Leena Dighole
成为会员时间:2022
钻石联赛
70891 积分
成为会员时间:2022
Learn to coordinate multiple specialized agents working together. This lesson teaches you when to use multi-agent systems, how to orchestrate agents with workflow patterns, and how agents communicate through shared state. By the end, you’ll build a complete multi-agent application.
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.
Complete the advanced Google DeepMind: Train A Small Language Model skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Access this lab at no-cost by signing up for the no-cost subscription. Receive 35 free credits each month!
In this course, you'll dive deep into the essential topics you need to know to design, build, and maintain a powerful CES solution. Get ready to transform your understanding of what's possible and create an architecture that drives customer satisfaction. This course is designed to introduce you to the architecture of the Customer Engagement Suite (CES). You'll explore the main considerations for building and implementing Conversational AI solutions including key architectural components and integrations. You'll also explore how Conversational AI interacts with Vertex AI and get a high-level overview of the key features of the Conversational AI Platform.
您已经构建了能够回答查询的基本 LLM 智能体,现在让我们为其赋予状态。使用会话状态来构建能够维护上下文、记住用户偏好并提供个性化体验的智能体。将智能体从“无状态的回复者”转变为“智能助理”。
您已经构建了具有高级配置的智能体,现在可赋予它们实际应用能力。为智能体配备能够搜索网络、执行代码、查询数据库和执行自定义操作的工具。让智能体从“智能回答者”转变为能够自主采取行动的得力助手。
了解如何使用智能体开发套件 (ADK) 构建可用于生产用途的复杂 AI 智能体。本课程介绍了 ADK 的开源框架,助力开发者从简单的提示工程跨越到代码优先的结构化软件开发方法,从而构建企业级多智能体系统。
打造您的首个 Gemini Enterprise 应用,赢得技能徽章!将各种数据源连接到您的应用中,构建强大、统一的搜索和分析引擎。掌握进阶能力,如:深度研究型智能体、多智能体协同构思,以及用于进行聚焦式分析的 NotebookLM。
了解 AI 智能体如何为业务带来实际影响。您将把智能体类型关联到您的关键绩效指标 (KPI),并探索能够解决实际瓶颈的用例。然后,您将了解 Gemini Enterprise 如何帮助您构建和编排合适的智能体,其范围涵盖从无代码到高代码的各种解决方案。
大致了解 AI 智能体的概念。了解 AI 智能体如何通过自主行动和推理来解决复杂问题。您将探索技术架构(模型、工具和编排),该架构使智能体能够学习、规划,并为您实现目标。
Transform your understanding of customer service with this course on the Customer Engagement Suite (CES) and its powerful generative AI capabilities. You'll start by tracing the journey of contact centers, understanding how they've evolved and where gen AI is propelling them next. Then, you'll gain a deep understanding of the core building blocks within the CES solution, seeing how each component contributes to delivering exceptional customer experiences. The course concludes by exploring the robust business case for CES, along with practical use cases and the various user personas that benefit from this innovative solution.
您已经创建了自己的第一个智能体,现在是时候更进一步了。在本课程中,您将通过学习应用高级指令、模型选择、规划功能以及结构化输出模式来精进技能,将基础 AI 智能体升级为一个精确、专业的智能助理。加入社区论坛,提出问题并参与讨论
使用 Google 的智能体开发套件 (ADK) 构建、配置和运行您的第一个 AI 智能体,将您对智能体的理解转化为实际应用。 在本实操课程中,您将设置一个完整的 ADK 开发环境,使用 Python 代码和 YAML 配置两种方式创建智能体,并通过多个界面运行智能体。您还将学习定义智能体行为的核心参数,将您在课程 1 中学到的知识应用到实际代码中。
AI 智能体代表着超越传统大语言模型 (LLM) 的重大转变:AI 智能体不再仅仅只是生成基于文本的解决方案,更能自主行动来执行这些方案。 本课程将介绍 AI 智能体的基础知识、AI 智能体与 LLM API 的区别,以及 AI 智能体在现实世界中的价值所在。本课程基于 Google 的智能体白皮书,将为您提供必要的理论基础知识,以助您编写首行智能体代码 — 非常适合希望从自主、目标导向行为(而不仅仅是文本生成)的角度理解 AI 系统的开发者、架构师和技术决策者。 加入社区论坛,提出问题并参与讨论。
Welcome to the "AI Infrastructure: Networking Techniques" course. In this course, you'll learn to leverage Google Cloud's high-bandwidth, low-latency infrastructure to optimize data transfer and communication between all the components of your AI system. By the end, you'll grasp the critical role networking plays across the entire AI pipeline from data ingestion and training to inference and be able to apply best practices to ensure your workloads run at maximum speed.
