Shankar M
Date d'abonnement : 2026
Ligue d'Argent
11818 points
Arcade Base Camp July 2026
Earned juil. 23, 2026 EDT
Build a Certification Study Guide: PCDBE Exam Prep
Earned juil. 23, 2026 EDT
[Deprecated]Google Security Operations - Fundamentals
Earned juil. 23, 2026 EDT
Quiz: GDC Air-Gapped Security Operator Fundamentals
Earned juil. 23, 2026 EDT
Security Command Center Fundamentals
Earned juil. 23, 2026 EDT
Introduction to Looker
Earned juil. 23, 2026 EDT
Network Observability on Google Cloud
Earned juil. 23, 2026 EDT
Introduction to Google Distributed Cloud Sandbox
Earned juil. 23, 2026 EDT
Introduction to Image Generation
Earned juil. 23, 2026 EDT
Google DeepMind: 03 Design And Train Neural Networks
Earned juil. 23, 2026 EDT
Innovating with Data and Google Cloud
Earned juil. 23, 2026 EDT
Google DeepMind: 07 Accelerate Your Model
Earned juil. 23, 2026 EDT
Innovating with Google Cloud Artificial Intelligence
Earned juil. 23, 2026 EDT
AI Infrastructure: Cloud TPUs
Earned juil. 23, 2026 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned juil. 23, 2026 EDT
Encoder-Decoder Architecture
Earned juil. 23, 2026 EDT
Human-Centered AI
Earned juil. 23, 2026 EDT
Build a Certification Study Guide: PMLE
Earned juil. 23, 2026 EDT
Introduction to Reliable Deep Learning
Earned juil. 23, 2026 EDT
Attention Mechanism
Earned juil. 23, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model
Earned juil. 23, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned juil. 23, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation
Earned juil. 23, 2026 EDT
Enterprise Search on Generative AI App Builder
Earned juil. 23, 2026 EDT
AI Boost Bites: Content Generation with Gemini Made Easy
Earned juil. 23, 2026 EDT
Introduction to reCAPTCHA
Earned juil. 23, 2026 EDT
Machine Learning Operations (MLOps): Getting Started
Earned juil. 22, 2026 EDT
Introduction to GKE Networking
Earned juil. 22, 2026 EDT
Generative AI for Healthcare
Earned juil. 22, 2026 EDT
Introduction to Generative AI
Earned juil. 22, 2026 EDT
AI Boost Bites: Triage a Crisis with Gemini
Earned juil. 22, 2026 EDT
AI Boost Bites: Tame Your Inbox with AI
Earned juil. 22, 2026 EDT
AI Boost Bites: The Recruiter's Playbook in Gmail
Earned juil. 22, 2026 EDT
AI Boost Bites: Gemini Calendar Hacks in Gmail
Earned juil. 22, 2026 EDT
Gemini in Gmail
Earned juil. 22, 2026 EDT
[DEPRECATED] Gmail
Earned juil. 22, 2026 EDT
Derive Insights from BigQuery Data
Earned juil. 21, 2026 EDT
Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Database Engineer certification exam. You'll get an overview of the Gemini Notebook essentials, learn how to add sources, and use the study guide to practice for a certification exam.
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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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This quiz tests your GDC Air-Gapped Security Operator Fundamental knowledge.
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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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In this introductory course, you'll learn how Looker can help you explore, analyze, and visualize your data to drive better decisions. Through a combination of video lectures and demos, you'll discover how to connect to various data sources, build interactive dashboards, and perform effective data analysis. Whether you're a data analyst, BI analyst, data scientist or business user, this course will equip you with the foundational knowledge to start using Looker effectively, regardless of your background.
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This mini-course will empower users to understand Network Observability in Google Cloud to gain comprehensive visibility into their network traffic, proactively identify issues, and optimize their infrastructure. By understanding how Network Observability works in Google Cloud, organizations can ensure seamless application delivery and enhance their overall cloud architecture and operations.
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In this course, you'll gain a solid understanding of Google Distributed Cloud (GDC) Sandbox—a cost-effective and accessible environment for building, testing, and evaluating GDC solutions. You'll explore the GDC Sandbox's architecture, key features, and service offerings and see how they enable real-world use cases. Most importantly, you'll observe demonstrations on performing essential operational tasks, such as deploying virtual machines and containers.
