enabling them to discover content offered by the website. As a website editor, you also learn how to use generative AI to quickly and efficiently translate and improve the content using suggestions.
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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.
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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production.
Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.
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An AI-driven Contact Center as a Service (CCaaS) solution that is built natively on Google Cloud. The Implementation course provides Partners with essential training about the delivery of key features and functionality. The course explores how to leverage your key understanding of the product into successful customer implementation engagements with tips, best practices, guides, and more.
Note: This product was previously called Contact Center AI (CCAI) Platform you may see references to that name still in the course, however the course is technically correct.
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Configure and Maintain CCaaS as an Admin is a course that provides end users with essential learning about the core features, functionality, reporting, and configuration information most relevant to the role. This course is most appropriate for those who perform administrative functions to support the operation of the contact center as well as analyze, troubleshoot, and configure the platform to best meet the demands of customers. While this program will review some monitoring and reporting aspects, those topics are explored in depth in the course titled, “Managing Functions and Reporting with CCaaS".
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Manage Functions and Reporting with CCaaS provides end-users with essential training about the core features, functionality, monitoring, reporting, and configuration information that is most relevant to the role. This course is most appropriate for those at the managerial level of the contact center who are tasked with monitoring the effectiveness, efficiency, and KPI attainment for all consumer interactions. While this program will review some aspects of settings and configuration options, the major focus is on reporting functionality in CCaaS.
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This course teaches contact center agents about the core agent features and functionality in Contact Center as a Service (CCaaS). CCaaS is a unified contact center platform that accelerates an organization's ability to leverage and deploy contact centers without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.
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Welcome to Hybrid Cloud Infrastructure Foundations with Anthos!
This is the first course of the Architecting Hybrid Cloud Infrastructure with Anthos path. Anthos enables you to build and manage modern applications, and gives you the freedom to choose where to run them. Anthos gives you one consistent experience in both your on-premises and cloud environments.
During this course, you will be presented with modules that will take you through skills that you will use as an architect or administrator running Anthos environments. The modules in this course include videos, hands-on labs, and links to helpful documentation.
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In questo corso, "Architecting with Google Kubernetes Engine: Production", imparerai a conoscere la sicurezza di Kubernetes e Google Kubernetes Engine (GKE), logging e monitoraggio e a utilizzare i servizi di archiviazione e database gestiti di Google Cloud dall'interno di GKE.
Si tratta del corso finale della serie Architecting with Google Kubernetes Engine. Dopo il completamento di questo corso, iscriviti al corso Reliable Google Cloud Infrastructure: Design and Process o al corso Hybrid Cloud Infrastructure Foundations with Anthos.
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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.
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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.
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Gen AI: Navigate the Landscape s the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.
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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.
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In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Vertex AI Agent Engine to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Engine.
Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.
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The course explores advanced services such as machine learning, and operational topics such as application deployment, monitoring, and troubleshooting.
In addition, we’ll introduce GDC software upgrades, logging, billing, and cost monitoring.
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The course examines service resources or workload components that exist in projects. You’ll learn about Kubernetes in GDC, Artifact Registry, GDC Object Storage, Database Service, Networking, and Key Management and Security.
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This course provides an introduction to the GDC platform—which enables you to host, control, and manage infrastructure and services directly on your premises.
GDC air-gapped is one component of Google Distributed Cloud offering which aligns to Google’s digital sovereignty vision. It supports public-sector customers and commercial entities that have strict data residency, security or privacy requirements.
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This L300 course explores the intricacies of the hardware and networking infrastructure, examines the role of Kubernetes in container orchestration, and how to master the deployment process. The course emphasizes critical security aspects, guiding you through defense-in-depth design, zero-trust architecture, and essential operational security measures for protecting sensitive data. You'll also gain valuable insights into operational aspects, such as resource management, upgrades, and solutions tailored for GDC customers.
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This L200 course comprehensively explores GDC air-gapped's concepts, architecture, and operational aspects, equipping learners with the knowledge to deploy and manage this solution effectively. The course delves into topics such as the roles of vendors and partners, hardware and software components, zero trust security, multi-tenancy, support and operations, observability, Identity and Access Management, managed services, and the GDC Sandbox environment. Furthermore, the course provides insights into compliance and accreditation processes, ensuring learners understand the regulatory landscape and can navigate it successfully. By the end of this course, learners will have a solid understanding of GDC air-gapped and be prepared to leverage its capabilities for their organization's needs.
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In this course, you will learn about GDC air-gapped (previously known as GDC Hosted), an offering from Google Distributed Cloud. This course provides both a business and technical overview of GDC air-gapped, exploring its key features and target customers.
Participants will gain insights into GDC air-gapped's value proposition and learn how to effectively communicate its benefits to potential clients, enabling them to qualify for sales opportunities.
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Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals.
This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharing of VPC networks. Additionally, the course covers network logging and monitoring techniques.
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In this skill badge, you will demonstrate your ability to deploy Google Agentspace and set up data stores and actions. To learn these skills, we encourage you to take the course Accelerate Knowledge Exchange with Agentspace.
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This L300 course offers a comprehensive exploration of GDC connected, encompassing design, deployment, operations, and advanced networking. It explores the architecture, configuration, and management of GDC infrastructure, including server setup, control plane operations, and network connectivity. The course also covers operational aspects, like high availability, failover, and observability, along with advanced networking topics such as APIs, network functions, and plugins.
