Ganamanas Das
Member since 2022
Silver League
16845 points
Govern Agent Access with Gemini platform
Earned אוק 10, 2026 EDT
Add Agents to Gemini
Earned אוק 9, 2026 EDT
Deploy an Agent with Agent Development Kit (ADK)
Earned אוק 8, 2026 EDT
Model Armor: Securing AI Deployments
Earned אוק 4, 2026 EDT
Improve Agent Search findings on Gemini platform
Earned אוק 4, 2026 EDT
Evaluate and Improve Agent Development Kit Agents
Earned אוק 4, 2026 EDT
Secure your Agents with Gemini Enterprise Agent Platform
Earned אוק 4, 2026 EDT
Govern agents with Agent Gateway, Agent Registry, and Policies
Earned אוק 4, 2026 EDT
Use a Third-Party Identity Provider with Workforce Identity Federation
Earned אוק 4, 2026 EDT
Deploy Gemini to Transform Enterprises
Earned אוק 4, 2026 EDT
Plan Change Management for Gemini Deployments
Earned אוק 4, 2026 EDT
Cost Estimation and Optimization for Agentic Solutions
Earned אוק 2, 2026 EDT
Hill Climb Generative and Agentic Systems
Earned אוק 2, 2026 EDT
Upgrade to the Latest Gemini Models
Earned אוק 2, 2026 EDT
Evaluate Agents on Gemini platform
Earned אוק 2, 2026 EDT
Evaluate Generative and Agentic Systems
Earned אוק 2, 2026 EDT
Craft ADK Agents with Persistent Memories
Earned אוק 2, 2026 EDT
Build Enterprise Agents with Code Execution on Gemini platform
Earned ספט 27, 2026 EDT
Build Agents with the Agent Development Kit
Earned ספט 26, 2026 EDT
Accelerate Development with Antigravity
Earned ספט 26, 2026 EDT
Build with the Managed Agents API on Gemini platform
Earned ספט 24, 2026 EDT
Accelerate Agent Development with Antigravity and Agents CLI
Earned ספט 23, 2026 EDT
Deploy Gemini with Workspace Data Sources and Model Armor
Earned יונ 1, 2026 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned אוק 16, 2025 EDT
Build a Certification Study Guide: PMLE
Earned יונ 9, 2025 EDT
[DEPRECATED] Deploy Google Agentspace
Earned יונ 1, 2025 EDT
Accelerate Knowledge Exchange with Gemini Enterprise
Earned מאי 31, 2025 EDT
Conversational AI Voice and Chat Integrations
Earned ינו 7, 2025 EST
Prompt Design in Agent Platform
Earned דצמ 27, 2024 EST
Introduction to Responsible AI - בעברית
Earned אפר 30, 2024 EDT
Transformer Models and BERT Model - בעברית
Earned מאי 11, 2023 EDT
Attention Mechanism - בעברית
Earned מאי 11, 2023 EDT
Introduction to Large Language Models - בעברית
Earned מאי 11, 2023 EDT
Introduction to Generative AI - בעברית
Earned מאי 10, 2023 EDT
Understanding Google Cloud Security and Operations - בעברית
Earned יול 6, 2022 EDT
Infrastructure and Application Modernization with Google Cloud - בעברית
Earned יול 5, 2022 EDT
Innovating with Data and Google Cloud - בעברית
Earned יול 3, 2022 EDT
Digital Transformation with Google Cloud - בעברית
Earned יול 2, 2022 EDT
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.
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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.
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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.
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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 apps. Explore other content in the Gemini Agent Ready (GEAR) program.
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This course covers techniques for boosting and filtering search results, as well as the implementation of meta tags for advanced search control.
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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.
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As organizations rapidly deploy AI workforces, securing these autonomous systems becomes paramount. Secure Your Agents with Gemini Enterprise Agent Platform is a practical, security-first course designed to help you establish centralized, zero-trust control and comprehensive visibility over your AI ecosystem.
Instead of relying on theoretical frameworks, this course teaches you how to defend AI agents the way they are actually attacked—layer by layer, with identity and access at the absolute foundation.
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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…
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This course provides learners the knowledge to configure Workforce Identity Federation to grant Google Cloud and Gemini access to users that authenticate using a third-party Identity Provider. The curriculum includes theory and demo videos covering workforce identity pools, OIDC and SAML providers, attribute mapping, IAM policies, and troubleshooting guidance.
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This course covers the technical side of deploying Gemini. It discusses the overall architecture of Gemini, decisions to be made when provisioning the app infrastructure, and integrating enterprise data via Data Stores, Connectors. and Actions. The course also explores the kinds of agents that can be added to Gemini. It offers guidance towards establishing a security perimeter using IAM, VPC Service Control, Context-Aware Access, and semantic controls deployed with Model Armor in Gemini platform. Finally, it empowers administrators to fine-tune the end-user experience through comprehensive configuration options, and explains how administrators keep AI deployments secure, compliant, and performant through OpenTelemetry instrumentation and prompt logging.
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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.
