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Chitra Devi Rajendran

Date d'abonnement : 2024

Ligue de Diamant

15600 points
Orchestrate LLM solutions with LangChain Earned déc. 2, 2025 EST
Developing Applications with Cloud Run Functions on Google Cloud Earned déc. 1, 2025 EST
Orchestrating Gen AI Applications with LangChain Earned nov. 30, 2025 EST
Accelerate Knowledge Exchange with Gemini Enterprise Earned nov. 30, 2025 EST
Get Started with Dataplex Earned nov. 28, 2025 EST
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service Earned nov. 13, 2025 EST
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine Earned nov. 13, 2025 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning Earned mars 24, 2024 EDT
Text Prompt Engineering Techniques Earned mars 24, 2024 EDT
Search with AI Applications Earned mars 23, 2024 EDT
Introduction to Vertex AI Studio Earned mars 23, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned mars 23, 2024 EDT
Generative AI Explorer : Vertex AI Earned mars 23, 2024 EDT
Generative AI Fundamentals Earned mars 16, 2024 EDT
Introduction to Responsible AI Earned mars 14, 2024 EDT
Introduction to Large Language Models Earned mars 13, 2024 EDT
Introduction to Generative AI Earned mars 11, 2024 EDT

Learn to use LangChain to call Google Cloud LLMs and Generative AI Services and Datastores to simplify complex applications' code.

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In this course, you learn about Cloud Run functions, Google's serverless, fully-managed functions as a service (FaaS) product that lets you implement single-purpose function code that reponds to HTTP requests and events from your cloud infrastructure.

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This course equips full-stack mobile and web developers with the skills to integrate generative AI features into their applications using LangChain. You'll learn how to leverage LangChain’s capabilities for backend flows and seamless model execution, all within the familiar environment of Python. The course guides you through the entire process, from prototyping to production, ensuring a smooth journey in building next-generation AI-powered applications.

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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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Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.

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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.

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In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Vertex AI Agent Engine to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Engine. Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.

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(This course was previously named Multimodal Prompt Engineering with Gemini and PaLM) This course teaches how to use Vertex AI Studio, a Google Cloud console tool for rapidly prototyping and testing generative AI models. You learn to test sample prompts, design your own prompts, and customize foundation models to handle tasks that meet your application's needs. Whether you are looking for text, chat, code, image or speech generative experiences Vertex AI Studio offers you an interface to work with and APIs to integrate your production application.

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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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(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used) 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 AI Applications to integrate enterprise-grade generative AI search.

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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.

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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you. In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.

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This content is deprecated. Please see the latest version of the course, here.

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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.

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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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