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This L200 course comprehensively explores GDC connected concepts, architecture, and operational aspects, equipping learners with the knowledge to deploy and manage this solution effectively. The course delves into topics such as its survivability features and best practices, security, networking, software stack, and hardware options. Furthermore, the course provides insights into its operating model. By the end of this course, learners will have a solid understanding of GDC connected and be prepared to leverage its capabilities for their organization's needs.
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In questo corso, "Architecting with Google Kubernetes Engine: Workloads", imparerai come eseguire le operazioni Kubernetes, creare e gestire i deployment, quali sono gli strumenti di networking di GKE e come fornire archiviazione permanente ai tuoi carichi di lavoro Kubernetes.
Questo è il secondo corso della serie Architecting with Google Kubernetes Engine. Dopo il completamento di questo corso, iscriviti al corso Reliable Google Cloud Infrastructure: Design and Process o al corso Hybrid Cloud Infrastructure Foundations with Anthos.
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In questo corso, "Progettazione dell'architettura con Google Kubernetes Engine: fondamenti", troverai un ripasso del layout e dei principi di Google Cloud, seguito da un'introduzione alla creazione e alla gestione dei container software, nonché all'architettura di Kubernetes.
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This course is for deployment personnel of Google Cloud and its partner organizations who are tasked with managing cultural change and skill gaps of customers adopting Google Workspace, engaging sponsors and enlisting the support of customer stakeholders, communicating the anticipated changes to the customer and their users. It will guide you through the Workspace change management methodology and all phases of the customer journey.
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This course on workspace transformation guides participants through modules designed to optimize and transform business environments using Google Workspace. It covers the Google Workspace Customer Success Methodology, provisioning processes, authentication and system access, mail routing, migration strategies, and coexistence planning to ensure a seamless transition and effective implementation.
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This course equips app developers with the skills to integrate generative AI features into their applications using Firebase Genkit. You learn how to leverage Firebase Genkit's capabilities for backend flows and seamless model execution, all using Node.js. The course guides you through the entire process, from prototyping to production, providing a pattern for building next-generation AI-powered applications.
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This course provides comprehensive skills on VM migration, from the initial assessment through the final implementation through presentations, demonstrations, and whiteboard session.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Snowflake to BigQuery. Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners' understanding of the topics. "This learning path aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Snowflake to BigQuery.
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In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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Migration from Oracle to Cloud Spanner using HarbourBridge. This course describes an example scenario that uses sample data during the migration. This process includes using HarbourBridge for Assessment, Schema Conversion, Schema Transformation, Data Migration, and supporting tools for data validation.
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In this course, you'll learn about Google Vids, an online video creation and editing app available to select Google Workspace users. Through lessons and demos, you'll learn how to build and tell compelling stories through video at work. You'll also discover how to seamlessly incorporate media, audio and video clips, customize styles, and easily share your creations.
Some Vids features use generative AI to help you work more efficiently. Remember, generative AI tools including Gemini, may suggest inaccurate or inappropriate information. Don’t rely on Gemini features as medical, legal, financial or other professional advice. It’s also important to remember that the Gemini feature suggestions don’t represent Google’s views, and should not be attributed to Google.
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Google Workspace with Gemini provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Drive using video lessons, hands-on activities and practical examples. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Drive to improve your workflows.
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In this course, you will learn about GDC connected (previously known as GDC Edge), an offering from Google Distributed Cloud. This course provides both a business and technical overview of GDC connected, exploring its key features and target customers.
Participants will gain insights into GDC connected's value proposition and learn how to effectively communicate its benefits to potential clients, enabling them to qualify for sales opportunities.
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This course focuses on how you can leverage the Google Cloud Analytics and AI/ML offerings to integrate and innovate with SAP
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This course is the third part of the SAP on Google Cloud Platform learning path. Following the SAP on Google Cloud Foundations eLearning and the SAP on Google Cloud Self-paced labs. Participants should have completed these two components before. This course consists of hands-on labs that provide a holistic experience of optimally configuring SAP on Google Cloud. Participants will learn to configure SAP on Google Cloud, and what best practices are, leaving the course with actionable experience to configure SAP on Google Cloud and run SAP workloads on Google Cloud for their customers.
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Perform a migration from Oracle to BigQuery using SQL Translation and DataFlow using Sample Data. Learners will complete a quiz that focuses on the process of transferring both schema and data from an Oracle enterprise data warehouse to BigQuery.
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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Oracle and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Oracle, you also learn about similarities and differences between Oracle and BigQuery to help you get started with data warehouses in BigQuery. After this course, you can continue your BigQuery journey by completing the skill badge quest titled Build and Optimize Data Warehouses with BigQuery.
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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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Unite Google’s expertise in search and AI with Gemini Enterprise, a powerful tool designed to help employees find specific information from document storage, email, chats, ticketing systems, and other data sources, all from a single search bar. The Gemini Enterprise assistant can also help brainstorm, research, outline documents, and take actions like inviting coworkers to a calendar event to accelerate knowledge work and collaboration of all kinds.
(Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)
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Imagen provides a suite of generative AI tools to help you accelerate your creative workflows. This course provides you with demonstrations of all the key features currently found in Imagen.
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Do you want to keep your users engaged by suggesting content they'll love?
