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Google Cloud Big Data & Machine Learning Fundamentals
This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform.
Course Description
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
Objectives
This course teaches participants the following skills:
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Recognize the data-to-AI lifecycle on Google Cloud and the major products of big data and machine learning.
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Design streaming pipelines with Dataflow and Pub/Sub.
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Analyze big data at scale with BigQuery.
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Identify different options to build machine learning solutions on Google Cloud.
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Describe a machine learning workflow and the key steps with Vertex AI.
- Build a machine learning pipeline using AutoML.
Audience
This class is intended for the following:
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Data analysts, Data scientists, Business analysts getting started with Google Cloud Platform.
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Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results and creating reports.
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Executives and IT decision makers evaluating Google Cloud Platform for use by data scientists.
Prerequisites
To get the most of out of this course, participants should have roughly one year of experience with one or more of the following:
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Database query language such as SQL
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Data engineering workflow from extract, transform, load, to analysis, modeling, and deployment
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Machine learning models such as supervised versus unsupervised models
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Machine learning and/or statistics
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Programming in Python.
Duration
One day
Delivery Method
Instructor-led, Instructor-led online
What to bring
For this class, please bring:
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Laptop (Windows, Mac OS or Linux)