Google Cloud Big Data and Machine Learning Fundamentals
Earned sept. 29, 2023 EDT
Security Practices with Google Security Operations - SIEM
Earned sept. 25, 2023 EDT
SAP on Google Cloud
Earned sept. 21, 2023 EDT
Preparing for Your Professional Cloud Security Engineer Journey
Earned sept. 6, 2023 EDT
This course will familiarize you with the core functionality of Chronicle, including the user interface, connections, and settings.
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This course reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI applications.
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Google Threat Intelligence provides unmatched visibility into threats by delivering detailed and timely threat intelligence to security teams around the world. This course covers the various capabilities of Google Threat Intelligence and common ways that organizations use this product to proactively mitigate threats.
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In the context of a real-world use case, learn how to use Security Command Center’s virtual red teaming feature to identify risks. Then, learn how attack exposure scores help you prioritize issues and how risk reports keep stakeholders in the loop.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Security Operations Engineer certification exam.
You'll review NotebookLM features, create a notebook in NotebookLM, and learn how to use a study guide to practice for a certification exam.
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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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Learn a variety of strategies and techniques to engineer effective prompts for generative models
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Learn how to leverage Gemini multimodal capabilities to process and generate text, images, and audio and to integrate Gemini through APIs to perform tasks such as content creation and summarization.
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This course delves into the complexities of assessing the quality of large language model outputs. It examines the challenges enterprises face due to the subjective and sometimes incorrect nature of LLM responses, including hallucinations and inconsistent results. The course introduces various evaluation metrics for different tasks like classification, text generation, and question answering, such as Accuracy, Precision, Recall, F1 score, ROUGE, BLEU, and Exact Match. It also explores evaluation methods offered by Vertex AI LLM Evaluation Services, including computation-based, autorater, and human evaluation, providing insights into their application and benefits. Finally, the module covers how to unit test LLM applications within Vertex AI.
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Data stores represent a simple way to make content available to many types of generative AI applications, including search applications, recommendations engines, Gemini Enterprise apps, Agent Development Kit agents, and apps built with Google Gen AI or LangChain SDKs. Connect data from many sources include Cloud Storage, Google Drive, chat apps, mail apps, ticketing systems, third-party file storage providers, Salesforce, and many more.
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Learn how to create Hybrid Search applications using Vertex AI Vertex Search to combine semantic searching with keyword search to return results based on both semantic meaning and keyword matching.
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Explore the four pillars of Enterprise Readiness in generative AI: data governance and privacy, security and compliance support, infrastructure reliability and sustainability, and responsible AI. You will also learn how these pillars address concerns about data privacy and security. Learn about customizing foundation models with your data while keeping your data safe using adapter layers, how to keep your AI models safe and compliant when deploying them across the world, and the multiple layers of encryption, rigorous controls, supply chain audits, and ongoing security testing that are built into Google Cloud. You will also learn about security controls such as VPC, customer-managed encryption keys, access transparency, and data residency zones. And explore enterprise controls, certifications, and responsible AI tooling available in Vertex AI to ensure your data remains secure and compliant with global regulations when deploying generative AI models.
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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.
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In this course, you will learn how to easily scale AI from laptop to Cloud by bringing Ray and Vertex AI together. You will learn how to create a Ray cluster, connect to it, and run some simple Ray code. You will also learn how to integrate BigQuery seamlessly with Ray data.
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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Vertex AI APIs, vector stores, and the LangChain framework.
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Initial deployment of Vertex AI Search and Gemini Enterprise apps takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience.
In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Gemini Enterprise apps.
(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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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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In this Google DeepMind course you will discover the mechanisms of the transformer architecture. You will investigate how transformer language models process prompts to make context-sensitive next-token predictions. Through practical activities you will explore the attention mechanism, visualize attention weights, and encounter advanced concepts like masked attention and multi-head attention. You will also learn other techniques that are necessary to build neural networks that are well-suited to be used as language models. Finally, through activities on values, stakeholder mapping and community engagement, you will practice concrete tools for ensuring AI projects are developed with communities, not just for them.
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AI Applications provides built-in analytics for your Vertex AI Search and Gemini Enterprise apps. Learn what metrics are tracked and how to view them in this course.