By the end, you'll be equipped to confidently navigate the GDC Sandbox environment.
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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 Gemini Enterprise Agent Platform.
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In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.
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Cloud technology on its own only provides a fraction of the true value to a business; When combined with data–lots and lots of it–it has the power to truly unlock value and create new experiences for customers.
In this course, you'll learn what data is, historical ways companies have used it to make decisions, and why it is so critical for machine learning. This course also introduces learners to technical concepts such as structured and unstructured data. database, data warehouse, and data lakes. It then covers the most common and fastest growing Google Cloud products around data.
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Train more powerful models with a single GPU. In this course, you will learn how hardware can speed up model training and the key considerations when training models on a GPU. First, you will learn how to estimate the number of computations and the amount of computer memory required to train large neural networks. You will then discover techniques for reducing the computing and memory requirements when training a model. Techniques which you will apply for fine-tuning a Gemma model with 4 billion parameters. Finally, you will consider the potential environmental impacts of machine learning, with a focus on where questions of energy, water, and e-waste intersect with justice and equity.
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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.
As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Welcome to 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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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.
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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.
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Explore the vital transition from task-driven workflows to human-centric AI orchestration. You will learn to strategically distinguish between augmentation and automation, and how to balance machine efficiency with human intuition.
Explore other content in the Gemini Agent Ready (GEAR) program.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
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This course introduces you to the world of reliable deep learning, a critical discipline focused on developing machine learning models that not only make accurate predictions but also understand and communicate their own uncertainty. You'll learn how to create AI systems that are trustworthy, robust, and adaptable, particularly in high-stakes scenarios where errors can have significant consequences.
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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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In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
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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 Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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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 Agent Platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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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 Generative AI App Builder to integrate enterprise-grade generative AI search.
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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 course equips learners with the information they need to deploy reCAPTCHA in their websites, mobile applications, and web application firewalls (WAF). The course covers roles and permissions needed to integrate various reCAPTCHA features such as keys, assessments, and IP address allowlists, as well as the steps involved in preparing their cloud environment for reCAPTCHA integration. Learners will then have the opportunity to integrate reCAPTCHA into a cloud security architecture with Cloud Armor Bot Management.
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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, the first in the Configure Google Kubernetes Engine Networking series, you'll learn how to use the Google Cloud Architecture Center to get started designing a VPC networking solution to support a GKE infrastructure.
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Specifically designed for healthcare professionals, this course demystifies generative AI, the latest breakthrough in artificial intelligence, and the large language models (LLMs) that drive it. Discover real-world applications of generative AI in healthcare settings and master the art of crafting effective prompts tailored to your goals. Explore other content in the Gemini Agent Ready (GEAR) program.
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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 video covers how to use the Gemini side panel in Gmail to analyze long email threads, identify technical owners, and draft escalations to resolve customer crises.
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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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In this video, you'll learn to streamline your email workflow using Gemini. Master the art of generating to-do lists from your inbox, crafting specific outreach prompts for better results, and polishing your drafts to perfection.
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This video covers how to use Gemini in Gmail to manage your Google Calendar by asking about your schedule in the side panel and using the one-click "add to calendar" feature for events detected in emails.
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This course covers how to use Gemini in Gmail to optimize your email management. Learn to summarize lengthy threads, retrieve information using natural language, draft professional responses, and organize communication strategies directly inside your inbox. Explore other content in the Gemini Agent Ready (GEAR) program.
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Gmail is Google’s cloud based email service that allows you to access your messages from any computer or device with just a web browser.
In this course, you’ll learn how to compose, send and reply to messages. You will also explore some of the common actions that can be applied to a Gmail message, and learn how to organize your mail using Gmail labels.
You will explore some common Gmail settings and features. For example, you will learn how to manage your own personal contacts and groups, customize your Gmail Inbox to suit your way of working, and create your own email signatures and templates.
Google is famous for search. Gmail also includes powerful search and filtering. You will explore Gmail’s advanced search and learn how to filter messages automatically.
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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Data Studio by connecting to BigQuery data.
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