This course equips you with the skills to build a cutting-edge recommendations app using your own data with no prior machine learning knowledge. You learn to leverage AI Applications to build recommendation applications so that audiences can discover more personalized content, like what to watch or read next, with Google-quality results customized using optimization objectives.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Oracle to Cloud SQL using the Ora2Pg.
An example scenario using sample data will be used to demonstrate the migration. Learners will complete an assessment quiz that focuses on the process of transferring schema, data and related processes to corresponding Google Cloud products.
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This course educates partners on key concepts around deploying Google Cloud VMware Engine (GCVE) and leveraging HCX to migrate VMs from on-premises VMware to GCVE.
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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Snowflake and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Snowflake, you also learn about similarities and differences between Snowflake and BigQuery to help you get started with data warehouses in BigQuery. After this course, you can continue your BigQuery journey by completing the skill badge quest titled Build and Optimize Data Warehouses with BigQuery.
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This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating workloads from Hadoop environments to corresponding Google Cloud services and hosted products. The following will addressed will be: The Hadoop ecosystem and products Hadoop architecture and post migration architectures to Google Cloud Assessment Data transfer options Workload migrations, namely: Spark to Dataproc Serverless, Apache Oozie to Composer (Airflow), and Hive to BigQuery Security and governance Logging and Monitoring
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Migration from AWS EC2 to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.
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Migration from on-premises VMware to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.
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Welcome to the course focusing on the Migration from Pivotal Cloud Foundry to Google Cloud. This program offers a practical demonstration that guides you through the step-by-step process of transitioning applications seamlessly between these two platforms.
Throughout this course, you'll engage in hands-on exercises and demos, providing a proof-of-concept journey.
This course provides insights into Pivotal Cloud Foundry and Tanzu Kubernetes Grid (TKG), and their roles in cloud infrastructure. It includes hands-on sessions for installing Tanzu CLI. You'll also learn to deploy management clusters efficiently, organize cloud resources, and create workload clusters.
Additionally, you will perform a workload migration from Tanzu Kubernetes Grid to Google Kubernetes Engine (GKE) and containerize an applications on Google Cloud.
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Migration from Azure to Google Cloud Compute Engine using Migrate to Virtual Machines (v5) using demo VM(s). It provides a proof-of-concept that walks you through the process of replicating a VM to doing test cutover and final cutover of the VM.
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Outline the key steps in publishing an API to deliver selective company information to applications created by external developers.
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L'elaborazione dei flussi di dati sta diventando sempre più diffusa poiché la modalità flusso consente alle aziende di ottenere parametri in tempo reale sulle operazioni aziendali. Questo corso tratta la creazione di pipeline di dati in modalità flusso su Google Cloud. Pub/Sub viene presentato come strumento per la gestione dei flussi di dati in entrata. Il corso spiega anche come applicare aggregazioni e trasformazioni ai flussi di dati utilizzando Dataflow e come archiviare i record elaborati in BigQuery o Bigtable per l'analisi. Gli studenti acquisiranno esperienza pratica nella creazione di componenti della pipeline di dati in modalità flusso su Google Cloud utilizzando QwikLabs.
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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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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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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 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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This skill badge course is designed to offer hands-on experience through labs, enabling participants to master Document AI for document processing and extraction tasks. By the end of the course, participants will be proficient in creating and testing Document AI processors, customizing document extraction using Document AI Workbench, and building custom processors to tackle real-world document processing challenges.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with building a Custom Doc Extractor using the Google Cloud AI solution. The following will be addressed:
Service: Document AI
Task: Extract fields
Processors: Custom Document Extractor and Document Splitter
Prediction: Using Endpoint to programmatically extract fields
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This course explores the quality assurance best practices and the tools available in Conversational Agents to ensure production grade quality during Conversational Agent development, as well as the key tenets for the creation of a robust end to end deployment lifecycle. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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This course explores the fundamentals of the feedback loop process for Conversational Agent development and introduces the native capabilities within Conversational Agents that support it. You will also learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents.
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In this course, you will learn the important role that different types of webhooks play in Conversational Agents development, and how to effectively integrate them into your routine configuration of a Conversational Agent. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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Discover flows in Conversational Agents and learn how to build deterministic chat and voice experiences with language models. Explore key concepts like drivers, intents, and entities, and how to use them to create conversational agents.
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This course explores the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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This course explores the best practices, methods and tools to programmatically lead CCAI virtual agent delivery. It includes a high level overview of the end to end journey for building and deploying a virtual agent, as well as the core tenets to create a strong delivery culture. Additionally, this course covers the best practices for workflow management, defect tracking, release management and post-release support to ensure optimal virtual agent performance.
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Welcome to "CCAI Operations and Implementation", the fourth course in the "Customer Experiences with Contact Center AI" series. In this course, learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale. In this course, you'll be introduced to Agent Assist and the technology it uses so you can delight your customers with the efficiencies and accuracy of services provided when customers require human agents, connectivity protocols, APIs, and platforms which you can use to create an integration between your virtual agent and the services already established for your business, Dialogflow's Environment Management tool for deployment of different versions of your virtual agent for various purposes, compliance measures and regulations you should be aware of when bringing your virtual agent to production, and you'll be given tips from virtua…
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Welcome to "Virtual Agent Development in Dialogflow CX 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). In this course, you'll be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations using Dialogflow CX.