完成在 Google Cloud 中实施 DevOps 工作流技能徽章中级课程, 展示您在以下方面的技能:利用 Cloud Source Repositories 创建 git 代码库; 在 Google Kubernetes Engine (GKE) 上启动、管理和扩缩 Deployment; 设计 CI/CD 流水线架构,以自动构建容器映像并将其部署到 GKE。
完成在 Google Cloud 上部署 Kubernetes 应用技能徽章中级课程,展示您在以下方面的技能: 配置和构建 Docker 容器映像,创建和管理 Google Kubernetes Engine (GKE) 集群,利用 kubectl 实现高效 集群管理,以及按照稳健的持续交付 (CD) 实践部署 Kubernetes 应用。
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.
完成中级技能徽章课程“优化 Google Kubernetes Engine 的费用”, 展示您在以下方面的技能:创建和管理多租户集群、按命名空间监控资源使用情况、 配置集群和 Pod 自动扩缩以提高效率、设置负载均衡以实现最佳资源分布, 以及实现活跃性与就绪性探测以确保应用正常运行并具有成本效益。
完成在 Google Cloud 中管理 Kubernetes这一中级技能徽章课程, 展示您在以下方面的技能:使用 kubectl 管理部署、监控并 调试在 Google Kubernetes Engine (GKE) 上运行的应用,以及持续交付技术。
完成在 Google Cloud 上实现 CI/CD 流水线技能徽章课程,赢取中级技能徽章。 您将学习如何使用 Artifact Registry、Cloud Build 和 Cloud Deploy。您将与 Google Cloud 控制台、Google Cloud CLI、Cloud Run 和 GKE 互动。本课程将介绍如何构建持续集成 流水线,存储和保护工件,扫描漏洞,证明已批准版本 的有效性。此外,您还将获得在 GKE 和 Cloud Run 中 部署应用的实操经验。
完成 使用 Google Cloud Speech API这一技能徽章课程,赢取技能徽章。在此课程中,您将学习如何创建 Speech-to-Text API 请求、 将音频语音转写成文字,以及转写语音。
In this course you will learn how to leverage Conversational Insights to uncover hidden information from your contact center data to increase operational efficiency and drive data-driven business decisions.
In this course, you’ll take a comprehensive journey through the storage solutions available on Google Cloud, specifically tailored for AI and high-performance computing (HPC) workloads. You’ll learn how to choose the right storage for each stage of the ML lifecycle. You’ll explore how to optimize for I/O performance during training, manage massive datasets for data preparation, and serve model artifacts with low latency. Through practical examples and demonstrations, you’ll gain the expertise to design robust storage solutions that accelerate your AI innovation.
This course provides a comprehensive guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud. Through a series of lessons and practical demonstrations, you’ll explore diverse deployment strategies, ranging from highly customizable environments using Google Compute Engine (GCE) to managed solutions like Google Kubernetes Engine (GKE). Specifically, you’ll learn how to create clusters and deploy GKE for inference.
Google Workspace 专用 Gemini 是一个插件,可在 Google Workspace 中为客户提供生成式 AI 功能。在本学习路线中,您将了解 Gemini 的主要功能,以及如何在 Google Workspace 中使用它们来提高工作效率。
This course is for developers interested in learning how to use TPUs for inference—from architecture to deployment, and how to solve common implementation challenges.
