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Dorin Damascan
Date d'abonnement : 2022
Ligue de Diamant
28345 points
Build Data Lakes and Data Warehouses on Google Cloud
Earned mars 4, 2025 EST
Introduction to Data Engineering on Google Cloud
Earned fév. 26, 2025 EST
Introduction to AI and Machine Learning on Google Cloud
Earned fév. 20, 2025 EST
Work with Gemini Models in BigQuery
Earned fév. 18, 2025 EST
Create ML Models with BigQuery ML
Earned fév. 17, 2025 EST
Build a Certification Study Guide: PMLE
Earned fév. 15, 2025 EST
Boost Productivity with Gemini in BigQuery
Earned fév. 15, 2025 EST
Manage Data Models in Looker
Earned fév. 15, 2025 EST
Derive Insights from BigQuery Data
Earned fév. 14, 2025 EST
BigQuery for Data Analysts
Earned fév. 12, 2025 EST
Google Cloud Data Analytics Essentials
Earned fév. 10, 2025 EST
Developing Data Models with LookML
Earned fév. 10, 2025 EST
Analyzing and Visualizing Data in Looker
Earned fév. 8, 2025 EST
Applying Advanced LookML Concepts in Looker
Earned fév. 6, 2025 EST
Understanding LookML in Looker
Earned fév. 5, 2025 EST
Prepare Data for Looker Dashboards and Reports
Earned fév. 4, 2025 EST
[Deprecated] Get Started with Looker
Earned fév. 4, 2025 EST
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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This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
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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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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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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.
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Complete the intermediate Manage Data Models in Looker skill badge course to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies.
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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Data Studio by connecting to BigQuery data.
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This course is designed for data analysts who want to learn about using BigQuery for their data analysis needs. Through a combination of videos, labs, and demos, we cover various topics that discuss how to ingest, transform, and query your data in BigQuery to derive insights that can help in business decision making.
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Discover how to turn raw numbers into clear, data-driven decisions on Google Cloud. Through hands-on labs and practical real-world scenarios, this beginner-level course guides you through querying data in BigQuery, exploring trends in Looker, and crafting shareable, interactive reports in Data Studio.
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This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.
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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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In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.
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In this course, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.
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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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