(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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This course dives into the world of media creation in Vertex AI using Nano Banana and Veo. Learn to design text and image-based prompts to produce high-quality, consistent images, and captivating, cinematic video clips. You'll also learn to refine generated assets using core editing functions. Finally, this course guides you through multi-tool workflow implementations for creative control and consistency, empowering you to transform images into video clips and leverage Gemini for prompt writing assistance and feedback.
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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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Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.
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This course explores how to implement a streaming analytics solution using Pub/Sub.
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NotebookLM is an AI-powered collaborator that helps you do your best thinking. After uploading your documents, NotebookLM becomes an instant expert in those sources so you can read, take notes, and collaborate with it to refine and organize your ideas.
NotebookLM Pro gives you everything already included with NotebookLM, as well as higher utilization limits, access to premium features, and additional sharing options and analytics.
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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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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.
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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
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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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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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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.
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This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
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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 introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
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This course introduces important topics of AI privacy and safety. It explores practical methods and tools to implement AI privacy and safety recommended practices through the use of Google Cloud products and open-source tools.
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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.
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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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Complete the Improve customer and agent satisfaction with Agent Assist skill badge to demonstrate your proficiency in configuring basic conversational agents that can escalate actions to human agents, and configuring Agent Assist to help human agents with customer queries. You prove your knowledge in configuring Generators for summarization, classification and recommendation of tickets as well leverage tools such as Generative Knowledge Assist, to provide further context to human agents.
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 course will focus on Agent Assist, an AI-powered tool designed to enhance customer service interactions. In this course, you will learn how Agent Assist can enhance the productivity of human agents while interacting with customers through the chat channel. You’ll learn how to take full advantage of Agent Assist from Gemini Enterprise for Customer Experience, and its range of Gen AI features and functionality.
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Connect conversational agents to external systems and APIs to expand what agents can do, designing an end-to-end system that is resilient, fault-tolerant and secure.
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Welcome to the Cloud TPUs course. We'll explore the advantages and disadvantages of TPUs in various scenarios and compare different TPU accelerators to help you choose the right fit. You'll learn strategies to maximize performance and efficiency for your AI models and understand the significance of GPU/TPU interoperability for flexible machine learning workflows. Through engaging content and practical demos, we'll guide you step-by-step in leveraging TPUs effectively.
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Curious about the powerful hardware behind AI? This module breaks down performance-optimized AI computers, showing you why they're so important. We'll explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them. By the end, you'll know exactly how to pick the right GPU for your AI projects, helping you make smart choices for your AI workloads.
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Ready to get started with AI Hypercomputers? This course makes it easy! We'll cover the basics of what they are and how they help AI with AI workloads. You'll learn about the different components inside a hypercomputer, like GPUs, TPUs, and CPUs, and discover how to pick the right deployment approach for your needs.
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This course equips learners with skills to govern data within their Google Workspace environment. Learners will explore data loss prevention rules in Gmail and Drive to prevent data leakage. They will then learn how to use Google Vault for data retention, preservation, and retrieval purposes. Next, they will learn how to configure data regions and export settings to align with regulations. Finally, learners will discover how to classify data using labels for enhanced organization and security.
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This course was designed to give learners a comprehensive understanding of Google Workspace core services. Learners will explore enabling, disabling, and configuring settings for these services, including Gmail, Calendar, Drive, Meet, Chat, and Docs. Next, they'll learn how to deploy and manage Gemini to empower their users. Finally, learners will examine use cases for AppSheet and Apps Script to automate tasks and extend the functionality of Google Workspace applications.
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This course empowers learners to secure their Google Workspace environment. Learners will implement strong password policies and two-step verification to govern user access. They will then utilize the security investigation tool to proactively identify and respond to security risks. Next, they will manage third-party app access and mobile devices to ensure security. Finally, learners will enforce email security and compliance measures to protect organizational data.
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This course was designed to provide an understanding of user and resource management in Google Workspace. Learners will explore the configuration of organizational units to align with their organization's needs. Additionally, learners will discover how to manage various types of Google Groups. They will also develop expertise in managing domain settings within Google Workspace. Finally, learners will master the optimization and structuring of resources within their Google Workspace environment.
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This course was designed to prepare Google Workspace Administrators to troubleshoot common Google Workspace issues. Learners will practice diagnosing and resolving problems in Gmail, Calendar, and Drive, and navigating the Admin console. They will also experience analyzing audit logs to troubleshoot security issues, and gathering information and using available resources to troubleshoot and report technical issues.
