Thời gian:
9:00am - 5:00 pm
Lịch học:
25.03.2022
Học phí:
FREE
01
Introducing Google Cloud
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Identify the different aspects of Google Cloud’s infrastructure.
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Identify the big data and ML products that form Google Cloud.
02
Recommending Products Using Cloud SQL and Spark
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Review how businesses use recommendation models.
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Evaluate how and where you will compute and store your housing rental model results.
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Analyze how running Hadoop in the cloud with Dataproc can enable scale.
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Evaluate different approaches for storing recommendation data off-cluster.
03
Predicting Visitor Purchases Using BigQuery ML
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Analyze big data at scale with BigQuery. Identify the purpose of and use cases for Google Compute Engine.
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Learn how BigQuery processes queries and stores data at scale.
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Walkthrough key ML terms: features, labels, training data.
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Evaluate the different types of models for structured datasets.
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Create custom ML models with BigQuery ML.
04
Real-time Dashboards with Pub/Sub, Dataflow, and Google Data Studio
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Identify modern data pipeline challenges and how to solve them at scale with Dataflow.
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Design streaming pipelines with Apache Beam.
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Build collaborative real-time dashboards with Data Studio.
05
Deriving Insights from Unstructured Data Using Machine Learning
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Evaluate how businesses use unstructured ML models and how the models work.
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Choose the right approach for machine learning models between pre-built and custom.
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Create a high-performing custom image classification model with no code using AutoML.
06
Summary
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Recap of key learning points.
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Contrast the App Engine standard environment with the App Engine flexible environment.
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Resources.
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