This course is designed for developers looking to build an optimized AI inference stack on Google Cloud. Whether you’re working with GPUs or TPUs, you’ll explore the fundamental components of an inference stack, learn design principles for maximizing performance and reliability, and explore practical techniques to take your workloads from 0 to 1.
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.
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.
In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.
In this video, you'll learn to use Gemini in Google Sheets to automatically generate organized trackers from unstructured data. You'll learn how to write a prompt that references other Google Drive files using the "@" symbol. You'll also see how Gemini builds a fully formatted, color-coded table with drop-down menus based on the data in your notes, saving you significant manual effort.
In this video, you'll learn to use Gemini in Google Workspace to manage your calendar from your Gmail inbox. You'll learn how to ask Gemini about your schedule in the side panel and how to create new events without switching apps. You'll also learn how to use Gemini's one-click scheduling feature when it automatically detects event details in an email.
In this video, you'll learn to use Gemini in Google Slides to build polished presentations efficiently. You'll see how to create slides by referencing content directly from your Google Drive files using the "@" symbol. You'll also learn to generate custom, professional images from a simple text prompt to visually enhance your presentation.
In this video, you'll learn to use the "Ask Gemini" feature in Google Sheets to manage your data with natural language. You'll see how to ask Gemini to create dropdowns, highlight sales data, create a pivot table, filter by month, and sort by revenue.
In this video, you'll learn to use the =AI() function in Google Sheets to automate your work. You'll see how to generate text like slogans, summarize paragraphs of customer feedback, and categorize data by classifying inquiries and analyzing sentiment.
In this video, you'll learn to create "what if" scenarios using AI's reasoning. You'll see how to set a "before" scene with a person holding a cake, prompt an action by asking "what would happen if they tripped?", and let the AI generate the plausible "after" image of the cake falling.
In this video, you'll learn the "creative mashup artist" technique for combining images. You'll see how to generate a subject and a scene as two separate images, and then use a final blending prompt to fuse the astronaut from the first image and the court from the second into one new picture.
In this video, you'll learn to art direct your images in the Gemini app. You'll see how to use multi-turn editing to furnish an empty room step-by-step, and how to "remix" a photo by applying the color and texture of a butterfly's wings to a pair of rainboots.
In this video, you'll learn to create imaginative portraits in the Gemini app that maintain your likeness. You'll see how to use the "Subject, Action, Scene, Style" formula for better prompts, transport yourself into a vintage photo, and combine a photo of yourself and your dog into one new image.
In this video, you'll learn to use Gemini in Google Sheets for advanced data analysis. You'll learn how to create data visualizations, like a scatter plot, using a simple prompt. You'll also learn how to ask Gemini to analyze your data for strategic insights and recommendations, such as how to save money.
In this video, you'll learn to use NotebookLM to manage a large-scale research project. You'll see how to upload all your documents to get summaries, ask deeper strategic questions to find key insights, and use the audio feature to listen to your findings on the go.
In this video, you'll learn to use NotebookLM to analyze raw data and find compelling stories. You'll see how to ground the AI in your specific documents, prompt it to generate newsworthy PR claims, and ask it to find hidden correlations between different data points to uncover new insights.
In this video, you'll learn pro tips for conducting thorough competitive research with Gemini Deep Research. You'll see how to enhance a basic prompt by assigning a persona, specifying a table format for the output, and directing the AI to search specific sources like Reddit for richer insights.
In this video, you'll learn to use an AI assistant to streamline large-scale event planning. You'll see how to prompt an AI to brainstorm off-site ideas, create fair groups for icebreakers, build a shuttle schedule based on arrival times, and analyze survey feedback for gains and losses.
In this video, you'll learn to use Gemini Deep Research to make complex purchasing decisions with confidence. You'll see how to write a nuanced, personal prompt about your specific needs and receive a synthesized, comparative report that cuts through the clutter of online reviews.
In this video, you'll learn to turn your study guides into interactive quizzes using Gemini Canvas. You'll see how to upload your notes and use a simple prompt to generate a quiz with multiple choice and fill-in-the-blank questions that provide immediate feedback.
