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Akshita Sood

Member since 2026

Diamond League

9634 points
Build generative virtual agents with API integrations Earned יונ 7, 2026 EDT
Build deterministic Virtual Agent enhanced with data stores Earned יונ 4, 2026 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation Earned יונ 2, 2026 EDT
Getting Started with Google Kubernetes Engine Earned מאי 29, 2026 EDT
Incorporate Generative Features into Conversational Agent Flows Earned מאי 28, 2026 EDT
Developing Applications with Cloud Run on Google Cloud: Fundamentals Earned מאי 28, 2026 EDT
Text Prompt Engineering Techniques Earned מאי 25, 2026 EDT
Select a Google Cloud Database for Your Applications Earned מאי 25, 2026 EDT
Build Production-Ready Conversational Agents Earned מאי 24, 2026 EDT
Google Cloud: Prompt Engineering Guide Earned מאי 23, 2026 EDT
Create Agents with Generative Playbooks Earned מאי 21, 2026 EDT
Essential Google Cloud Infrastructure: Core Services Earned מאי 11, 2026 EDT
Customer Experience Agent Studio: Fundamentals Earned מאי 10, 2026 EDT
Conversational AI Voice and Chat Integrations Earned מאי 10, 2026 EDT
Introduction to Gemini Enterprise for Customer Experience Earned מאי 7, 2026 EDT
Extend virtual agents with webhooks, tools, and Messenger integration Earned מאי 7, 2026 EDT
Build agents with CX Agent Studio Earned מאי 7, 2026 EDT
Create Conversational Agents with Stateful Flows Earned מאי 4, 2026 EDT
Extend Conversational Agents Functionality with Webhooks and Tools Earned מאי 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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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.

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Welcome to the Getting Started with Google Kubernetes Engine course. If you're interested in Kubernetes, a software layer that sits between your applications and your hardware infrastructure, then you’re in the right place! Google Kubernetes Engine brings you Kubernetes as a managed service on Google Cloud. The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, as it’s commonly referred to, and how to get applications containerized and running in Google Cloud. The course starts with a basic introduction to Google Cloud, and is then followed by an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.

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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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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.

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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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