Sreenivasulu Goniguntla
Member since 2019
Diamond League
15037 points
Build with Gemini
Earned Sep 15, 2026 EDT
運用 Gemini 分析多模態資料並推論
Earned Jun 30, 2026 EDT
Deploy an Agent with Agent Development Kit (ADK)
Earned Jun 29, 2026 EDT
Craft ADK Agents with Persistent Memories
Earned Jun 29, 2026 EDT
Build Enterprise Agents with Code Execution on Gemini platform
Earned Jun 29, 2026 EDT
Evaluate and Improve Agent Development Kit Agents
Earned Jun 28, 2026 EDT
Build Agents with the Agent Development Kit
Earned Jun 28, 2026 EDT
Govern Agent Access with Gemini platform
Earned Jun 28, 2026 EDT
Add Agents to Gemini
Earned Jun 28, 2026 EDT
Deploy Gemini with Workspace Data Sources and Model Armor
Earned Jun 28, 2026 EDT
Govern agents with Agent Gateway, Agent Registry, and Policies
Earned Jun 28, 2026 EDT
Plan Change Management for Gemini Deployments
Earned Jun 26, 2026 EDT
Accelerate Development with Antigravity
Earned Mar 10, 2026 EDT
運用 Gemini CLI 加速開發應用程式
Earned Mar 5, 2026 EST
生成式 AI 代理：實現組織轉型
Earned Sep 10, 2025 EDT
生成式 AI 應用程式：徹底改變工作方式
Earned Sep 10, 2025 EDT
生成式 AI：掌握幕後技術與環境
Earned Sep 10, 2025 EDT
生成式 AI：瞭解基礎概念
Earned Sep 10, 2025 EDT
生成式 AI：不只是聊天機器人
Earned Sep 10, 2025 EDT
Transform and Clean your Data with Dataprep by Alteryx on Google Cloud
Earned Feb 29, 2024 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Feb 27, 2024 EST
透過 Vertex AI 建構及部署機器學習解決方案
Earned Feb 25, 2024 EST
Google Cloud 的 AI 和機器學習服務簡介
Earned Feb 23, 2024 EST
圖像生成簡介
Earned Sep 1, 2023 EDT
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Sep 1, 2023 EDT
[DEPRECATED] Generative AI Fundamentals
Earned Sep 1, 2023 EDT
負責任的 AI 技術簡介
Earned Aug 31, 2023 EDT
大型語言模型簡介
Earned Aug 31, 2023 EDT
生成式 AI 簡介
Earned Aug 29, 2023 EDT
Intro to BigQuery: Analytics & Machine Learning
Earned Sep 13, 2021 EDT
Intro to Infrastructure
Earned May 30, 2021 EDT
This is intended for individuals who completed the Build with Gemini workshop to validate the knowledge gained in that workship and earn a Skill Badge
Learn more
完成運用 Gemini 分析多模態資料並推論技能徽章中階課程，即可證明自己具備下列技能：使用 Gemini 2.0 Flash 分析文字、圖像、音訊 (以樂譜呈現) 和影片資料；以及依據這類複合型資訊，推導出結論及擷取洞察結果。
Learn more
In this challenge lab, you will demonstrate your ability to author agents using Agent Development Kit (ADK), deploy those agents to Agent Engine, and use them from a web app. Complete the challenge lab to earn a Google Cloud skill badge.
Learn more
This course explores architecting stateful AI agents that use short-term memory within a session or long-term memory services. Additionally, it covers giving agents existing expertise through skills. It details the core pillars of context engineering to facilitate personalized, continuous conversational experiences with expert agents.
Learn more
In this course, you explore the Code Execution feature of the Gemini platform, which lets AI agents safely generate and run Python code in isolated sandbox environments. You learn how the Agent Sandbox fits into the broader platform architecture, how to configure and operate Code Execution sandboxes using the Agent Platform SDK, and how to integrate code execution into agent workflows with the Agent Development Kit (ADK) in Gemini platform.
Learn more
Complete the Evaluate and Improve Agent Development Kit Agents skill badge to demonstrate your ability to use ADK's evaluation tools to "hill climb" — making measurable, iterative improvements to an agent. You will run an initial evaluation to establish a baseline, apply optimization techniques, and re-evaluate the agent to measure your success.
