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MUKKARA SANGEETHA

Date d'abonnement : 2026

Ligue d'Or

3084 points
Create Your First Gemini Enterprise Application Earned août 14, 2026 EDT
Responsible AI for Developers: Fairness & Bias Earned juil. 23, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation Earned juil. 23, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI Earned juil. 23, 2026 EDT
AI Boost Bites: Presentation Scripts with Gemini Earned juil. 23, 2026 EDT
Prompt Design in Agent Platform Earned juil. 16, 2026 EDT
Gemini in Google Drive Earned juil. 15, 2026 EDT
Gemini in Google Chat Earned juil. 15, 2026 EDT
Gemini in Google Meet Earned juil. 15, 2026 EDT
Gemini in Google Sheets Earned juil. 15, 2026 EDT
Gemini in Google Slides Earned juil. 15, 2026 EDT
Deploy Your First Agent Earned juil. 15, 2026 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned juil. 15, 2026 EDT
[DEPRECATED]Introduction to Responsible AI Earned juil. 15, 2026 EDT
Build and Deploy Agents in Production Earned juil. 15, 2026 EDT
Introduction to Large Language Models Earned juil. 14, 2026 EDT
Introduction to Generative AI Earned juil. 14, 2026 EDT

Create your first Gemini Enterprise application to earn a skill badge! Connect diverse data sources to your application to build a powerful, unified search and analysis engine. Master advanced capabilities like deep research agents, multi-agent ideation, and Gemini Notebook for focused analysis. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.

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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production. Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Agent Platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.

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AI Boost Bites is a video series designed to help you leverage Google's AI tools in your daily work. Each episode, under 10 minutes, features a quick video demonstrating a real-world AI use case or topic. After the video, you'll get a challenge to apply what you've learned. It's an easy, interactive way to boost your AI skills and improve your productivity.

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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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This course covers how to use Gemini in Google Drive to manage and retrieve files. Learn to locate assets using natural language, extract specific facts via AI Overviews without opening files, instantly summarize multiple media formats, and save file collections as Projects for repeatable research. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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This course covers how to use Gemini in Google Chat to streamline business messaging. Learn to cut through notification noise with summaries, use natural language search to locate buried decisions, and refine message tone with real-time writing tools. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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This course covers how to use Gemini in Google Meet to enhance video collaboration. Learn to automate note-taking, utilize real-time text and speech translation, privately catch up on missed discussions, and instantly optimize your audio and video quality. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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This course covers how to use Gemini in Google Sheets to automate data organization and crunch complex numbers. Learn to structure tables from raw text, auto-populate data using natural language, generate native spreadsheet formulas on demand, and rapidly extract high-level insights or visualizations without needing advanced spreadsheet expertise. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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This course covers how to use Gemini in Google Slides to transform concepts into visually compelling presentations. Learn to generate structured decks from a single prompt or existing source document, refine slide layouts using automated design enhancement, create custom vector graphics and photos, and dynamically craft on-slide copy alongside precise speaker notes.

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Take your agents from localhost to production. This course teaches you to deploy ADK agents to Vertex AI Agent Engine and Cloud Run, with optional cross-session memory via Memory Bank. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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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 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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Explore the architecture and deployment of multi-agent systems using Google’s Agent Development Kit (ADK) and Google Cloud’s robust infrastructure. You will learn to design hierarchical agent trees and deterministic workflow agents while identifying the ideal hosting environment—from serverless Cloud Run to high-performance GKE—to ensure your AI agents are secure, scalable, and production-ready. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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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. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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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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