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Akshita Sood

Mitglied seit 2026

Diamond League

9634 Punkte
Build generative virtual agents with API integrations Earned Jun 7, 2026 EDT
Build deterministic Virtual Agent enhanced with data stores Earned Jun 4, 2026 EDT
Elastische Google Cloud-Infrastruktur: Skalierung und Automatisierung Earned Jun 2, 2026 EDT
Erste Schritte mit der Google Kubernetes Engine Earned Mai 29, 2026 EDT
Incorporate Generative Features into Conversational Agent Flows Earned Mai 28, 2026 EDT
Developing Applications with Cloud Run on Google Cloud: Fundamentals Earned Mai 28, 2026 EDT
Text Prompt Engineering Techniques Earned Mai 25, 2026 EDT
Select a Google Cloud Database for Your Applications Earned Mai 25, 2026 EDT
Build Production-Ready Conversational Agents Earned Mai 24, 2026 EDT
Google Cloud: Prompt Engineering Guide Earned Mai 23, 2026 EDT
Create Agents with Generative Playbooks Earned Mai 21, 2026 EDT
Einführung in die Google Cloud-Infrastruktur: Hauptdienste Earned Mai 11, 2026 EDT
Customer Experience Agent Studio: Fundamentals Earned Mai 10, 2026 EDT
Conversational AI Voice and Chat Integrations Earned Mai 10, 2026 EDT
Introduction to Gemini Enterprise for Customer Experience Earned Mai 7, 2026 EDT
Extend virtual agents with webhooks, tools, and Messenger integration Earned Mai 7, 2026 EDT
Build agents with CX Agent Studio Earned Mai 7, 2026 EDT
Create Conversational Agents with Stateful Flows Earned Mai 4, 2026 EDT
Extend Conversational Agents Functionality with Webhooks and Tools Earned Mai 4, 2026 EDT

Demonstrate the ability to create and deploy generative virtual agents with natural language using Vertex AI Agent Builder and augment responses by integrating Gemini responses with third party APIs and your own data stores You will use the following technologies and Google Cloud services: Vertex AI Agent Builder Gemini Cloud Functions

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Demonstrate the ability to create and deploy deterministic virtual agents using Dialgflow CX and augment responses by grounding results on your own data integrating with Vertex AI Agent Builder data stores and leveraging Gemini for summarizations. You will use the following technologies and Google Cloud services: Vertex AI Agent Builder Dialogflow CX Gemini

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Dieser On-Demand-Intensivkurs bietet Teilnehmenden eine Einführung in die umfangreiche und flexible Infrastruktur und die Plattformdienste von Google Cloud. In Videovorträgen, Demos und praxisorientierten Labs lernen Teilnehmende Lösungselemente kennen und stellen sie bereit. Dazu gehören sichere Interconnect-Netzwerke, Load Balancing, Autoscaling, Automatisierung der Infrastruktur und verwaltete Dienste.

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Willkommen beim Kurs „Erste Schritte mit der Google Kubernetes Engine“. Sie interessieren sich für Kubernetes, eine Software-Ebene, die sich zwischen Ihren Anwendungen und der Hardwareinfrastruktur befindet? Dann sind Sie hier genau richtig! Die Google Kubernetes Engine bietet Ihnen Kubernetes als verwalteten Dienst in Google Cloud. In diesem Kurs lernen Sie die Grundlagen der Google Kubernetes Engine (GKE) kennen und erfahren, wie Sie Anwendungen containerisieren und in Google Cloud ausführen. Er beginnt mit einer Einführung in Google Cloud, gefolgt von einem Überblick über Container und Kubernetes, die Kubernetes-Architektur sowie Kubernetes-Vorgänge.

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Explore the Generative AI features for Conversational Agents and how to incorporate them into stateful Flows. Discover the possibilities with Generators, Generative Fallback, and Data Stores, as well as best practices and security settings for using these features.

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This course introduces the Cloud Run serverless platform for running applications. In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle. You learn about service identities, how to control access to services, and how to develop and test your application locally before deploying it to Cloud Run. The course also teaches you how to integrate with other services on Google Cloud so you can build full-featured applications.

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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.

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In this course, you learn to analyze and choose the right database for your needs, to effectively develop applications on Google Cloud. You explore relational and NoSQL databases, dive into Cloud SQL, AlloyDB, and Spanner, and learn how to align database strengths with your application requirements, including those of generative AI. Gain hands-on experience configuring Vector Search and migrating applications to the cloud.

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This course will equip you with the tools to develop complex conversational experiences in Conversational Agents using best practices to create production-ready agents.

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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.

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This course will teach you how to build conversational experiences for Conversational Agents using Generative Playbooks. You'll start with an introduction to playbooks and learn how to set up your first one. You'll also learn about the importance of testing, as well as key production considerations like quota limits and integration. The course concludes with a case study that shows how to use playbooks for generative steering.

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Dieser On-Demand-Intensivkurs bietet Teilnehmenden eine Einführung in die umfangreiche und flexible Infrastruktur und die Plattformdienste von Google Cloud, mit Schwerpunkt auf der Compute Engine. In Videovorträgen, Demos und praxisorientierten Labs lernen die Teilnehmenden Lösungselemente kennen und stellen sie dann bereit. Dazu gehören Infrastrukturkomponenten wie Netzwerke, Systeme und Anwendungsdienste. Außerdem werden praktische Lösungen vorgestellt, beispielsweise für von Kundinnen und Kunden bereitgestellte Verschlüsselungsschlüssel, die Sicherheits- und Zugriffsverwaltung, Kontingente und Abrechnung sowie das Ressourcenmonitoring.

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This course aims to equip conversational designers and builders with the concepts and practical skills to design, build, and test sophisticated, multi-agent, and multimodal Customer Experience agents using Customer Experience Agent Studio (CX Agent Studio).

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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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This course explores the different products and capabilities of Gemini Enterprise for Customer Experience, including CX Agent Studio, Agent Assist and CX Insights. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.

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Complete the Extend agent functionality with Webhooks, Tools, and Integrations skill badge to demonstrate your ability to let conversational agents take actions. You will create a flow that calls a webhook and a playbook with a tool and combine them into a hybrid agent. You'll also prepare custom payload for rich content experiences in the Conversational Messenger. 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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The objective of this challenge lab is to demonstrate your proficiency configuring agents in CX Agent Studio. You create agents, sub-agents and tools and run conversations in the preview agent.

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Discover flows in Conversational Agents and learn how to build deterministic chat and voice experiences with language models. Explore key concepts like drivers, intents, and entities, and how to use them to create conversational agents.

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Connect conversational agents to external systems and APIs to expand what agents can do, designing an end-to-end system that is resilient, fault-tolerant and secure.

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