Andres Sanchez
Member since 2024
Deploy Multi-Agent Architectures
Earned авг. 30, 2026 EDT
Implement Cloud Security Fundamentals on Google Cloud
Earned авг. 24, 2026 EDT
Vertex AI Search for Commerce
Earned авг. 18, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation
Earned авг. 18, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned авг. 18, 2026 EDT
Serverless Data Processing with Dataflow: Foundations
Earned авг. 8, 2026 EDT
Prompt Design in Agent Platform
Earned авг. 5, 2026 EDT
Introduction to Large Language Models
Earned авг. 5, 2026 EDT
Introduction to Generative AI
Earned авг. 5, 2026 EDT
[DEPRECATED] The Skills Challenge at Next 2025
Earned апр. 14, 2025 EDT
Data Insights Quiz: Analyze my data to gain insights
Earned апр. 11, 2025 EDT
Scalability Quiz: Make my application scalable and reliable
Earned апр. 11, 2025 EDT
Develop Your Google Cloud Network
Earned авг. 2, 2024 EDT
Optimize Costs for Google Kubernetes Engine
Earned июля 9, 2024 EDT
Build Infrastructure with Terraform on Google Cloud
Earned июня 26, 2024 EDT
Set Up an App Dev Environment on Google Cloud
Earned июня 16, 2024 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned июня 7, 2024 EDT
Cloud Hero: Core Infrastructure I
Earned апр. 10, 2024 EDT
Complete the advanced Deploy Multi-Agent Architectures skill badge to demonstrate skills in the following: building multi-agent systems with ADK, connecting agents with the Agent-to-Agent (A2A) protocol, integrating external tools using the Model Context Protocol (MCP), and deploying a complete multi-agent solution to Agent Engine. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.
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This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.
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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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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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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 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 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 Course is utilized to certify completion of The Skills Challenge at Next 2025.
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Extract valuable insights from your data with Google's scalable analytics tools for processing, warehousing, and visualizing information.
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Ensure your application can handle fluctuating traffic and remain available with Google''s robust infrastructure and auto-scaling features.
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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.
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Complete the intermediate Optimize Costs for Google Kubernetes Engine skill badge course to demonstrate skills in the following: creating and managing multi-tenant clusters, monitoring resource usage by namespace, configuring cluster and pod autoscaling for efficiency, setting up load balancing for optimal resource distribution, and implementing liveness and readiness probes to ensure application health and cost-effectiveness.
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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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Cloud Hero is played around the world, in person and online. Today, you have the opportunity to become one of the Cloud Heroes! Today's game is all about Core Infrastructure basics. You will compete to see who can finish the game with the most points. Speed is important, and so is accuracy! Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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