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Muhammad Risky Pahlevi

Member since 2024

Gold League

18880 points
Google Cloud Fundamentals: Core Infrastructure Earned Jun 13, 2025 EDT
Intro to ML: Language Processing Earned Sep 7, 2024 EDT
Build LookML Objects in Looker Earned Sep 7, 2024 EDT
Create ML Models with BigQuery ML Earned Sep 7, 2024 EDT
Perform Predictive Data Analysis in BigQuery Earned Sep 7, 2024 EDT
Analyze Images with the Cloud Vision API Earned Sep 5, 2024 EDT
Gemini for Data Scientists and Analysts Earned Sep 4, 2024 EDT
Integrating Applications with Gemini 1.0 Pro on Google Cloud Earned Sep 4, 2024 EDT
Analyze Sentiment with Natural Language API Earned Sep 3, 2024 EDT
Gemini for Application Developers Earned Sep 3, 2024 EDT
Build Infrastructure with Terraform on Google Cloud Earned Sep 2, 2024 EDT
Analyze Speech and Language with Google APIs Earned Sep 1, 2024 EDT
Manage Kubernetes in Google Cloud Earned Aug 30, 2024 EDT
Monitor and Manage Google Cloud Resources Earned Aug 29, 2024 EDT
Create and Manage Cloud SQL for PostgreSQL Instances Earned Aug 28, 2024 EDT
Generative AI Explorer - Vertex AI Earned Aug 24, 2024 EDT
Create and Manage AlloyDB Instances Earned Aug 21, 2024 EDT

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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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory course, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.

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Complete the introductory Build LookML Objects in Looker skill badge course to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.

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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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Earn the intermediate skill badge by completing the Perform Predictive Data Analysis in BigQuery course, where you will gain practical experience on the fundamentals of sports data science using BigQuery, including how to create a soccer dataset in BigQuery by importing CSV and JSON files; harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data, and evaluate the impressiveness of World Cup goals.

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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows. Duet AI was renamed to Gemini, our next-generation model.

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This short course on integrating applications with Gemini 1.0 Pro models on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 1.0 Pro and Gemini 1.0 Pro Vision models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.

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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow. Duet AI was renamed to Gemini, our next-generation model.

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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 Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.

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Complete the intermediate Manage Kubernetes in Google Cloud skill badge to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

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This challenge lab tests your skills and knowledge from the labs in the Monitor and Manage Google Cloud Resources quest. You should be familiar with the content of labs before attempting this lab.

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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.

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The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.

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Complete the introductory Create and Manage AlloyDB Instances skill badge to demonstrate skills in the following: performing core AlloyDB operations and tasks, migrating to AlloyDB from PostgreSQL, administering an AlloyDB database, and accelerating analytical queries using the AlloyDB Columnar Engine.

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