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Lalit Bhardwaj

成为会员时间:2024

黄金联赛

4251 积分
Arcade February 2026 Sprint 4 Earned Feb 23, 2026 EST
Arcade February 2026 Sprint 3 Earned Feb 21, 2026 EST
Arcade February 2026 Sprint 2 Earned Feb 20, 2026 EST
Arcade February 2026 Sprint 1 Earned Feb 17, 2026 EST
Arcade Trail: Application Development Earned Feb 13, 2026 EST
Google DeepMind: 03 Design And Train Neural Networks Earned Feb 10, 2026 EST
Model Armor:保障 AI 部署安全 Earned Feb 4, 2026 EST
AI 时代安全性简介 Earned Feb 4, 2026 EST
面向开发者的 Responsible AI:隐私保护和安全 Earned Feb 3, 2026 EST
面向开发者的 Responsible AI:可解释性和透明度 Earned Feb 2, 2026 EST
面向开发者的 Responsible AI:公平性与偏见 Earned Feb 1, 2026 EST
利用 Vertex AI 实现机器学习运维 (MLOps):模型评估 Earned Feb 1, 2026 EST
适用于生成式 AI 的机器学习运维 (MLOps) Earned Feb 1, 2026 EST
Google Skills Arcade Trivia January 2026 Week 3 Earned Jan 29, 2026 EST
Google Skills Arcade Trivia January 2026 Week 2 Earned Jan 27, 2026 EST
Level 2: Event-Driven Systems Earned Jan 24, 2026 EST
Level 1: Compute, Storage and Monitoring Earned Jan 17, 2026 EST

This month's Arcade Sprint 4 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!

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This month's Arcade Sprint 3 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!

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This month's Arcade Sprint 2 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!

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This month's Arcade Sprint 1 is live! It's designed for quick learning. Since the labs are open all month, there's no rush; just jump in when you have the time. You'll earn 1 Arcade Point and a new skill with each step. It's that simple: grab your point and keep the momentum going!

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Developers using managed cloud services can reduce infrastructure management effort by up to 60%, allowing more time to focus on building features that matter. In this level, you’ll gain hands-on experience with Cloud SQL, containerized workloads, and cloud-native application development through the Arcade ACE App Dev series, helping you design, deploy, and manage scalable applications more efficiently.

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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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本课程回顾了 Model Armor 的基本安全功能,并让您能够使用该服务。您将了解与 LLM 相关的安全风险,以及 Model Armor 如何保护您的 AI 应用。

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人工智能 (AI) 具备巨大的变革潜力,但也带来了新的安全挑战。本课程专为负责安全性和数据保护的领导者而设计,助其运用相关策略在组织内安全管理 AI。学习一个有助于实现以下目标的框架:主动识别并减轻 AI 特有的风险,保护敏感数据,确保遵从法规,构建弹性 AI 基础设施。通过四个不同行业的精选用例,探索这些策略如何应用于现实场景。

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本课程介绍 AI 隐私保护和安全方面的重要主题,还将探索使用 Google Cloud 产品和开源工具实施建议的 AI 隐私保护和安全实践的实用方法和工具。

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本课程介绍了 AI 可解释性和透明度的相关概念,探讨了 AI 透明度对于开发者和工程师的重要性。同时探索了有助于在数据和 AI 模型中实现可解释性和透明度的实用方法及工具。

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本课程介绍了 Responsible AI 的概念和 AI 原则,还介绍了在 AI/机器学习实践中识别公平性与偏见以及减少偏见的实用技巧,同时探索了使用 Google Cloud 产品和开源工具来实施 Responsible AI 最佳实践的实用方法和工具。

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本课程能让机器学习从业者掌握评估生成式和预测式 AI 模型的基本工具、方法和最佳实践。要确保机器学习系统在实际运用中提供可靠、准确、高效的结果,做好模型评估至关重要。 学员将深入了解各项评估指标、方法及如何在不同模型类型和任务中适当应用这些指标和方法。课程将着重介绍生成式 AI 模型带来的独特挑战,并提供有效解决这些挑战的策略。通过利用 Google Cloud 的 Vertex AI Platform,学员可学习如何在模型选择、优化和持续监控工作中实施卓有成效的评估流程。

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本课程致力于为您提供所需的知识和工具,让您能够了解 MLOps 团队在部署和管理生成式 AI 模型以及探索 Vertex AI 如何帮助 AI 团队简化 MLOps 流程时面临的独特挑战,并帮助您在生成式 AI 项目中取得成功。

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Hey there! You're invited to game on with Google Skills Arcade Trivia for January Week 3! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the January Trivia Week 3 badge!

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Hey there! You're invited to game on with Google Skills Arcade Trivia for January Week 2! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the January Trivia Week 2 badge!

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Over 80% of modern applications rely on event-driven architectures or real-time messaging to stay responsive at scale. In challenge, you’ll work with Pub/Sub to build event-driven systems, deploy workloads on Google Kubernetes Engine, manage authentication and dynamic secrets with Vault, and explore language processing using Cloud APIs. You’ll also build Flutter applications and work with Cloud Spanner, gaining hands-on experience across messaging, security, data, and application development.

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A new year brings a fresh opportunity to build consistency in how you learn and apply cloud skills. In this challenge, you’ll deploy applications using App Engine and Cloud Run Functions, work with Compute Engine instances, and manage data through Cloud Storage using both the console and CLI. You’ll also define fine-grained access with custom IAM roles, analyze logs, create alerts from logs-based metrics, and monitor workloads across multiple projects. Together, these labs help you begin the year by strengthening essential cloud operations skills and developing habits that support reliable, well-monitored applications.

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