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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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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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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 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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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 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 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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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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This course introduces AI Applications. You will learn about the types of apps that you can create using AI Applications, the high-level steps that its data stores automate for you, and what advanced features can be enabled for Search apps.
(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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Learn about the fundamental features of Security Command Center on Google Cloud. Spend time in this course to understand assets, detection and compliance. Security Command Center is a key part of your Google Cloud security journey, complete these modules and quiz to earn a completion badge.
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This course covers the baseline skills needed for the Google Security Operations Platform. The modules will cover specific actions and features that security engineers should become familiar with to start using the toolset.
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Take the next steps in working with the Chronicle Security Operations Platform. Build on fundamental knowledge to go deeper on cusotmization and tuning.
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This course provides a comprehensive overview of Google Cloud Security Command Center (SCC) Enterprise, a Cloud-Native Application Protection Platform (CNAPP) solution that helps organizations prevent, detect, and respond to threats across Google Cloud services.
You will learn about core SCC Enterprise features, including enhanced threat detection, in-depth vulnerability management, and integrated case management.
Fundamental concepts in threat management and vulnerability assessment will also be covered, along with practical demonstrations of how to use SCC Enterprise to identify, investigate, and remediate security risks within your multi-cloud environment.
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This training aims to up-skill Google Cloud partners to deliver customer engagements through Delivery Navigator for available technical practice offerings. Learners will be able to navigate around the Delivery Navigator platform, select the desired method(s), and export the project WBS to a desired work management tool and Shared Google Drive. Sample artefacts are available through the Delivery Navigator methods and will be provided for reference.
Contents of this course will be updated as new features are released for the Delivery Navigator platform.
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Google Threat Intelligence provides unmatched visibility into threats by delivering detailed and timely threat intelligence to security teams around the world. This course covers the various capabilities of Google Threat Intelligence and common ways that organizations use this product to proactively mitigate threats.
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This course gives you a deep dive into the workflows of Tier 3 analysts.
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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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In this course, you'll learn to develop AI agents that answer questions using websites, documents, or structured data. You will explore 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 course gives you a deep dive into the workflows of Tier 1 and Tier 2 security analysts.
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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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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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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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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 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: 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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Welcome to the fourth course of the "Networking in Google Cloud" series: Network Security!
In this course, you'll dive into the services for safeguarding your Google Cloud network infrastructure.
The first module, Distributed Denial of Service (DDoS) Protection, covers how to fortify your network against Distributed Denial of Service (DDoS) attacks, ensuring uninterrupted availability of your services.
In the second module, Controlling Access to VPC Networks, you'll learn the network access control, enabling you to define permissions for who can access your resources and how.
Finally, in the third module, Advanced Security Monitoring and Analysis, we'll explore how to proactively detect and respond to potential threats, keeping your Google Cloud environment secure and resilient.
By the end of this course, you'll have a comprehensive understanding of Google Cloud network security.
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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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This course provides an introduction to databases and summarized the differences in the main database technologies. This course will also introduce you to Looker and how Looker scales as a modern data platform. In the lessons, you will build and maintain standard Looker data models and establish the foundation necessary to learn Looker's more advanced features.
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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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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images
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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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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
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Discover how to use Colab Enterprise, a managed notebook environment that provides secure and compliant storage for your notebooks, that comes with two code-generation features: code complete and code gen. Create and use runtime templates in Vertex AI Workbench to give users access to more powerful compute resources while still maintaining control over the types of resources that are spun up. Share notebooks with other users and use versioning to keep track of changes to your notebooks. Learn how Colab Enterprise integrates BigQuery and Vertex AI. You will see how to pull data from BigQuery, use BQML to train a model, and have it all integrated with Vertex Model Registry. Explore how to fine-tune a Foundation model or generative AI model using the Vertex AI SDK. And, learn how to evaluate a tuned model and compare the results of multiple runs.
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Embark on a journey into the captivating world of embeddings! This course equips you with the theoretical and practical knowledge to harness their power in both product search and generative AI.
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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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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 implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataproc.
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Welcome to Optimize in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on optimization.
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Welcome to Design in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on schema design.