In this video, you'll learn to use Gemini Deep Research to conduct competitive marketing analysis. You'll see how to submit a research prompt, approve the personalized research plan Gemini creates, and receive a detailed, synthesized report on competitor campaigns to inform your strategy.
In this video, you'll learn to build a working prototype of a personalized weather app using Gemini Canvas. You'll see how to specify the cities for a 7-day forecast and then use a follow-up prompt to change the app's theme to a minimal, dark mode interface.
In this video, you'll learn to create an animated bar chart race using Gemini Canvas. You'll see how to write a prompt to visualize data over time and then use a follow-up prompt to refine the animation, such as slowing it down for a presentation.
In this video, you'll learn to create complex animated art using Gemini Canvas. You'll see how to write a descriptive prompt to generate a kinetic typography animation with distortion effects, and then use a follow-up prompt to completely change its color style.
In this video, you'll learn to build a reusable, custom "Study Guide Gem." You'll see how to write the core instructions for your Gem once, and then use it again and again to transform messy notes and articles into a perfectly structured study guide with a summary, outline, and glossary.
In this video, you'll learn to create an interactive 3D simulation using Gemini Canvas. You'll see how to build a 3D model of the solar system from a single sentence and then use follow-up prompts to add interactive and educational features, like clickable planets and fun facts.
In this video, you'll learn to build a custom personal utility app using Gemini Canvas. You'll see how to write a detailed prompt to create a Pomodoro timer tailored to your specific needs, and then use follow-up prompts to adjust its visual design.
In this video, you'll learn to use the Guided Learning experience in Gemini to build a deep understanding of any topic. You'll see how to start a conversation, engage with Gemini's probing questions, and use interactive tools like diagrams and quizzes to guide your learning journey.
In this video, you'll learn to use a simple text prompt in Gemini Canvas to build a playable game. You'll see how to create a Tic-Tac-Toe game, use a follow-up prompt to customize its theme to a retro 8-bit style, and share the final game with a link.
In this video, you'll learn to build a working music synthesizer using a simple text prompt in Gemini Canvas. You'll see how to specify controls like waveform, attack, and sustain, and then interact with the generated instrument to create and experiment with your own unique sounds.
In this video, you'll learn to use creative prompts in Gemini to make complex research fun and easy to understand. You'll see how to ask Gemini to research a topic and present the findings in a creative format, like a sports scouting report and a head-to-head bracket, to better visualize and compare your options.
In this video, you'll learn to use the Create menu in Gemini Canvas to instantly convert a block of text into a variety of visual formats. You’ll see how to take a brainstormed marketing campaign and turn it into both a shareable infographic and an internal webpage with just one click.
In this video, you'll learn to use Gemini Canvas to turn a simple drawing into a working app. You'll upload a sketch, use a simple prompt to generate code, watch a live preview build itself, and make iterative changes to your app prototype using natural language.
This video covers how NotebookLM's Reports feature dynamically suggests formats to help you create customized, trustworthy analyses of your documents with ease.
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.
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.
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.
This video covers how to build a personalized "Work with Me" agent using Gemini Gems, which helps streamline foundational feedback and makes your meetings more strategic and efficient.
AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.
Earn a skill badge by completing the Build Custom Processors with Document AI course. You learn how to extract data and classify documents by creating custom ML models specific to your business needs. This course teaches the foundation skills of building your own processors, working with optical character recognition, form parsing, processor creation, and uptraining the DocumentAI model.
