#dataengineeringongcp

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Data Engineering on GCP | Google Cloud Data Engineer | GKCS

Course Description

This four-day instructor-led class provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The Data Engineering on GCP course covers structured, unstructured, and streaming data.

Objectives

This Google Cloud Data Engineer course teaches participants the following skills:

Design and build     data processing systems on Google Cloud Platform

Process batch and     streaming data by implementing autoscaling data pipelines on Cloud     Dataflow

Derive business     insights from extremely large

datasets using     Google BigQuery

Train, evaluate     and predict using machine learning models using Tensorflow and Cloud ML

Leverage     unstructured data using Spark and ML APIs on Cloud Dataproc

Enable instant     insights from streaming data

Audience

This class is intended for the following:

Extracting, loading, transforming, cleaning,     and validating data

Designing pipelines and architectures for data     processing

Creating and maintaining machine learning and     statistical models

Querying datasets, visualizing query results     and creating reports

Prerequisites

To get the most of out of this course, participants should have:

Completed Google     Cloud Fundamentals- Big Data and Machine Learning course #8325 OR have     equivalent experience

Basic proficiency     with common query language such as SQL

Experience with     data modeling, extract, transform, load activities

Developing     applications using a common programming language such Python

Familiarity with  �� Machine Learning and/or statistics

Content

The course includes presentations,     demonstrations, and hands-on labs.

Leveraging Unstructured Data with Cloud     Dataproc on Google Cloud Platform

Module 1: Google Cloud Dataproc Overview

Module 2: Running Dataproc Jobs

Module 3: Integrating Dataproc with Google Cloud Platform

Module 4: Making Sense of Unstructured Data with Google’s Machine Learning APIs

Module 5: Serverless data analysis with BigQuery

Module 6: Serverless, autoscaling data pipelines with Dataflow

Module 7: Getting started with Machine Learning

Module 8: Building ML models with Tensorflow

Module 9: Scaling ML models with CloudML

Module 10: Feature Engineering

Module 11: Architecture of streaming analytics pipelines

Module 12: Ingesting Variable Volumes

Module 13: Implementing streaming pipelines

Module 14: Streaming analytics and dashboards

Module 15: High throughput and low-latency with Bigtable

For more IT Training on Google Cloud Courses visit GK Cloud Solutions.

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