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Welcome to "Virtual Agent Development in Dialogflow CX for Software Devs", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop more customized customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to more advanced and customized handling for virtual agent conversations that need to look up and convey dynamic data, and methods available to you for testing your virtual agent and logs which can be useful for understanding issues that arise.
This is an intermediate course, intended for learners with the following type of role:
Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API.
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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 educates partners on key concepts of Google’s Migrate to Containers. It will cover planning, workload fitness for conversion, deployment with a processing cluster, and the migration process.
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In this course, you will learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
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This course explores advanced technical considerations to optimize Webhook connectivity for comprehensive, end-to-end, Conversational Agent self-service experiences. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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This course will equip you with the tools to develop complex conversational experiences in Conversational Agents capable of identifying the user intent and routing it to the right self service flow.
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Explore the Generative AI features for Conversational Agents and how to incorporate them into stateful Flows.
Discover the possibilities with Generators, Generative Fallback, and Data Stores, as well as best practices and security settings for using these features.
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This course will equip you with the tools to develop complex conversational experiences in Conversational Agents capable of identifying the user intent and routing it to the right self service flow. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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Explore Playbooks and their implementation of the ReAct pattern for building Conversational Agents. You will learn how to construct a Playbook, set up goals and instructions to build a chatbot in natural language, and learn to test and deploy your solution.
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Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
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Learn which Mandiant products directly enhance or augment capabilities provided by Chronicle SIEM and SOAR and how those products integrate into our workflow.
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This course will provide you with an overview of SIEM technology to set the stage for the differentiation and expansion of capabilities that Chronicle SIEM provides.
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This course will familiarize you with the core functionality of Chronicle, including the user interface, connections, and settings.
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In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.
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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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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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Ottieni un badge delle competenze completando il corso Configura un ambiente di sviluppo di app su Google Cloud, in cui imparerai a creare e connettere un'infrastruttura cloud incentrata sull'archiviazione utilizzando le funzionalità di base delle seguenti tecnologie: Cloud Storage, Identity and Access Management, Cloud Functions e Pub/Sub.
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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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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 questi concetti 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 primo corso fornisce una panoramica del cloud computing, dei modi per utilizzare Google Cloud e
diverse opzio…
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This workload aims to upskill Google Cloud partners to deploy and manage Google Backup and Disaster Recovery (BDR).
The following will be addressed:
the core components and business value of Google BDR,
the prerequisites before installing Google BDR,
the initial deployment of Google BDR,
creating and configuring components of a Backup Plan,
the components of a Backup Plan,
discovering VMware and Compute Engine VMs,
and protecting, backing up, and restoring VMs.
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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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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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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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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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine.
This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.
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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.
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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 describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models.
The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data.
The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models.
Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.
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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.
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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.
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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.
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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 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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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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In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel.
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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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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities, learn to identify high-impact use cases, and develop the skills to demonstrate and integrate these technologies seamlessly into client solutions and operations.
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This course is for Partner sellers and technical pre-sales engineers to gain a comprehensive understanding of Google Cloud's cutting-edge Generative AI capabilities and learn to identify high-impact use cases.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC).
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps network engineers create, update, and maintain VPC networks. You learn how to prompt Gemini to provide specific guidance for your networking tasks, beyond what you would receive from a search engine. Using a hands-on lab, you experience how Gemini makes it easier for you to work with Google Cloud VPC networks.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture.
Duet AI was renamed to Gemini, our next-generation model.
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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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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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This skill badge course is designed to offer hands-on experience through labs, enabling participants to migrate applications to the cloud using a "Rehost" strategy. Participants will learn essential tasks involved in migrating both frontend (.Net application) and backend (MySQL database) components to existing virtual machines. Through guided and challenge labs, participants will validate successful migrations, reinforcing their understanding of cloud application modernization concepts.
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This learning path aims to upskill Google Cloud partners to perform the specific tasks associated with the priority workload. Learners will discover the specific tasks in rehosting applications from on-premises to Google Cloud. It also aims to re-platform applications to run in GKE. Learners will perform the tasks of Migrating MySQL, Angular, and .NET applications from their on-premises machines to Google Cloud VM instances. Sample code will be used during the migration. Learners will complete a challenge lab that focuses on the critical steps in a rehosting exercise - copying over code for the back-end, front-end, and middle-tier applications and validating that the applications have been migrated correctly. Learners will also complete a challenge lab that focuses on the critical steps in a re-platforming exercise - creating back-end, front-end, and middle-tier Docker images, deploying the same in the GKE cluster, and validating that the application has been deployed correctly.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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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.
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This skill badge course is designed to offer hands-on experience through labs, guiding participants in gaining practical expertise in modernizing Java applications on the Google Cloud.
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This course aims to upskill Google Cloud partners to perform specific tasks in rehosting applications from on-premise to Google Cloud. It also aims to re-platform applications to run in GKE. Learners will perform the tasks of Migrating MySQL, Angular, and Java applications from their on-premise machines to Google Cloud VM instances. Sample code will be used during the migration.
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This course explores the different products and capabilities of Customer Engagement Suite (CES) and Conversational agents. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.
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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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In this course you will learn how Conversational AI Agent Assist can help distill complex customer interactions into concise and clear summaries. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
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In this course you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the voice channel, as well as the options available for integration with other platforms in the Conversational AI ecosystem.
