Job Nunes
Date d'abonnement : 2022
Ligue d'Or
8292 points
Develop Serverless Applications on Cloud Run
Earned juin 15, 2026 EDT
Engineer AI Agents with Agent Development Kit (ADK)
Earned juin 13, 2026 EDT
Implement Cloud Security Fundamentals on Google Cloud
Earned juin 12, 2026 EDT
Set Up an App Dev Environment on Google Cloud
Earned juin 9, 2026 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned juin 7, 2026 EDT
Networking in Google Cloud: Fundamentals
Earned mai 23, 2026 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned mai 21, 2026 EDT
Essential Google Cloud Infrastructure: Core Services
Earned mai 21, 2026 EDT
Google Cloud Fundamentals: Core Infrastructure
Earned mai 10, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK)
Earned mai 2, 2026 EDT
Build Agents with Agent Development Kit (ADK)
Earned mai 1, 2026 EDT
Build Google Cloud Infrastructure for AWS Professionals
Earned mai 1, 2026 EDT
Build a Data Warehouse with BigQuery
Earned avr. 12, 2026 EDT
Build Streaming Data Pipelines on Google Cloud
Earned mars 8, 2026 EDT
Build Batch Data Pipelines on Google Cloud
Earned mars 7, 2026 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned jan. 15, 2026 EST
Introduction to Data Engineering on Google Cloud
Earned jan. 15, 2026 EST
Build a Certification Study Guide: PDE Exam Prep
Earned jan. 7, 2026 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Earned jan. 6, 2023 EST
Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.
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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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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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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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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.
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Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals.
This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharing of VPC networks. Additionally, the course covers network logging and monitoring techniques.
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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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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
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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 Agent Ready (GEAR) program.
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Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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Earn a skill badge by completing the Build Google Cloud Infrastructure for AWS Professionals course, where you learn how to configure IAM permission, orchestrate workloads using Kubernetes, host a web application using compute engine, and configure load balancing.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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This course, Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Cloud Computing Fundamentals .The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
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