完成“在 Google Cloud 上使用 TensorFlow 进行图片分类”课程,赢取中级技能徽章 。在此课程中,您将学习如何使用 TensorFlow 和 Vertex AI 来创建和训练机器学习模型。您将主要使用 Vertex AI Workbench 上用户管理的 笔记本。
完成用 Document AI 实现大规模自动数据采集课程,赢取入门级技能徽章。在本课程中,您将学习如何使用 Document AI 提取、处理和采集数据。
完成使用 Google API 分析语音和语言课程,赢取技能徽章 。在此课程中,您将学习如何在真实场景中使用 Natural Language API 和 Speech API。
完成 Sensitive Data Protection 使用入门 这一入门级技能徽章课程,展示您在以下方面的技能:使用 Sensitive Data Protection 服务 (包括 Cloud Data Loss Prevention API)来检查和隐去 Google Cloud 中的敏感数据,并对敏感数据进行去标识处理。
完成用 Cloud Vision API 分析图片课程,赢取技能徽章。在此挑战任务中,您将了解如何利用 Cloud Vision API 执行各种任务,包括从图片中提取文本。
Cloud Storage、Cloud Functions 和 Cloud Pub/Sub 都是 Google Cloud Platform 服务,可用于存储、处理和管理数据。这三项 服务可结合使用,创建各种数据驱动型应用。在 这一技能徽章课程中,您将使用 Cloud Storage 存储图片,使用 Cloud Functions 处理图片,并使用 Cloud Pub/Sub 将图片发送到另一款应用。
AI 推理是指利用经过训练的机器学习模型,通过应用其学习到的模式,对新的、未见过的数据进行预测的过程。本课程专为有兴趣在 Cloud Run 上快速部署 AI 推理服务的开发者、数据科学家和机器学习工程师而设计。对于熟悉基于云的无服务器应用部署解决方案,但可能没有使用 Google Cloud 无服务器产品运行 AI 推理经验的学员来说,本课程非常有用。 本课程包含使用 GPU 部署 AI 推理模型,以及将生成式 AI 应用与数据存储服务集成的示例。
This video covers how to create a 'project notebook' in NotebookLM by adding all relevant sources to build a central, searchable knowledge hub for your team.
This video covers how to use the Video Overviews feature in NotebookLM to automatically generate a short explainer video based on your source documents.
This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.
This video covers how to use the Mind Maps feature in NotebookLM to automatically create a visual representation of your sources, helping you understand connections and key concepts.
This video covers how to use NotebookLM as a personal research assistant by adding sources, asking questions, and generating new content formats based on your documents.
This video covers how to use Gemini in Gmail to draft new emails, refine their tone, respond with context from Drive files, and use smart reply suggestions.
This video covers how to use the 'Help me create' feature in Google Docs to generate a complete, formatted document by referencing content from other files in your Drive.
This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.
This video covers how to use Gemini in Gmail to summarize emails, find information, and draft replies, helping you manage your inbox more efficiently.
This video covers how to use Gemini in Slides to automatically generate meeting recaps and draft follow-up emails, which can streamline your post-meeting workflow and save you time.
This video covers how to use Gemini and Apps Script to automate manual tasks across Google Workspace. You'll learn to prompt Gemini to generate Apps Script code that automatically drafts email reminders in Google Sheets for tasks not marked 'Complete.' Automate your workflow with little to no technical expertise, freeing up time for more important work and eliminating manual follow-ups.
AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.
This video covers how to personalize your Gemini results in Google Workspace. Learn to incorporate documents and research papers directly into your prompts using the "@" symbol to get more targeted and relevant AI output tailored to your needs.
This video covers prompt engineering fundamentals for effective AI communication. Learn a simple framework (Persona, Task, Context, Format) to craft clear prompts, getting better, faster results from Gemini in Google Workspace. Discover how to use natural language, be specific, and iterate for optimal AI assistance.
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.
This video covers how to use NotebookLM for common marketing tasks like analyzing customer feedback, conducting market research, and generating content ideas.