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Gemini per Google Workspace è un componente aggiuntivo che fornisce agli utenti accesso a funzionalità di AI generativa. Questo corso approfondisce le funzionalità di Gemini in Google Meet. Attraverso lezioni video e attività ed esempi pratici, acquisirai una comprensione completa delle funzionalità di Gemini in Google Meet. Imparerai a utilizzare Gemini per generare immagini di sfondo, migliorare la qualità video e tradurre i sottotitoli. Alla fine del corso avrai acquisito le conoscenze e le competenze necessarie per utilizzare con sicurezza Gemini in Google Meet per massimizzare l'efficacia delle tue videoconferenze.
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Gemini per Google Workspace è un componente aggiuntivo che fornisce ai clienti funzionalità di AI generativa in Google Workspace. In questo mini corso imparerai le funzionalità principali di Gemini e come possono essere utilizzate per migliorare la produttività e l'efficienza in Presentazioni Google.
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Gemini per Google Workspace è un componente aggiuntivo che fornisce ai clienti funzionalità di AI generativa in Google Workspace. In questo mini corso imparerai le funzionalità principali di Gemini e come possono essere utilizzate per migliorare la produttività e l'efficienza in Fogli Google.
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Gemini per Google Workspace è un componente aggiuntivo che fornisce agli utenti accesso a funzionalità di AI generativa. Questo corso approfondisce le funzionalità di Gemini in Documenti Google utilizzando lezioni video, attività ed esempi pratici. Imparerai a utilizzare Gemini per generare contenuti scritti in base a dei prompt. Inoltre, esplorerai l'utilizzo di Gemini per modificare il testo che hai già scritto, aiutandoti a migliorare la tua produttività complessiva. Alla fine del corso avrai acquisito le conoscenze e le competenze necessarie per utilizzare con sicurezza Gemini in Documenti Google per migliorare la tua scrittura.
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Gemini per Google Workspace è un componente aggiuntivo che fornisce ai clienti funzionalità di AI generativa in Google Workspace. In questo mini corso imparerai le funzionalità principali di Gemini e come possono essere utilizzate per migliorare la produttività e l'efficienza in Gmail.
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Gemini per Google Workspace è un componente aggiuntivo che fornisce ai clienti funzionalità di AI generativa in Google Workspace. In questo percorso di apprendimento imparerai le funzionalità principali di Gemini e come possono essere utilizzate per migliorare la produttività e l'efficienza in Google Workspace.
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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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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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In this course, you'll learn to develop generative agents that answer questions using websites, documents, or structured data. You will explore Vertex AI Applications and understand the advantages of data store agents, including their scalability and security.
You'll learn about different data store types and also discover how to connect data stores to agents and add personalization for enhanced responses.
Finally, you'll gain insights into common search configurations and troubleshooting techniques.
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This is an introductory course to all solutions in the Conversational AI portfolio and the Gen AI features that are available to transform them. The course also explores the business case around Conversational AI, and the use cases and user personas addressed by the solution. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
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In this course you will learn the key architectural considerations that need to be taken into account when designing for the implementation of Conversational AI solutions. Please note Dialogflow CX was recently renamed to Conversational Agents and CCAI Insights was renamed to Conversational Insights.
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This is a introductory course to all solutions in the Contact Centre AI (CCAI) portfolio and the Generative AI features that are poised to transform them. The course also explores the CCAI go to market and engagement model, the business case around CCAI, as well as the use cases and user personas addressed by the solution.
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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of rehosting Oracle Workloads on Google Cloud.
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This course focuses on modernizing applications using OpenShift on Google Cloud. Throughout this course, you'll gain the skills necessary to describe and understand OpenShift and successfully re-platform it to Google Cloud.
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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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The Google Cloud Rapid Migration & Modernization Program (RaMP) is a holistic, end-to-end migration/modernization program that helps customers & partners leverage expertise and best practices, lower risk, control costs, and simplify a customer's path to cloud success. This course will give an overview of the program and some of the tools and best practices available to support customer migrations & modernizations.
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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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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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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models.
The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
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This course enables system integrators and partners to understand the principles of automated migrations, plan legacy system migrations to Google Cloud leveraging G4 Platform, and execute a trial code conversion.
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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud.
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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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes.
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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This content is deprecated. Please see the latest version of the course, here.
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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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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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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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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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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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This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.
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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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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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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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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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Guadagna un badge delle competenze completando i corsi Introduction to Generative AI, Introduction to Large Language Models e Introduction to Responsible AI. Superando il quiz finale, dimostrerai la tua comprensione dei concetti fondamentali relativi all'IA generativa.
Un badge delle competenze è un badge digitale rilasciato da Google Cloud come riconoscimento della tua conoscenza dei prodotti e dei servizi Google Cloud. Condividi il tuo badge delle competenze rendendo pubblico il tuo profilo e aggiungendolo al tuo profilo sui social media.
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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.