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This course explores the Geographic Information Systems (GIS), GIS Visualization, and machine learning enhancements to BigQuery.
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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.
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This course explores how to implement a streaming analytics solution using Dataflow and BigQuery.
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Identify critical assets and their compliance requirements.
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This training course introduces Cloud NGFW. Topics include how Cloud NGFW provides centralized firewall management, centralized firewall visibility, advanced threat protection, and firewall insights.
En savoir plus
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.
En savoir plus
This course is for Google Cloud’s top 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. Those who complete the training and assessment will receive the Google Cloud Generative AI Trailblazer badge through Skills Boost.
En savoir plus
This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.
En savoir plus
This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
En savoir plus
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.
En savoir plus
As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
En savoir plus
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.
En savoir plus
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.)
En savoir plus
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.
En savoir plus
This course explores the different products and capabilities of Gemini Enterprise for Customer Experience 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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
(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.
En savoir plus
This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
En savoir plus
Welcome to the third course of the "Networking in Google Cloud" series: Network Architecture!
In this course, you will explore the fundamentals of designing efficient and scalable network architectures within Google Cloud.
In the first module, Introduction to Network Architecture, we'll start by introducing you to the core components and concepts of network architecture, including subnets, routes, firewalls, and load balancing.
Then in the second module, network topologies, we'll dive into various network topologies commonly used in Google Cloud, discussing their strengths, and weaknesses.
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Welcome to the second course in the networking and Google Cloud series routing and addressing.
In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities.
Module one will lay the foundation by exploring network routing and addressing in Google Cloud, covering key building blocks such as routing IPv4, bringing your own IP addresses and setting up cloud DNS. In Module two will shift our focus to private connection options, exploring use cases and methods for accessing Google and other services privately using internal IP addresses.
By the end of this course, you'll have a solid grasp of how to effectively route and address your network traffic within Google Cloud.
En savoir plus
While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
En savoir plus
This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
En savoir plus
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.
En savoir plus
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.
En savoir plus
Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series.
In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area.
You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training.
This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.
En savoir plus
Google Workspace with Gemini provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Meet. Through video lessons, hands-on activities and practical examples, you will gain a comprehensive understanding of the Gemini features in Google Meet. You learn how to use Gemini to generate background images, improve your video quality, and translate captions. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Meet to maximize the effectiveness of your video conferences.
En savoir plus
This course helps you structure your preparation for the Professional Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
En savoir plus
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.
En savoir plus
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.
En savoir plus
In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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In this course, we’ll show you how organizations are aligning their BI strategy to most effectively achieve business outcomes with Looker. We'll follow four iterative steps: Plan, Build, Launch, Grow, and provide resources to take into your own services delivery to build Looker with the goal of achieving business outcomes.
En savoir plus
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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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.
En savoir plus
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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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.
En savoir plus
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.
En savoir plus
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.
En savoir plus
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
En savoir plus
This course explores how to leverage Looker to create data experiences and gain insights with modern business intelligence (BI) and reporting.
En savoir plus
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.
En savoir plus
Good news! There’s a new updated version of this learning path available for you!Open the new Professional Cloud DevOps Engineer Certification Learning Path to begin, once you’ve selected the new path all your current progress will be reflected in the new version.
En savoir plus
This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls.
This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.
En savoir plus
Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Sheets.
En savoir plus
Google Workspace with Gemini provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Docs using video lessons, hands-on activities and practical examples. You learn how to use Gemini to generate written content based on prompts. You also explore using Gemini to edit text you’ve already written, helping you improve your overall productivity. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Docs to improve your writing.
En savoir plus
Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Gmail.
En savoir plus
Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this learning path, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Workspace.
En savoir plus
This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
En savoir plus
This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
En savoir plus
This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.
En savoir plus
Good news! There’s a new updated version of this learning path available for you!Open the new Professional Cloud Security Engineer Certification Learning Path to begin, once you’ve selected the new path all your current progress will be reflected in the new version.
En savoir plus
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
En savoir plus
Learn the technical aspects you need to know about Chronicle and how it can help you detect and action threats.
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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.
En savoir plus
This course helps learners prepare for the Professional Cloud Security Engineer (PCSE) Certification exam. Learners will be exposed to and engage with exam topics through a series of lectures, diagnostic questions, and knowledge checks. After completing this course, learners will have a personalized workbook that will guide them through the rest of their certification readiness journey.
