José Yobán Rodríguez González
Member since 2026
Gold League
6422 points
Introduction to Image Generation
Earned أغسطس 28, 2026 EDT
Create Image Captioning Models
Earned أغسطس 26, 2026 EDT
Introduction to Generative AI
Earned أغسطس 25, 2026 EDT
Introduction to Large Language Models
Earned أغسطس 25, 2026 EDT
Transformer Models and BERT Model
Earned أغسطس 24, 2026 EDT
Encoder-Decoder Architecture
Earned أغسطس 24, 2026 EDT
Attention Mechanism
Earned أغسطس 24, 2026 EDT
Liftoff with Google Antigravity: Build a Video Game with AI
Earned أغسطس 23, 2026 EDT
[DEPRECATED]Introduction to Responsible AI
Earned أغسطس 20, 2026 EDT
Model Armor: Securing AI Deployments
Earned أغسطس 18, 2026 EDT
Introduction to Security in the World of AI
Earned أغسطس 17, 2026 EDT
Responsible AI for Developers: Privacy & Safety
Earned أغسطس 17, 2026 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned أغسطس 17, 2026 EDT
Responsible AI for Developers: Fairness & Bias
Earned أغسطس 17, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation
Earned أغسطس 17, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned أغسطس 17, 2026 EDT
Add Agent Capabilities With Tools
Earned أغسطس 14, 2026 EDT
Manage Agent Memory and State
Earned أغسطس 14, 2026 EDT
Optimize Agent Behavior
Earned أغسطس 13, 2026 EDT
Engineer AI Agents with Agent Development Kit (ADK)
Earned أغسطس 13, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK)
Earned أغسطس 13, 2026 EDT
Gen AI Agents: Transform Your Organization
Earned أغسطس 13, 2026 EDT
Orchestrate Multi-agent Workflows with Gemini Enterprise
Earned أغسطس 13, 2026 EDT
Human-Centered AI
Earned أغسطس 13, 2026 EDT
Create Your First Gemini Enterprise Application
Earned أغسطس 13, 2026 EDT
Enterprise Agents and Use Cases
Earned أغسطس 13, 2026 EDT
Agent Fundamentals
Earned أغسطس 13, 2026 EDT
Introduction to AI Agents
Earned أغسطس 13, 2026 EDT
This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Gemini Enterprise Agent Platform.
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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images
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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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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 course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
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In this course, you'll learn to build software at a propulsive speed by orchestrating agents in Google Antigravity. This hands-on course will first guide you to install and get started with Antigravity by making a Hello, World(s)! app. Next, you'll use Firebase to deploy that app. Finally, you'll build a video game, Voyager, by orchestrating agents in Antigravity to work in parallel.
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 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 course reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI applications. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.
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This course introduces important topics of AI privacy and safety. It explores practical methods and tools to implement AI privacy and safety recommended practices through the use of Google Cloud products and open-source tools.
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This course introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
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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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You’ve built agents with advanced configuration—now give them real-world capabilities. Equip agents with tools that enable searching the web, executing code, querying databases, and performing custom actions. Transform agents from intelligent responders into capable assistants that take action. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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You've built basic LLM agents that respond to queries—now let's make them stateful. Use session state to build agents that maintain context, remember user preferences, and provide personalized experiences. Transform agents from stateless responders to intelligent assistants.Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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You’ve built your first agent—now it’s time to take it further. In this course, you’ll advance your skills by learning how to turn a basic AI agent into a sophisticated, precise assistant—applying advanced instructions, model selection, planning capabilities, and structured output patterns.
Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
Join the community forum for questions and discussions
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Complete the intermediate Engineer AI Agents with Agent Development Kit (ADK) skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK).
In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior, taking what you learned in course 1 and applying it to working code.
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 Enterprise Agent Ready (GEAR) program.
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Complete the introductory Orchestrate Multi-Agent Workflows with Gemini Enterprise skill badge to demonstrate skills in the following: using agentic assistants powered by Gemini Enterprise to unify data across first- and third-party sources, develop multimedia marketing materials, and automate business actions across systems.
Skill badges validate your practical knowledge on specific products through hands-on labs and challenge assessments. Earn a badge by completing a course or jump straight into the challenge lab to get your badge today. Badges prove your proficiency, enhance your professional profile, and ultimately lead to increased career opportunities. Visit your profile to track badges you’ve earned.
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Explore the vital transition from task-driven workflows to human-centric AI orchestration. You will learn to strategically distinguish between augmentation and automation, and how to balance machine efficiency with human intuition.
Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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.
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Discover how AI agents drive business impact. You’ll map agent types to your KPIs and explore use cases that solve real bottlenecks. Then, learn how Gemini Enterprise empowers you to build and orchestrate the right agents—from no-code to high-code solutions. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This course introduces the fundamentals of AI agents and explores where agents add value in the real world. It provides a foundation for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior.
Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.
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