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Jacob GOOGLEUSER

Member since 2025

Diamond League

6909 points
Responsible AI for Developers: Fairness & Bias Earned يوليو 1, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation Earned يونيو 27, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI Earned يونيو 27, 2026 EDT
Prompt Design in Agent Platform Earned يونيو 27, 2026 EDT
Gen AI Agents: Transform Your Organization Earned أبريل 1, 2026 EDT
Gen AI Apps: Transform Your Work Earned أبريل 1, 2026 EDT
Gen AI: Navigate the Landscape Earned مارس 31, 2026 EDT
Gen AI: Unlock Foundational Concepts Earned مارس 30, 2026 EDT
Gen AI: Beyond the Chatbot Earned مارس 30, 2026 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned مارس 30, 2026 EDT
AI Boost Bites: Create Your Own Retro Arcade Game Earned فبراير 1, 2026 EST
Introduction to Large Language Models Earned سبتمبر 8, 2025 EDT
[DEPRECATED]Introduction to Responsible AI Earned سبتمبر 8, 2025 EDT
Introduction to Generative AI Earned سبتمبر 6, 2025 EDT
[DEPRECATED] Google Sheets Earned سبتمبر 6, 2025 EDT

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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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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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools. Explore other content in the Gemini Agent Ready (GEAR) program.

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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and Gemini Notebook. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.

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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.

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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 video covers how to use a simple prompt in Gemini Canvas to build, customize, and share your own playable game, like Tic-Tac-Toe.

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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 Agent Ready (GEAR) program.

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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 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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In this course we will introduce you to Google Sheets, Google’s cloud-based spreadsheet software, included with Google Workspace. With Google Sheets, you can create and edit spreadsheets directly in your web browser—no special software is required. Multiple people can work simultaneously, you can see people’s changes as they make them, and every change is saved automatically. You will learn how to open Google Sheets, create a blank spreadsheet, and create a spreadsheet from a template. You will add, import, sort, filter and format your data using Google Sheets and learn how to work across different file types. Formulas and functions allow you to make quick calculations and better use your data. We will look at creating a basic formula, using functions, and referencing data. You will also learn how to add a chart to your spreadsheet. Google Sheets spreadsheets are easy to share. We will look at the different ways you can share with others. We will also discuss how to track changes…

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