[DEPRECATED] SOAR Fundamentals
Earned déc. 9, 2025 EST
Model Armor: Securing AI Deployments
Earned déc. 5, 2025 EST
Google Threat Intelligence
Earned déc. 5, 2025 EST
Security Command Center: Identify and Prioritize Risks
Earned déc. 5, 2025 EST
Build a Certification Study Guide: PSOE Exam Prep
Earned déc. 5, 2025 EST
Find, Explore and Deploy Model Garden Models
Earned nov. 7, 2025 EST
Engineer Effective Prompts for Generative Models
Earned nov. 7, 2025 EST
Explore Google's Gen AI Models
Earned nov. 7, 2025 EST
Model evaluation on Vertex AI
Earned nov. 7, 2025 EST
Create Data Stores for Gen AI Applications
Earned nov. 7, 2025 EST
Implement Hybrid Search
Earned nov. 5, 2025 EST
Enterprise Readiness in Generative AI
Earned nov. 4, 2025 EST
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service
Earned nov. 4, 2025 EST
Scale AI with Ray on Vertex AI
Earned nov. 4, 2025 EST
Implement RAG with Vertex AI
Earned nov. 4, 2025 EST
Vertex AI Search and Gemini Enterprise UI Configurations
Earned nov. 3, 2025 EST
How Google Does Machine Learning
Earned nov. 3, 2025 EST
Google DeepMind: 04 Discover The Transformer Architecture
Earned nov. 2, 2025 EST
Vertex AI Search and Gemini Enterprise Analytics
Earned oct. 20, 2025 EDT
Generate and Edit Media in Vertex AI
Earned sept. 17, 2025 EDT
Boost Productivity with Gemini in BigQuery
Earned sept. 16, 2025 EDT
Using BigQuery Machine Learning for Inference
Earned sept. 16, 2025 EDT
Data Warehousing for Partners: Stream Data with Pub/Sub
Earned sept. 16, 2025 EDT
Introduction to NotebookLM
Earned sept. 16, 2025 EDT
Azure Virtual Machines to Compute Engine
Earned sept. 15, 2025 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned sept. 14, 2025 EDT
Create ML Models with BigQuery ML
Earned sept. 14, 2025 EDT
Custom Search with Embeddings in Vertex AI
Earned sept. 14, 2025 EDT
Vector Search and Embeddings
Earned sept. 14, 2025 EDT
Introduction to Vertex AI Studio
Earned sept. 14, 2025 EDT
Transformer Models and BERT Model
Earned sept. 14, 2025 EDT
Prepare Data for ML APIs on Google Cloud
Earned sept. 13, 2025 EDT
Build a Certification Study Guide: PMLE
Earned sept. 13, 2025 EDT
Working with Notebooks in Vertex AI
Earned sept. 11, 2025 EDT
Introduction to Generative AI
Earned sept. 10, 2025 EDT
Introduction to Large Language Models
Earned sept. 10, 2025 EDT
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned sept. 10, 2025 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned sept. 10, 2025 EDT
Responsible AI for Developers: Privacy & Safety
Earned sept. 10, 2025 EDT
Responsible AI for Developers: Fairness & Bias
Earned sept. 9, 2025 EDT
Create Generative AI Apps on Google Cloud
Earned sept. 9, 2025 EDT
Improve customer and agent satisfaction with Agent Assist
Earned sept. 4, 2025 EDT
Introduction to Agent Assist and its GenAI Capabilities
Earned sept. 4, 2025 EDT
Extend Conversational Agents Functionality with Webhooks and Tools
Earned août 15, 2025 EDT
AI Infrastructure: Cloud TPUs
Earned août 7, 2025 EDT
AI Infrastructure: Cloud GPUs
Earned août 7, 2025 EDT
AI Infrastructure: Introduction to AI Hypercomputer
Earned août 7, 2025 EDT
Google Workspace Data Governance
Earned août 7, 2025 EDT
Google Workspace Core Services
Earned août 7, 2025 EDT
Google Workspace Security
Earned août 7, 2025 EDT
Google Workspace User and Resource Management
Earned août 7, 2025 EDT
Google Workspace Troubleshooting
Earned août 5, 2025 EDT
Snowflake to BigQuery Migration
Earned juin 16, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned juin 15, 2025 EDT
AI Boost Bites: No-Code Sheets & Scripts