Infrastruttura Google Cloud di base: fondamenti
Earned ott 7, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned ott 6, 2025 EDT
Find, Explore and Deploy Model Garden Models
Earned set 27, 2025 EDT
AI Boost Bites: Project Notebooks
Earned set 17, 2025 EDT
AI Boost Bites: NotebookLM for Market Research
Earned set 17, 2025 EDT
AI Boost Bites: NotebookLM Video Overviews
Earned set 17, 2025 EDT
AI Boost Bites: Discover Sources in NotebookLM
Earned set 17, 2025 EDT
AI Boost Bites: NotebookLM Mind Maps
Earned set 16, 2025 EDT
AI Boost Bites: Intro to NotebookLM
Earned set 16, 2025 EDT
AI Boost Bites: Email Content Creation
Earned set 16, 2025 EDT
AI Boost Bites: Create Docs in Seconds
Earned set 9, 2025 EDT
AI Boost Bites: AI Power-Ups for Google Workspace
Earned set 4, 2025 EDT
AI Boost Bites: Tame Your Inbox with AI
Earned set 4, 2025 EDT
AI Boost Bites: Gemini Slide Summaries
Earned set 4, 2025 EDT
AI Boost Bites: No-Code Sheets & Scripts
Earned set 4, 2025 EDT
AI Boost Bites: Amplify Exec Voices with AI
Earned set 4, 2025 EDT
AI Boost Bites: Exec Summaries with Gemini Gems
Earned set 4, 2025 EDT
AI Boost Bites: Automate tasks with Gemini and Apps Script
Earned set 4, 2025 EDT
AI Boost Bites: "Eat the Frog" with NotebookLM
Earned set 4, 2025 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack
Earned set 4, 2025 EDT
AI Boost Bites: Poke Holes in Your Strategy
Earned set 4, 2025 EDT
AI Boost Bites: NotebookLM for Competitive Edge
Earned set 4, 2025 EDT
AI Boost Bites: Personalization with customized prompts
Earned set 1, 2025 EDT
AI Boost Bites: TL;DR with Gemini in Docs & Drive
Earned set 1, 2025 EDT
AI Boost Bites: Prompting like a Pro with Google Workspace
Earned set 1, 2025 EDT
AI Boost Bites: Content Generation with Gemini Made Easy
Earned ago 26, 2025 EDT
AI Boost Bites: Customer insights with NotebookLM
Earned ago 26, 2025 EDT
AI Boost Bites: Gemini Gems – Your ultimate marketing sidekick
Earned ago 26, 2025 EDT
Build search and recommendations applications with AI Applications
Earned ago 11, 2025 EDT
Deploy a RAG application with vector search in Firestore
Earned ago 11, 2025 EDT
Edit images with Imagen
Earned lug 31, 2025 EDT
Deploy and Evaluate Model Garden Models
Earned lug 30, 2025 EDT
Extend Gemini with controlled generation and Tool use
Earned lug 30, 2025 EDT
Build Generative AI Agents with Vertex AI and Flutter
Earned lug 30, 2025 EDT
Website Modernization with Generative AI on Google Cloud
Earned lug 29, 2025 EDT
Create Generative AI Apps on Google Cloud
Earned lug 21, 2025 EDT
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned giu 30, 2025 EDT
Create Embeddings, Vector Search, and RAG with BigQuery
Earned giu 26, 2025 EDT
Contact Center as a Service Implementation
Earned giu 4, 2025 EDT
Configure and Maintain CCaaS as an Admin
Earned mag 20, 2025 EDT
Manage Functions and Reporting with CCaaS
Earned mag 20, 2025 EDT
Handle Consumer Interactions with CCaaS
Earned mag 20, 2025 EDT
Hybrid Cloud Infrastructure Foundations with Anthos
Earned mag 12, 2025 EDT
Architecting with Google Kubernetes Engine: Production - Italiano
Earned mag 12, 2025 EDT
Gen AI Agents: Transform Your Organization
Earned apr 30, 2025 EDT
Gen AI Apps: Transform Your Work
Earned apr 30, 2025 EDT
Gen AI: Navigate the Landscape
Earned apr 30, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned apr 22, 2025 EDT
Gen AI: Beyond the Chatbot
Earned apr 22, 2025 EDT
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine
Earned apr 21, 2025 EDT
AI Services and GDC Deployments and Operations
Earned apr 14, 2025 EDT
Compute, Network, and Storage Services Configuration in GDC
Earned apr 11, 2025 EDT
GDC Platform Introduction
Earned apr 11, 2025 EDT
L300 Google Distributed Cloud air-gapped
Earned apr 3, 2025 EDT
L200 Google Distributed Cloud air-gapped
Earned mar 26, 2025 EDT
Introduction to Google Distributed Cloud air-gapped
Earned mar 20, 2025 EDT
Networking in Google Cloud: Fundamentals
Earned mar 19, 2025 EDT
Deploy Google Agentspace
Earned mar 17, 2025 EDT
L300 Google Distributed Cloud connected
Earned mar 10, 2025 EDT
L200 Google Distributed Cloud Connected
Earned mar 10, 2025 EDT
Architecting with Google Kubernetes Engine: Workloads - Italiano
Earned mar 10, 2025 EDT
Progettazione dell'architettura con Google Kubernetes Engine: fondamenti
Earned feb 25, 2025 EST
Change Management for Google Workspace
Earned feb 14, 2025 EST
Workspace Transformation
Earned feb 14, 2025 EST
Build Generative AI Apps with Firebase Genkit
Earned feb 7, 2025 EST
VM Migration for Partners
Earned feb 6, 2025 EST
Snowflake to BigQuery Migration
Earned feb 6, 2025 EST
Introduction to Data Engineering on Google Cloud
