Data Engineer: Google Cloud Certified - Professional Data Engineer

  • 15 Courses | 14h 58m 20s
  • 2 Books | 17h 38m
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Acquire knowledge of building and maintaining data processing systems, and data analysis as you prepare for the Data Engineer certification.

GETTING STARTED

Platform Fundamentals

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    1. 
    Google Cloud Platform Concepts
    3m 50s
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  • Playable
    2. 
    Navigating Google Cloud Platform Services
    4m 38s
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COURSES INCLUDED

Platform Fundamentals
Google Cloud Platform offers several solutions to streamline any enterprise while keeping costs low. Explore these benefits, including how to navigate GCP and choose between the various data processing products it provides.
9 videos | 47m
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Storage & Analytics
Google Cloud Platform (GCP) offers several services for analytics and storage. Explore the storage, compute, and analytics concepts and how they are tied together.
13 videos | 1h 13m
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Deeper through GCP Analytics & Scaling
The big data industry is getting bigger, and GCP has several management tools designed for common use cases. Explore common concepts and use cases, including analytics tools and operations.
10 videos | 43m
has Assessment available Badge
GCP Network Data Processing Models
You can create and manage an assortment of data processes and network models using GCP. Explore the various types, including using a GPU and TensorFlow to create and manage GPU and instances.
10 videos | 40m
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Dataproc
GCP provides fully managed cloud services for running Apache Spark and Hadoop. Explore the concepts of cluster management with Dataproc, including machine types and workers.
10 videos | 40m
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Dataproc Architecture
Dataproc can be used to perform several operations when integrating platforms, including Pig and Hive. Explore Dataproc architecture while introducing the use of Pig and Hive.
10 videos | 44m
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Dataproc Operations
Executing Dataproc implementations with big data can provide a variety of methods. Examine Dataproc implementations with Spark and Hadoop using the cloud shell and introduce BigQuery PySpark REPL package.
10 videos | 56m
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Implementations with BigQuery for Big Data
You can query big data using the BigQuery tool in the Google Cloud Platform. Discover the concepts of using BigQuery, including querying data and using the Google API.
11 videos | 1h 11m
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Fundamentals of Big Query
BigQuery is an essential tool for any data analyst using Google Cloud Platform. Explore BigQuery and examine several operations including multiple table queries, nested and repeated fields and building BigQueries.
10 videos | 1h 13m
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APIs & Machine Learning
Machine learning and ML APIs are part of the Cloud ML engine. Explore the various ML APIs and how to implement an app that uses the Vision API.
9 videos | 1h 3m
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Dataflow Autoscaling Pipelines
Apache Beam, Cloud Dataflow, and Cloud Dataprep can be used to create data pipelines. Explore how areas of Beam, Apache Beam SDK, Cloud Dataflow, and Cloud Dataprep assist in pipeline management.
10 videos | 42m
has Assessment available Badge
Machine Learning with TensorFlow & Cloud ML
Cloud ML combines the Google Cloud Platform with TensorFlow to create models at scale. Explore concepts behind TensorFlow and scaling, as well as training models locally and in the cloud.
14 videos | 1h 26m
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