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Hands-on Foundations for Data Science and Machine Learning Google Cloud Labs

In this Google Cloud Labs Specialization, you'll receive hands-on experience building and practicing skills in BigQuery and Cloud Data Fusion. You will start learning the basics of BigQuery, building and optimizing warehouses, and then get hands-on practice on the more advanced data integration features available in Cloud Data Fusion. Learning will take place leveraging Google Cloud's Qwiklab platform where you will have the virtual environment and resources need to complete each lab. This specialization is broken up into 4 courses comprised of a series of courses: BigQuery Basics for Data Analysts Build and Optimize Data Warehouses with BigQuery Building Advanced Codeless Pipelines on Cloud Data Fusion Data Science on Google Cloud: Machine Learning You will even be able to earn a Skills Badge in one of these lab-based courses.

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What's inside

Four courses

Data Science on Google Cloud: Machine Learning

(0 hours)

Activities in these self-paced labs are derived from exercises in the book Data Science on Google Cloud Platform. Run machine learning jobs with Google Cloud tools and services.

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Build and Optimize Data Warehouses with BigQuery

(0 hours)

In this Google Cloud Labs Series, learn how to use BigQuery to transform your data warehouse. You'll learn how to query and load data, create reporting tables, create dataset partitions, create and troubleshoot joins, load and query semi-structured datasets, and use Data Catalog.

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BigQuery Basics for Data Analysts

(0 hours)

Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive collection of BigQuery Google Cloud Labs Series.

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Building Advanced Codeless Pipelines on Cloud Data Fusion

(0 hours)

In this Google Cloud Labs Series, learners get hands-on practice on the more advanced data integration features available in Cloud Data Fusion, while sharing best practices to build more robust, reusable, dynamic pipelines.

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Time

25 hours

Via

Coursera

Institution

Google Cloud

Instructor

Google Cloud Training

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