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In this course, you’ll learn how to estimate and manage GenAI solution costs, focusing on the unique unit economics of AI versus traditional cloud billing. You will learn to:
Understand Metering: Master the four Google Cloud GenAI metering categories and the token economy driving costs.
Estimate Costs: Build defensible estimates using the Pricing Calculator for models, context caching, and agentic components.
Optimize Spend: Leverage controls—such as input/output token reduction, caching, RAG efficiency, and model routing—while balancing cost, quality, and latency.
Implement Governance: Apply FinOps best practices, including budgets, quotas, cost attribution, and Provisioned Throughput management to control spend.
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In this course, you'll learn the disciplined process of hill climbing to transform your generative and agentic systems into reliable, high-performing tools. You'll examine the iterative 8-step loop by diagnosing system failures through trajectory analysis and applying precise interventions across the model, prompt, tool, and framework layers. By the end of this course, you'll be prepared to optimize system architecture and automate the hill climbing cycle while balancing quality, cost, and latency as first-class metrics.
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In this course, you'll learn how to establish a rigorous upgrade regression testing pipeline, safely deploy models using A/B testing and/or shadow mode, and address legacy prompt technical debt. You'll also learn the latest about Gemini 3 parameters including thinking levels and thought signatures, as well as new capabilities like media resolution controls and streaming function calls.
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In this course, you learn to evaluate, diagnose, and optimize AI agents on the Gemini platform. You begin where most teams begin: the agent runs, but you have no eval cases, no test data, and no production traffic to grade it with. From there you follow the Quality Flywheel, the evaluate-analyze-optimize loop at the center of Gemini platform. You instrument the agent so it emits the telemetry Gemini platform reads, generate eval cases by simulation, choose the metrics that grade them, run offline evaluations, monitor live traffic and alert on quality drift, then cluster failures and optimize. A final module covers build-time evaluation with the Agent Development Kit (ADK) in Gemini platform, which runs on your machine before you deploy.
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Throughout this course, you'll learn how to establish rigorous evaluation criteria, perform evaluations, design objective rubrics, calibrate autoraters, and simulate evaluation data. You'll gain the skills needed to design, execute, and scale a comprehensive evaluation plan that aligns system capabilities with organizational KPIs. This course is designed for technical practitioners, machine learning engineers, and software architects who build and deploy generative and agentic applications.
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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.
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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.
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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.
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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!
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In this course, you'll learn to build and run enterprise agents on the Managed Agents API, the managed agent runtime on Gemini platform. Three conceptual lessons give you the mental model. You'll learn why a real business task needs an agent rather than a chat model. You'll examine how the platform splits into a control plane that defines agents and a data plane that runs them. You'll learn how to assemble an agent from a definition, a sandboxed environment, mounted data, tools, and skills. Furthermore, you'll learn how to run it with background interactions, a streamed reason-act loop, resilient typed results, and state that persists across turns. You then put that model to work in a hands-on lab, where you build, run, and harden a retail merchandising agent for Cymbal Retail from an empty project to a production-shaped deployment. By the end, you'll be able to design, build, and operate a managed agent of your own.
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In this course, you’ll learn to simplify the creation of autonomous enterprise agents using the Agent Development Kit (ADK) in Gemini platform and you will learn how to leverage the power of Antigravity and the Agents CLI to transform your agent development workflow. In this course, you will explore practical techniques to automate repetitive tasks and significantly accelerate the creation of robust, enterprise-grade agents, ensuring scalability and efficiency in your AI projects.
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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
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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.
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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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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.
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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.)
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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.
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Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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זהו קורס מבוא ממוקד שמטרתו להסביר מהי אתיקה של בינה מלאכותית, למה היא חשובה ואיך Google נוהגת לפי כללי האתיקה של הבינה המלאכותית במוצרים שלה. מוצגים בו גם 7 עקרונות ה-AI של Google.
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בקורס הזה נציג את הארכיטקטורה של טרנספורמרים ואת המודל של ייצוגים דו-כיווניים של מקודד מטרנספורמרים (BERT). תלמדו על החלקים השונים בארכיטקטורת הטרנספורמר, כמו מנגנון תשומת הלב, ועל התפקיד שלו בבניית מודל BERT. תלמדו גם על המשימות השונות שאפשר להשתמש ב-BERT כדי לבצע אותן, כמו סיווג טקסטים, מענה על שאלות והֶקֵּשׁ משפה טבעית. נדרשות כ-45 דקות כדי להשלים את הקורס הזה.
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בקורס נלמד על מנגנון תשומת הלב, שיטה טובה מאוד שמאפשרת לרשתות נוירונים להתמקד בחלקים ספציפיים ברצף הקלט. נלמד איך עובד העיקרון של תשומת הלב, ואיך אפשר להשתמש בו כדי לשפר את הביצועים במגוון משימות של למידת מכונה, כולל תרגום אוטומטי, סיכום טקסט ומענה לשאלות.