Earned juin 13, 2025 EDT
AI Boost Bites: Amplify Exec Voices with AI
Earned juin 13, 2025 EDT
AI Boost Bites: Exec Summaries with Gemini Gems
Earned juin 13, 2025 EDT
AI Boost Bites: "Eat the Frog" with NotebookLM
Earned juin 13, 2025 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack
Earned juin 13, 2025 EDT
AI Boost Bites: NotebookLM for Competitive Edge
Earned juin 13, 2025 EDT
AI Boost Bites: TL;DR with Gemini in Docs & Drive
Earned juin 13, 2025 EDT
AI Boost Bites: Customer insights with NotebookLM
Earned juin 13, 2025 EDT
AI Boost Bites: Gemini Gems – Your ultimate marketing sidekick
Earned juin 13, 2025 EDT
Gemini for Data Scientists and Analysts
Earned juin 13, 2025 EDT
Introduction to AI Applications
Earned mai 22, 2025 EDT
Security Command Center Fundamentals
Earned mai 15, 2025 EDT
Google Security Operations - Fundamentals
Earned mai 15, 2025 EDT
Google Security Operations - Deep Dive
Earned mai 14, 2025 EDT
Getting Started with Security Command Center Enterprise
Earned mai 14, 2025 EDT
Delivery Navigator for Partners
Earned mai 14, 2025 EDT
DEPRECATED Google Threat Intelligence
Earned mai 13, 2025 EDT
SecOps on GDC for Tier 3 Analysts
Earned mai 10, 2025 EDT
Conversational Agents Quality Assurance and Deployment Lifecycle
Earned mai 7, 2025 EDT
Extend CX Agents with Vertex AI Search data stores
Earned mai 7, 2025 EDT
SecOps on GDC for Tier 1 and Tier 2 Analysts
Earned avr. 26, 2025 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned avr. 23, 2025 EDT
Build Batch Data Pipelines on Google Cloud
Earned avr. 21, 2025 EDT
Chronicle SIEM Fundamentals
Earned avr. 17, 2025 EDT
Mandiant Fundamentals
Earned avr. 17, 2025 EDT
Gen AI: Navigate the Landscape
Earned avr. 17, 2025 EDT
Gen AI Agents: Transform Your Organization
Earned avr. 17, 2025 EDT
Gen AI Apps: Transform Your Work
Earned avr. 17, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned avr. 17, 2025 EDT
Gen AI: Beyond the Chatbot
Earned avr. 17, 2025 EDT
Networking in Google Cloud: Network Security
Earned avr. 13, 2025 EDT
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine
Earned avr. 10, 2025 EDT
The Modern Data Platform and LookML
Earned mars 17, 2025 EDT
Natural Language Processing on Google Cloud
Earned mars 10, 2025 EDT
Feature Engineering
Earned mars 8, 2025 EST
Create Image Captioning Models
Earned mars 8, 2025 EST
Production Machine Learning Systems
Earned mars 8, 2025 EST
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned mars 7, 2025 EST
Launching into Machine Learning
Earned mars 7, 2025 EST
Building AI with Colab Enterprise
Earned mars 7, 2025 EST
Vector Search and Embeddings in Product Search
Earned mars 2, 2025 EST
Create Embeddings, Vector Search, and RAG with BigQuery
Earned mars 2, 2025 EST
Document AI: Building a Custom Document Extractor
Earned fév. 27, 2025 EST
Data Warehousing for Partners: Process Data with Dataproc
Earned fév. 27, 2025 EST
Data Warehousing for Partners: Optimize in BigQuery
Earned fév. 27, 2025 EST
Data Warehousing for Partners: Design in BigQuery
Earned fév. 27, 2025 EST
Data Warehousing for Partners: BigQuery Extended Capabilities
Earned fév. 27, 2025 EST
Data Warehousing for Partners: Enable Google Cloud Customers
Earned fév. 27, 2025 EST
Data Warehousing for Partners: Streaming Analytics
Earned fév. 27, 2025 EST
Evaluate Your Cloud Next Generation Firewall Needs
Earned fév. 23, 2025 EST
Introduction to Cloud Next Generation Firewall
Earned fév. 23, 2025 EST
Unlocking the Power of Google Cloud Generative AI for Partners
Earned fév. 22, 2025 EST
