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Reza Siahaan

Jest członkiem od 2020

Liga brązowa

3079 pkt.
Build a Certification Study Guide: PMLE Earned lis 20, 2025 EST
Analyzing and Visualizing Data in Looker Earned lip 10, 2024 EDT
Podstawy: dane, uczenie maszynowe, AI Earned wrz 20, 2020 EDT
Kubernetes in Google Cloud Earned wrz 1, 2020 EDT
Machine Learning APIs Earned sie 19, 2020 EDT
Data Catalog Fundamentals Earned sie 15, 2020 EDT
DEPRECATED BigQuery for Marketing Analysts Earned sie 13, 2020 EDT

Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.

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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

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Big data, uczenie maszynowe i sztuczna inteligencja to najpopularniejsze tematy współczesnej informatyki, jednak to dość wyspecjalizowane dziedziny i trudno znaleźć materiały wprowadzające do nich. Na szczęście Google Cloud udostępnia przyjazne dla użytkownika usługi w tych obszarach, a dzięki temu kursowi dla początkujących możesz poznać podstawy narzędzi takich jak BigQuery, Cloud Speech API i Video Intelligence.

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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.

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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? Enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.

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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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