Earned feb 5, 2025 EST
Preparing for your Professional Data Engineer Journey
Earned gen 30, 2025 EST
Oracle to Cloud Spanner
Earned gen 29, 2025 EST
Create Engaging Video with Google Vids
Earned gen 27, 2025 EST
Gemini in Google Drive
Earned gen 27, 2025 EST
Introduction to Google Distributed Cloud connected
Earned gen 27, 2025 EST
Analytics for SAP on Google Cloud
Earned gen 15, 2025 EST
SAP on Google Cloud
Earned gen 15, 2025 EST
Oracle to BigQuery Migration
Earned gen 6, 2025 EST
BigQuery Fundamentals for Oracle Professionals
Earned gen 6, 2025 EST
Boost Productivity with Gemini in BigQuery
Earned dic 31, 2024 EST
Accelerate Knowledge Exchange with Gemini Enterprise
Earned dic 18, 2024 EST
Accelerate Your Creativity with Text-to-Image using Imagen
Earned dic 18, 2024 EST
Recommendations with AI Applications
Earned dic 13, 2024 EST
Oracle to Cloud SQL for PostgreSQL
Earned dic 6, 2024 EST
Migrating VMware to Google Cloud VMware Engine
Earned dic 6, 2024 EST
BigQuery Fundamentals for Snowflake Professionals
Earned nov 14, 2024 EST
BI Reporting: Looker Visualization on BigQuery
Earned nov 6, 2024 EST
Migrating Hadoop Workloads
Earned nov 6, 2024 EST
AWS EC2 to Compute Engine
Earned nov 6, 2024 EST
On-Premises VMware to Compute Engine
Earned nov 6, 2024 EST
Migrating Pivotal Cloud Foundry (PCF) to Google Cloud
Earned nov 6, 2024 EST
Azure Virtual Machines to Compute Engine
Earned nov 6, 2024 EST
Google API products: A key to modern application development
Earned ott 31, 2024 EDT
Creazione di sistemi di analisi dei flussi di dati resilienti su Google Cloud
Earned ott 30, 2024 EDT
Introduzione al ML: elaborazione del linguaggio
Earned ott 28, 2024 EDT
Baseline: dati, ML, AI
Earned ott 28, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned ott 24, 2024 EDT
Baseline: Deploy & Develop
Earned ott 22, 2024 EDT
Build Custom Processors with Document AI
Earned ott 21, 2024 EDT
Document AI: Building a Custom Document Extractor
Earned ott 18, 2024 EDT
Conversational Agents Quality Assurance and Deployment Lifecycle
Earned ott 14, 2024 EDT
Performance Measurement
Earned ott 4, 2024 EDT
Webhook fundamentals
Earned ott 3, 2024 EDT
Stateful Flows
Earned ott 3, 2024 EDT
Conversation Design Fundamentals
Earned ott 1, 2024 EDT
DFCX Virtual Agent Delivery Framework
Earned ott 1, 2024 EDT
CCAI Operations and Implementation
Earned set 25, 2024 EDT
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned set 23, 2024 EDT
Virtual Agent Development in Dialogflow CX for Software Devs
Earned set 20, 2024 EDT
Contact Center AI: Conversational Design Fundamentals
Earned set 20, 2024 EDT
Migrate to Containers using the Migration Assessment Tool
Earned set 17, 2024 EDT
Advanced Performance Measurement
Earned set 15, 2024 EDT
Advanced Webhook Concepts
Earned set 11, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned set 11, 2024 EDT
Incorporate Generative Features into Conversational Agent flows
Earned set 9, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned set 9, 2024 EDT
Generative Playbooks
Earned set 9, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned set 8, 2024 EDT
Mandiant Fundamentals
Earned ago 29, 2024 EDT
Chronicle SIEM Fundamentals
Earned ago 29, 2024 EDT
SOAR Fundamentals
Earned ago 29, 2024 EDT
Serverless Data Processing with Dataflow: Operations
Earned ago 29, 2024 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned ago 28, 2024 EDT
Security & Identity Fundamentals
Earned ago 26, 2024 EDT
[DEPRECATED] - Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Earned ago 21, 2024 EDT
Configura un ambiente di sviluppo di app su Google Cloud
Earned ago 21, 2024 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Earned ago 19, 2024 EDT
[DEPRECATED]- Google Cloud Computing Foundations: Cloud Computing Fundamentals - Italiano
Earned ago 16, 2024 EDT
Google Backup and Disaster Recovery
Earned ago 16, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned ago 12, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals - Italiano
Earned ago 12, 2024 EDT
Modernizing Retail and Ecommerce Solutions with Google Cloud
Earned ago 12, 2024 EDT
Orchestrating Gen AI Applications with LangChain
Earned ago 2, 2024 EDT
Improving developer velocity with Gemini Code Assist
Earned lug 31, 2024 EDT
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned lug 24, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned lug 24, 2024 EDT
Recommendation Systems on Google Cloud
Earned lug 24, 2024 EDT
Natural Language Processing on Google Cloud
Earned lug 23, 2024 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned lug 19, 2024 EDT
Computer Vision Fundamentals with Google Cloud
