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Fitria Nur Aida

Member since 2025

Gold League

1941 points
Enhance Gemini Model Capabilities Earned февр. 15, 2026 EST
Implement Cloud Security Fundamentals on Google Cloud Earned февр. 15, 2026 EST
Develop Serverless Applications on Cloud Run Earned февр. 15, 2026 EST
Prompt Design in Vertex AI Earned февр. 14, 2026 EST
Monitor and Log with Google Cloud Observability Earned февр. 10, 2026 EST
Monitoring in Google Cloud Earned февр. 9, 2026 EST
Build Serverless Applications with Cloud Run Functions Earned февр. 9, 2026 EST
Build Real World AI Applications with Gemini and Imagen Earned февр. 8, 2026 EST
Configure Service Accounts and IAM Roles for Google Cloud Earned февр. 6, 2026 EST
Build AI Agents with Enterprise Databases Earned февр. 5, 2026 EST
Prepare Data for ML APIs on Google Cloud Earned февр. 4, 2026 EST
Engineer Data for Predictive Modeling with BigQuery ML Earned янв. 30, 2026 EST
Use Machine Learning APIs on Google Cloud Earned янв. 28, 2026 EST
Use APIs to Work with Cloud Storage Earned янв. 26, 2026 EST
Implement Multimodal Vector Search with BigQuery Earned янв. 25, 2026 EST
The Basics of Google Cloud Compute Earned янв. 23, 2026 EST
Perform Predictive Data Analysis in BigQuery Earned янв. 21, 2026 EST
Create ML Models with BigQuery ML Earned янв. 20, 2026 EST

Complete the intermediate Enhance Gemini Model Capabilities skill badge to demonstrate skills in the following: leveraging advanced features of Gemini models, including code generation and execution, grounding, controlled content generation, and synthetic data creation, to build more powerful and sophisticated AI applications.

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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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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 introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.

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Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.

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Complete the introductory Monitoring in Google Cloud skill badge course to demonstrate skills in the following: using Cloud Monitoring tools to monitor resources on Google Cloud.

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Earn a Introductory skill badge by completing the Build Serverless Applications with Cloud Run Functions course, where you learn how to use Cloud Run functions through the Google Cloud console and on the command line.

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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Vertex AI platform.

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Earn the Introductory skill badge by completing the Configure Service Accounts and IAM Roles for Google Cloud course, where you learn about service accounts, custom roles, and how to set permissions using gcloud .

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Build AI agents that can leverage enterprise databases using the MCP Toolbox for Databases. You will define secure database interaction tools, and implement intelligent querying capabilities (leveraging vector embeddings, structured queries).

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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.

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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.

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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.

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Complete the introductory Use APIs to Work with Cloud Storage skill badge to demonstrate skills in the following: using APIs to work with Cloud Storage resources, including the Cloud Storage API.

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Complete the intermediate Implement Multimodal Vector Search with BigQuery skill badge to demonstrate skills in the following: using Gemini in BigQuery to generate and debug SQL, conduct sentiment analysis, summarize text and identify keywords, generate embeddings, create a Retrieval Augmented Generation (RAG) pipeline, and implement multimodal vector search.

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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.

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Complete the intermediate Perform Predictive Data Analysis in BigQuery skill badge course to demonstrate skills in the following: creating datasets in BigQuery by importing CSV and JSON files; harnessing the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on soccer event data and evaluate the impressiveness of World Cup goals.

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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.

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