本课程面向为组织配置 Gemini Code Assist 的 Google Cloud 开发者和 DevOps 工程师,需事先掌握 Google Cloud 控制台的基本知识。本课程介绍了 Gemini Code Assist 的优势,并比较了不同 Gemini Code Assist 版本的功能。本课程还介绍了如何在组织内配置和管理 Gemini Code Assist。
完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据,展示以下技能: 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Dataproc 中创建集群和运行 Apache Spark 作业,以及调用机器学习 API,包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。
完成在 Google Cloud 上使用 Machine Learning API 课程,赢取高级技能徽章。 在本课程中,您将了解以下机器学习和 AI 技术的基本功能: Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
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。
欢迎学习 Cloud TPU 课程。我们将探讨 TPU 在不同场景下的优势和劣势,并比较不同的 TPU 加速器,以帮助您选择合适的加速器。您将了解可通过哪些策略充分提高 AI 模型的性能和效率,并理解 GPU/TPU 互操作性对于创建灵活的机器学习工作流程的重要性。通过引人入胜的课程内容和实际演示,您将逐步了解如何有效利用 TPU。
对 AI 背后的强大硬件感到好奇吗?本单元将详细讲解性能经过优化的 AI 计算机,向您展示它们为何如此重要。我们将探讨 CPU、GPU 和 TPU 如何让 AI 任务高速运行,介绍它们各自的特点,并说明 AI 软件是如何充分发挥这些硬件的性能的。学习结束后,您将清楚地知道如何为自己的 AI 项目选择合适的 GPU,从而为 AI 工作负载做出明智的决策。
准备好探索 AI Hypercomputer 了吗?这门课程将带您轻松入门!我们将介绍相关基础知识,并阐释它们如何助力 AI 处理 AI 工作负载。您将了解超级计算机内部的各个组件,如 GPU、TPU 和 CPU,并知晓如何根据您的需求选择合适的部署方法。
完成中级技能徽章课程使用 Gemini 分析和推理多模态数据,展示自己在以下方面的技能:使用 Gemini 2.0 Flash 分析文本、图片、音频(以乐谱形式表示)和视频数据,对这些综合信息进行推理,以便得出结论并提取分析洞见。
完成使用 Natural Language API 分析情感挑战任务,赢取技能徽章 。在此过程中,您将学习如何使用 API 从文本中提取情感。
在本课程中,您将了解 Gemini(Google Cloud 的生成式 AI 赋能的协作工具)如何帮助分析客户数据并预测产品销售情况。此外,您还将了解如何在 BigQuery 中使用客户数据来识别、开发新客户并对其进行分类。通过动手实验,您将体验 Gemini 如何改进数据分析和机器学习工作流。 Duet AI 已更名为 Gemini,这是我们的新一代模型。
探索生成式 AI - Vertex AI 课程汇集了多组实验, 指导用户在 Google Cloud 平台上运用生成式 AI。参与实验,您将了解 如何使用 Vertex AI PaLM API 系列模型,包括 text-bison、chat-bison 和 textembedding-gecko。您还将了解提示设计、最佳实践, 以及如何使用生成式 AI 进行构思、文本分类、文本提取、文本 总结等任务。您还将学习如何通过 Vertex AI 自定义训练对基础模型进行调优, 并将模型部署到 Vertex AI 端点。
完成中级技能徽章课程使用 Vertex AI 中的 Gemini API 探索生成式 AI,展示自己在以下方面的技能: 文本生成技能、用于增强内容创作能力的图像和视频分析技能,以及在 Gemini API 中应用函数调用技术的技能。 了解如何运用先进的 Gemini 技术、探索多模态内容生成方法,并扩展 AI 赋能项目的功能。
完成在 Google Cloud 上使用 Terraform 构建基础设施技能徽章中级课程, 展示您在以下方面的技能:在使用 Terraform 时遵循基础设施即代码 (IaC) 原则;利用 Terraform 配置 来预配和管理 Google Cloud 资源;管理有效状态(本地和远程);以及将 Terraform 代码模块化,以方便重复使用和整理。
“生成式 AI 智能体:助力组织转型”是“Gen AI Leader”学习路线中的第五门课程,也是最后一门课程。本课程探讨了组织如何使用量身定制的生成式 AI 智能体,帮助应对特定的业务挑战。您将亲自动手构建一个基本的生成式 AI 智能体,并探索这些智能体的组成部分,例如模型、推理循环以及各种工具。
“生成式 AI 应用:改变工作方式”是 Generative AI Leader 学习路线的第四门课程。本课程介绍 Google 的生成式 AI 应用,例如 Gemini for Workspace 和 NotebookLM。它将引导您逐一了解接地、检索增强生成、构建有效提示和构建自动化工作流等概念。
“生成式 AI: 全面了解生成式 AI”是 Generative AI Leader 学习路线中的第三门课程。生成式 AI 正在改变我们的工作方式,以及我们与周围世界的互动方式。作为领导者,应该如何利用生成式 AI 来推动实现实际的业务成果?在本课程中,您将探索构建生成式 AI 解决方案的不同层级、Google Cloud 的产品,以及选择解决方案时需要考虑的因素。
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。
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。
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。
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。
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.