Learn more
In this course, you'll learn to use the Agent Development Kit (ADK) in Gemini platform to build systems where multiple AI agents collaborate on complex tasks. You'll start with the ADK agent model: how ADK represents agents, tools, and runners, and how a single agent is configured and run. You'll then make tools the model can call, persist session state across agents, and instrument the execution lifecycle with callbacks and plugins. Next, you'll orchestrate multiple agents using ADK's template workflow agents and graph-based workflows, and ground them in enterprise data through multi-source retrieval and MCP integrations. Finally, you'll deploy a multi-agent system to Agent Runtime as a managed service and register and share it through Gemini so users across an organization can reach it.
Learn more
In this challenge lab, you will act as a cloud engineer supporting the Cymbal Pools finance team. Your mission is to deploy a BigQuery-enabled agent to Agent Runtime to help process invoice data using natural language.
Rather than building from scratch, you inherit an unsecured deployment. You must establish basic data governance by configuring the Agent Development Kit (ADK), deploying the agent with a dedicated SPIFFE identity, identifying permission blocks, and applying least-privilege IAM roles so the agent can safely query and update the BigQuery database from the Agent Runtime Playground.
Learn more
In this challenge lab, you will demonstrate your ability to add agents to Gemini. You will build an agent with Agent Designer, and you will build a no-code agent with Agent Development Kit, deploy it to Agent Engine, and add it to Gemini.
Learn more
In this challenge lab, you act as a Security Engineer deploying a secure Gemini environment for Cymbal Bank. You will ground Gemini in web search and internal Workspace sources to ensure accurate, contextual responses. To maintain compliance, you will configure Model Armor policies to filter sensitive data and block threats like prompt injections and malicious URLs. Finally, you will manage specific end-user features to customize the AI experience safely
Learn more
This course covers the technical side of governing an AI agent workforce using Agent Gateway, Agent Registry, and Policies. It discusses the overall architecture of centralized agent governance, focusing on managing agent sprawl and securing communication with internal systems. The course explores the infrastructure and enterprise networking required to deploy the Agent Gateway, including automated deployment with Terraform and configuring private egress via Private Service Connect. It offers guidance towards establishing a zero-trust security perimeter using unique agent identities with mTLS, per-tool authorization with REQUEST_AUTHZ, and granular CEL policies. Furthermore, it empowers administrators to implement content security guardrails using Model Armor in Gemini platform and Cloud DLP to mitigate semantic threats like prompt injection and data leakage. Finally, the course explains how to manage tool discovery through the Agent Registry and ensure end-to-end observability and thr…
Learn more
This course will guide you through designing customer engagements that result in successful, well-utilized Gemini deployments. Study the art of change management, how to identify and engage sponsors, recruit early adopters, help your customer identify and address cultural change challenges and skills gaps, and effectively deliver project communications. Additionally, learn how to support your customer to plan, offer, conduct, and evaluate end-user training, leverage partner resources, and create essential project documents.
Learn more
Complete the Accelerate Development with Antigravity skill badge to demonstrate your proficiency in using the Antigravity IDE for developing agentic workflows. You will be tasked with configuring an MCP server, authoring custom agent skills and rules, prototyping with the Agents CLI, and deploying to the Google Cloud Agent Runtime.
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!