Google Cloud Generative AI Trailblazer
Earned fév. 22, 2025 EST
Security Best Practices in Google Cloud
Earned fév. 22, 2025 EST
Machine Learning Operations (MLOps) for Generative AI
Earned fév. 20, 2025 EST
Vertex AI Search for Commerce
Earned fév. 19, 2025 EST
Responsible AI: Applying AI Principles with Google Cloud
Earned fév. 19, 2025 EST
Deploy Google Agentspace
Earned fév. 18, 2025 EST
Accelerate Knowledge Exchange with Gemini Enterprise
Earned fév. 18, 2025 EST
Recommendations with AI Applications
Earned fév. 18, 2025 EST
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned fév. 18, 2025 EST
Generative Playbooks
Earned fév. 16, 2025 EST
Accelerate Your Creativity with Text-to-Image using Imagen
Earned fév. 16, 2025 EST
Customer Experience with Google AI Architecture
Earned fév. 13, 2025 EST
Conversational AI Voice and Chat Integrations
Earned fév. 12, 2025 EST
Building Complex Self-Service Experiences in Conversational Agents
Earned fév. 11, 2025 EST
Search with AI Applications
Earned fév. 1, 2025 EST
Work with Gemini Models in BigQuery
Earned jan. 23, 2025 EST
Networking in Google Cloud: Network Architecture
Earned oct. 4, 2024 EDT
Networking in Google Cloud: Routing and Addressing
Earned oct. 4, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned sept. 27, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned juin 16, 2024 EDT
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned juin 15, 2024 EDT
Machine Learning Operations (MLOps): Getting Started
Earned juin 15, 2024 EDT
DEPRECATED Planning for a Google Workspace Deployment
Earned juin 1, 2024 EDT
Gemini in Google Meet
Earned mai 30, 2024 EDT
Preparing for Your Professional Cloud Network Engineer Journey
Earned mai 16, 2024 EDT
Migrating VMware to Google Cloud VMware Engine
Earned mai 16, 2024 EDT
Modernizing Mainframe Applications with Google Cloud
Earned mai 16, 2024 EDT
Developing a Google SRE Culture
Earned avr. 12, 2024 EDT
Achieving Business Outcomes with Looker
Earned avr. 3, 2024 EDT
Digital Transformation with Google Cloud
Earned mars 18, 2024 EDT
Trust and Security with Google Cloud
Earned mars 18, 2024 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned mars 18, 2024 EDT
Innovating with Google Cloud Artificial Intelligence
Earned mars 18, 2024 EDT
Scaling with Google Cloud Operations
Earned mars 17, 2024 EDT
Exploring Data Transformation with Google Cloud
Earned mars 17, 2024 EDT
Analyzing and Visualizing Data in Looker
Earned mars 17, 2024 EDT
Data Warehousing for Partners: Analyze Data with Looker
Earned mars 16, 2024 EDT
BI Reporting: Looker Visualization on BigQuery
Earned mars 16, 2024 EDT
Certification Learning Path: Professional Cloud DevOps Engineer
Earned mars 13, 2024 EDT
Managing Security in Google Cloud
Earned mars 1, 2024 EST
Gemini in Google Sheets
Earned jan. 12, 2024 EST
Gemini in Google Docs
Earned jan. 12, 2024 EST
Gemini in Gmail
Earned jan. 12, 2024 EST
Introduction to Google Workspace with Gemini
Earned jan. 12, 2024 EST
Encoder-Decoder Architecture
Earned déc. 28, 2023 EST
Attention Mechanism
Earned déc. 28, 2023 EST
Introduction to Image Generation
Earned déc. 28, 2023 EST
Introduction to Responsible AI
Earned déc. 22, 2023 EST
Certification Learning Path: Professional Cloud Security Engineer
Earned oct. 8, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned sept. 29, 2023 EDT
Security Practices with Google Security Operations - SIEM
Earned sept. 25, 2023 EDT
SAP on Google Cloud
Earned sept. 21, 2023 EDT
Preparing for Your Professional Cloud Security Engineer Journey
Earned sept. 6, 2023 EDT