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.
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.
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.
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!
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.
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.
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.
This video covers how to create your own Gemini Gems, advanced AI capabilities that can automate repetitive tasks and supercharge your productivity.
完成在 Vertex AI 上构建和部署机器学习解决方案课程,赢取中级技能徽章。 在此课程中,您将了解如何使用 Google Cloud 的 Vertex AI Platform、AutoML 以及自定义训练服务来 训练、评估、调优、解释和部署机器学习模型。 此技能徽章课程的目标受众是专业的数据科学家和机器学习 工程师。 技能徽章是由 Google Cloud 颁发的专属数字徽章,旨在认可 您对 Google Cloud 产品与服务的熟练度;您需要在 交互式实操环境中参加考核,证明自己运用所学知识的能力后才能获得此徽章。完成此技能徽章课程 和作为最终评估的实验室挑战赛,即可获得数字徽章, 在您的人际圈中炫出自己的技能。
“生成式 AI: 剖析基本概念”是 Generative AI Leader 学习路线中的第二门课程。在本课程中,您将了解生成式 AI 的基本概念。您要探索 AI、机器学习和生成式 AI 之间的区别,了解各种数据类型如何赋能生成式 AI,从而应对各种业务挑战。您还将深入了解 Google Cloud 应对基础模型局限性的策略,以及负责任和安全的 AI 开发与部署面临着哪些关键挑战。
“生成式 AI:不只是聊天机器人”是 Generative AI Leader 学习路线中的第一门课程。学习本课程没有知识门槛。本课程旨在帮助您超越对聊天机器人的基本认知,探索生成式 AI技术为您的组织带来的真正潜力。您将探索基础模型和提示工程等概念,这些知识对利用生成式 AI 的强大功能至关重要。本课程还将说明,为组织制定成功的生成式 AI 策略时,需要考虑哪些重要因素。
完成中级技能徽章课程“提升 Gemini 模型的能力”,展示您在以下方面的技能: 利用 Gemini 模型的高级功能(包括代码生成和执行、接地、受控内容生成 和合成数据创建)来构建功能更强大、更复杂的 AI 应用。
完成“使用 Gemini 和 Imagen 构建实际 AI 应用”技能徽章入门课程,展示您在以下方面的技能:图像识别、自然语言处理、 使用 Google 强大的 Gemini 和 Imagen 模型生成图像、在 Vertex AI 平台上部署应用。
生成式 AI 应用可以提供大语言模型 (LLM) 问世前几乎不可能实现的全新用户体验。作为应用开发者,您要如何利用生成式 AI 在 Google Cloud 上构建更具吸引力且功能强大的应用? 在本课程中,您将了解生成式 AI 应用,以及如何利用提示设计和检索增强生成 (RAG) 技术,构建使用 LLM 的强大应用。您将了解可用于生产用途且适合生成式 AI 应用的架构,并构建一个基于 LLM 和 RAG 的聊天应用。
完成中级技能徽章课程使用多模态 Gemini 和多模态 RAG 检查富文档,展示您在以下方面的技能: 将多模态与 Gemini 配合使用,从而使用多模态提示从文本数据和视觉数据中提取信息、生成视频说明、 检索视频中不包含的额外信息; 将多模态检索增强生成 (RAG) 与 Gemini 配合使用,以构建包含文本和图片的文档的元数据、获取所有相关文本块并输出引用。
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。
在本次课程中,探索 AI 赋能的搜索技术、工具和应用。学习利用向量嵌入的语义搜索、融合语义和关键字的混合搜索方法,以及检索增强生成 (RAG) 技术,以打造基于事实的 AI 智能体,尽可能减少 AI 幻觉。获取 Vertex AI Vector Search 实战经验,打造您自己的智能搜索引擎。
Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.