Learn more
這門課程適合應用程式開發人員和 DevOps 工程師，您將學會如何運用 Gemini CLI (終端機適用並採用 Gemini 技術的生成式 AI 代理)，以更聰明的方式處理工作。這門課程會說明 Gemini CLI 的安裝方式與設定、介紹用途和安全性最佳做法，並解釋指令、工具、MCP 伺服器和擴充功能。在實作練習，您會安裝及設定 Gemini CLI，藉此分析程式碼，還有建構及修改應用程式。
Learn more
「生成式 AI 代理：實現組織轉型」是 Gen AI Leader 學習路徑的第五堂也是最後一堂課程。本課程將探討組織如何運用自訂生成式 AI 代理，解決特定的業務難題。您將動手練習建構基本的生成式 AI 代理，同時探索這類代理的各種元件，例如模型、推論迴圈和工具。
Learn more
「生成式 AI 應用程式：徹底改變工作方式」是 Generative AI Leader 學習路徑的第四門課程。本課程將介紹 Google 的生成式 AI 應用程式,例如 Gemini for Workspace 和NotebookLM,也會引導您瞭解各種概念,像是建立基準、檢索增強生成、建構有效的提示詞,以及打造自動化工作流程等。
Learn more
「生成式 AI：掌握幕後技術與環境」是 Gen AI Leader 學習路徑的第三門課程。生成式 AI 正在改變我們的工作方式，以及與周遭世界的互動模式。身為領導者，您要如何駕馭其強大的功能，創造實際的業務成果？在本課程中，您將認識建構生成式 AI 解決方案時的各個層面、Google Cloud 產品與服務，以及選擇解決方案時應考量的因素。
Learn more
生成式 AI：瞭解基礎概念是 Gen AI Leader 學習路徑的第二門課程。在本課程中，您將瞭解 AI、機器學習和生成式 AI 的差異，以及各種類型的資料如何協助生成式 AI 解決業務難題，進而掌握生成式 AI 的基礎概念。您還能深入瞭解 Google Cloud 因應基礎模型限制的策略，以及開發、部署安全且負責任的 AI 技術時面臨的主要挑戰。
Learn more
「生成式 AI：不只是聊天機器人」是 Gen AI Leader 學習路徑的第一門課程，沒有先修條件。本課程旨在帶領您超越對聊天機器人的基本認識，探索生成式 AI 能為貴組織帶來的真正潛力。您將瞭解基礎模型和提示工程等概念，這些都是發揮生成式 AI 威力的關鍵。本課程也會引導您思考重要事項，協助您為貴組織制定成功的生成式 AI 策略。
Learn more
Dataprep is Google's self-service data preparation tool built in collaboration with Alteryx. Learn the basics of cleaning and preparing data for analysis and visualization, all in the Google ecosystem. In this course, you will learn how to connect Dataprep to your data in Cloud Storage and BigQuery, clean data using the interactive UI, profile the data, and publish your results back into the Google ecosystem. You will learn the basics of data transformation, including filtering values, reshaping the data, combining multiple datasets, deriving new values, and aggregating your dataset.
Learn more
完成 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程，即可證明您具備下列技能： 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Managed Service for Apache Spark 建立叢集和執行 Apache Spark 工作，以及呼叫機器學習 API，包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。
Learn more
完成 透過 Vertex AI 建構及部署機器學習解決方案 課程，即可瞭解如何使用 Google Cloud 的 Vertex AI 平台、AutoML 和自訂訓練服務， 訓練、評估、調整、解釋及部署機器學習模型。 這個技能徽章課程適合專業數據資料學家和機器學習 工程師，完成即可取得中階技能徽章。技能 徽章是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品和服務方面的精通程度， 代表您已通過測驗，能在互動式實作環境應用相關知識。完成這個技能徽章課程 和結業評量挑戰實驗室，就能獲得數位徽章， 並與親友分享。
Learn more
本課程介紹 Google Cloud 的 AI 和機器學習 (ML) 功能，著重說明如何開發生成式和預測式 AI 專案。我們也會探討「從資料到 AI」整個生命週期都適用的技術、產品和工具，並透過互動式練習，協助資料科學家、AI 開發人員和機器學習工程師精進專業知識。
Learn more
本課程將介紹擴散模型，這是一種機器學習模型，近期在圖像生成領域展現亮眼潛力。概念源自物理學，尤其深受熱力學影響。過去幾年來，在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中，擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論，並說明如何在 Vertex AI 上訓練和部署這些模型。
Learn more
隨著企業持續擴大使用人工智慧和機器學習，以負責任的方式發展相關技術也日益重要。對許多企業來說，談論負責任的 AI 技術可能不難，如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術，本課程絕對能助您一臂之力。
您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談，協助貴機構奠定良好基礎，實踐負責任的 AI 技術。
Learn more
Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
Learn more
這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。
Learn more
這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。
Learn more
這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
Learn more
Welcome Gamers! Today's game is all about experimenting with Big Query for Machine Learning! Use real life case studies to learn various concepts of BQML and have fun. Take labs to earn points. The faster you complete the lab objectives, the higher your score.
Learn more
Welcome Gamers! You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
Learn more