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זהו קורס מבוא ממוקד שבוחן מהם מודלים גדולים של שפה (LLM), איך משתמשים בהם בתרחישים שונים לדוגמה ואיך אפשר לשפר את הביצועים שלהם באמצעות כוונון של הנחיות. הוא גם כולל הסבר על הכלים של Google שיעזרו לכם לפתח אפליקציות בינה מלאכותית גנרטיבית משלכם.
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זהו קורס מבוא ממוקד שמטרתו להסביר מהי בינה מלאכותית גנרטיבית, איך משתמשים בה ובמה היא שונה משיטות מסורתיות של למידת מכונה. הוא גם כולל הסבר על הכלים של Google שיעזרו לכם לפתח אפליקציות בינה מלאכותית גנרטיבית משלכם.
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הקורס בוחן ניהול עלויות, אבטחה ותפעול בענן. ראשית, מוסבר איך עסקים יכולים לרכוש שירותי IT מספק שירותי ענן ולשמר חלק מהתשתית שלהם או לבחור לא לשמר אותה בכלל. שנית, הקורס מתאר איך האחריות על אבטחת נתונים מתחלקת בין ספק שירותי הענן לעסק, וסוקר את אבטחת ההגנה לעומק (defense-in-depth) שמובנית ב-Google Cloud. לבסוף, הקורס מתייחס לכך שצוותי IT ומנהלי העסק צריכים לשנות את החשיבה על ניהול משאבי IT בענן, ונוגע באופן שבו כלי ניטור המשאבים ב-Google Cloud יכולים לסייע להם לשמור על שליטה וניראות בסביבת הענן שלהם.
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בארגונים מסורתיים רבים משתמשים במערכות ובאפליקציות מדורות קודמים, וקשה לבצע באמצעותן התאמה לעומס ופעולות מהירות הדרושות כדי לעמוד בציפיות מודרניות של לקוחות. מנהיגים עסקיים וקובעי מדיניות IT צריכים כל הזמן לבחור בין תחזוקה של מערכות מדורות קודמים לבין השקעה במוצרים ובשירותים חדשים.
בקורס הזה נבחן את האתגרים הנובעים משימוש בתשתית IT מיושנת, ואיך בעלי עסקים יכולים לבצע מודרניזציה של תשתיות בעזרת טכנולוגיית ענן. הקורס מתחיל בהבנה מעמיקה של אפשרויות המחשוב השונות הזמינות בענן ופירוט היתרונות של כל אחת מהאפשרויות. לאחר מכן נבחן את האפשרויות למודרניזציה של האפליקציות ושל ממשקי API (ממשק תכנות יישומים). בקורס מתוארים גם מגוון פתרונות של Google Cloud שיכולים לשפר את תהליך פיתוח המערכות וניהולן בעסקים שונים, כמו Compute Engine, App Engine ו-Apigee.
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טכנולוגיית הענן לבדה מספקת לעסק חלק קטן בלבד מהערך האמיתי שלה. כשהיא משולבת עם נתונים בנפח רב מאוד, נוצרת העוצמה שמאפשרת להפיק ערך וליצור חוויות חדשות ללקוחות.
במסגרת הקורס הזה תלמדו מהם נתונים, איך השתמשו בהם בעבר בחברות לצורך קבלת החלטות ולמה הם קריטיים כל כך ללמידה חישובית. בנוסף, בקורס הזה יוצגו ללומדים מושגים טכניים כמו נתונים מובְנים ולא מובְנים, מסד נתונים, מחסן נתונים (data warehouse) ואגמי נתונים (data lakes). בהמשך, הקורס יעסוק במוצרי Google Cloud הנפוצים ביותר בתחום הנתונים, ובמוצרים כאלה ששיעור השימוש בהם גדל במהירות הרבה ביותר.
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מהי טכנולוגיית ענן ומהו מדע הנתונים? וחשוב יותר, איך הם יכולים לעזור לכם, לצוות שלכם ולעסק שלכם?
קורס המבוא הזה בנושא טרנספורמציה דיגיטלית מתאים למי שרוצה ללמוד על טכנולוגיית הענן כדי להתמקצע ולהצטיין בעבודתו וכדי לעזור בפיתוח העתיד של העסק.
בקורס יוגדרו מונחי יסוד כגון הענן, נתונים וטרנספורמציה דיגיטלית. בנוסף, נבחן דוגמאות של חברות מרחבי העולם שמשתמשות בטכנולוגיית הענן כדי לבצע טרנספורמציה בעסק. הקורס כולל סקירה של סוגי ההזדמנויות שיש לחברות ושל האתגרים הנפוצים שחברות מתמודדות איתם במהלך טרנספורמציה דיגיטלית. הקורס גם מדגים איך עמודי התווך של פתרונות Google Cloud יכולים לעזור בתהליך. חשוב לומר: טרנספורמציה דיגיטלית לא קשורה רק לשימוש בטכנולוגיות חדשות. כדי הטרנספורמציה תהיה מלאה, ארגונים צריכים גם ליישם חדשנות ולפתח דפוס חשיבה שמקדם חדשנות בכל התחומים והצוותים. השיטות המומלצות המתוארות בקורס יעזרו לכם להשיג את המטרה הזו.
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