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。
完成 在 Vertex AI 中设计提示入门技能徽章课程,展示以下方面的技能: Vertex AI 中的提示工程、图片分析和多模态生成式技术。探索如何编写有效的提示,指导生成式 AI 输出, 以及将 Gemini 模型应用于真实的营销场景。
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.
本课程教您如何使用深度学习来创建图片标注模型。您将了解图片标注模型的不同组成部分,例如编码器和解码器,以及如何训练和评估模型。学完本课程,您将能够自行创建图片标注模型并用来生成图片说明。
本课程介绍 Vertex AI Studio,这是一种用于与生成式 AI 模型交互、围绕业务创意进行原型设计并在生产环境中落地的工具。通过沉浸式应用场景、富有吸引力的课程和实操实验,您将探索从提示到产品的整个生命周期,了解如何将 Vertex AI Studio 用于多模态 Gemini 应用、提示设计、提示工程和模型调优。本课程的目的在于帮助您利用 Vertex AI Studio,在自己的项目中充分发掘生成式 AI 的潜力。
本课程向您介绍 Transformer 架构和 Bidirectional Encoder Representations from Transformers (BERT) 模型。您将了解 Transformer 架构的主要组成部分,例如自注意力机制,以及该架构如何用于构建 BERT 模型。您还将了解可以使用 BERT 的不同任务,例如文本分类、问答和自然语言推理。完成本课程估计需要大约 45 分钟。
本课程简要介绍了编码器-解码器架构,这是一种功能强大且常见的机器学习架构,适用于机器翻译、文本摘要和问答等 sequence-to-sequence 任务。您将了解编码器-解码器架构的主要组成部分,以及如何训练和部署这些模型。在相应的实验演示中,您将在 TensorFlow 中从头编写简单的编码器-解码器架构实现代码,以用于诗歌生成。
本课程将向您介绍注意力机制,这是一种强大的技术,可令神经网络专注于输入序列的特定部分。您将了解注意力的工作原理,以及如何使用它来提高各种机器学习任务的性能,包括机器翻译、文本摘要和问题解答。
本课程向您介绍扩散模型。这类机器学习模型最近在图像生成领域展现出了巨大潜力。扩散模型的灵感来源于物理学,特别是热力学。过去几年内,扩散模型成为热门研究主题并在整个行业开始流行。Google Cloud 上许多先进的图像生成模型和工具都是以扩散模型为基础构建的。本课程向您介绍扩散模型背后的理论,以及如何在 Vertex AI 上训练和部署此类模型。
完成 Introduction to Generative AI、Introduction to Large Language Models 和 Introduction to Responsible AI 三门课程,赢取技能徽章。通过最终测验,即表明您理解了生成式 AI 的基本概念。 技能徽章是由 Google Cloud 颁发的数字徽章,旨在认可您对 Google Cloud 产品与服务的了解程度。公开您的个人资料并将技能徽章添加到您的社交媒体个人资料中,以此来分享您获得的成就。
随着企业对人工智能和机器学习的应用越来越广泛,以负责任的方式构建这些技术也变得更加重要。但对很多企业而言,真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI,本课程正适合您。 本课程将介绍 Google Cloud 目前如何践行 Responsible AI,以及从中总结的最佳实践和经验教训,便于您以此为框架构建自己的 Responsible AI 方法。
这是一节入门级微课程,旨在解释什么是负责任的 AI、它的重要性,以及 Google 如何在自己的产品中实现负责任的 AI。此外,本课程还介绍了 Google 的 7 个 AI 开发原则。
这是一节入门级微学习课程,探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能,还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
这是一节入门级微课程,旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。