Earned lug 18, 2024 EDT
Production Machine Learning Systems
Earned lug 14, 2024 EDT
Feature engineering
Earned lug 11, 2024 EDT
Crea, addestra ed esegui il deployment di modelli ML tramite Keras su Google Cloud
Earned lug 11, 2024 EDT
Launching into Machine Learning - Italiano
Earned lug 9, 2024 EDT
Introduzione all'AI e al machine learning su Google Cloud
Earned lug 2, 2024 EDT
Explore Generative AI with the Gemini API in Vertex AI
Earned lug 2, 2024 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned lug 2, 2024 EDT
Introduction to Agent Assist and its GenAI Capabilities
Earned lug 1, 2024 EDT
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned giu 24, 2024 EDT
Selling the Platform & Building Client Trust
Earned giu 24, 2024 EDT
Unlocking the Power of Google Cloud Generative AI for Partners
Earned giu 24, 2024 EDT
Gemini for end-to-end SDLC
Earned giu 17, 2024 EDT
Gemini for DevOps Engineers
Earned giu 17, 2024 EDT
Gemini for Network Engineers
Earned giu 17, 2024 EDT
Gemini for Security Engineers
Earned giu 14, 2024 EDT
Gemini for Data Scientists and Analysts
Earned giu 14, 2024 EDT
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI
Earned giu 11, 2024 EDT
Modernize .Net Applications
Earned giu 11, 2024 EDT
.NET Modernization
Earned giu 10, 2024 EDT
Gemini for Cloud Architects
Earned mag 31, 2024 EDT
Gemini for Application Developers
Earned mag 31, 2024 EDT
Vertex AI Search for Commerce
Earned mag 31, 2024 EDT
Modernize Java Applications
Earned mag 31, 2024 EDT
Modernization of Java Applications for Google Cloud
Earned mag 31, 2024 EDT
Introduction to CES and Conversational Agents
Earned mag 22, 2024 EDT
Search with AI Applications
Earned mag 17, 2024 EDT
Agent Summarization (Custom)
Earned mag 17, 2024 EDT
Integrate Agent Assist with Telephony and Chatbot Systems
Earned mag 17, 2024 EDT
Gemini in Google Meet - Italiano
Earned mag 17, 2024 EDT
Gemini in Presentazioni Google
Earned mag 17, 2024 EDT
Gemini in Fogli Google
Earned mag 17, 2024 EDT
Gemini in Documenti Google
Earned mag 17, 2024 EDT
Gemini in Gmail
Earned mag 17, 2024 EDT
Introduzione a Gemini in Google Workspace
Earned mag 17, 2024 EDT
Text Prompt Engineering Techniques
Earned mag 10, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned mag 10, 2024 EDT
Virtual FAQ with data store agents
Earned mag 9, 2024 EDT
Intro to Conversational AI and Conversational AI Engagement Framework
Earned apr 28, 2024 EDT
Customer Engagement Suite with Google AI Architecture
Earned apr 19, 2024 EDT
Intro to CCAI and CCAI Engagement Framework
Earned apr 19, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned apr 16, 2024 EDT
Migrating Oracle Workloads to Google Cloud
Earned apr 16, 2024 EDT
Modernization of Applications using Openshift on Google Cloud
Earned apr 14, 2024 EDT
Custom Search with Embeddings in Vertex AI
Earned apr 11, 2024 EDT
Rapid Migration & Modernization Program
Earned apr 9, 2024 EDT
Vector Search and Embeddings
Earned apr 8, 2024 EDT
Machine learning in azienda
Earned mar 25, 2024 EDT
How Google Does Machine Learning
Earned mar 25, 2024 EDT
Modernizing Mainframe Applications with Google Cloud
Earned mar 24, 2024 EDT
Trust and Security with Google Cloud
Earned mar 22, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned mar 22, 2024 EDT
Generative AI Explorer : Vertex AI
Earned mar 19, 2024 EDT
Generative AI for Business Leaders
Earned mar 7, 2024 EST
Generative AI Fundamentals
Earned ago 17, 2023 EDT
Scaling with Google Cloud Operations
Earned lug 19, 2023 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned lug 19, 2023 EDT
Exploring Data Transformation with Google Cloud
Earned lug 19, 2023 EDT
Digital Transformation with Google Cloud
Earned lug 19, 2023 EDT
Text Prompt Engineering Techniques
Earned lug 14, 2023 EDT
Implementing Generative AI with Vertex AI
Earned lug 13, 2023 EDT
Viaggio nell'AI generativa - Vertex AI
Earned lug 13, 2023 EDT
Responsible AI: Applying AI Principles with Google Cloud - Italiano
Earned lug 13, 2023 EDT
Introduction to Generative AI Studio - Italiano
Earned giu 12, 2023 EDT
Create Image Captioning Models - Italiano
Earned giu 11, 2023 EDT
Transformer Models and BERT Model - Italiano
Earned giu 11, 2023 EDT
Encoder-Decoder Architecture - Italiano
Earned giu 11, 2023 EDT
Attention Mechanism - Italiano
Earned giu 11, 2023 EDT
Introduction to Image Generation - Italiano
Earned giu 11, 2023 EDT
Generative AI Fundamentals - Italiano
Earned giu 9, 2023 EDT
Introduction to Responsible AI - Italiano
Earned giu 9, 2023 EDT
Introduction to Large Language Models - Italiano
Earned giu 9, 2023 EDT
Introduction to Generative AI - Italiano
Earned giu 9, 2023 EDT