GCP Engineering and Streaming Architecture

Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level

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Overview/Description
Feature engineering can be an essential tool in applied machine learning when enhancing a dataset. In this course, you will learn about concepts of feature engineering, including areas of streaming architecture and implementations.

Target Audience
Data professionals who are responsible for provisioning and optimizing big data solutions, and data enthusiasts getting started with Google Cloud Platform

Prerequisites
None

Expected Duration (hours)
1.3

Lesson Objectives

GCP Engineering and Streaming Architecture

start the course

describe the concepts of feature engineering

recall the benefits of quality features with feature engineering and feature selection

describe the process of input selection in feature engineering

demonstrate feature engineering in use cases

recall the concepts of streaming data and real-time stream processing

describe Dataflow triggers and late data

install Java JDK on Windows 10

demonstrate how to install Apache Maven on Windows 10

install Google Cloud SDK and initialize SDK Shell on Windows 10

demonstrate the process of streaming pipelines using Dataflow SDK 2.x and Java in Cloud SDK Shell

demonstrate the process of streaming pipelines using Dataflow SDK 2.x and Python in Google Cloud Shell

describe feature engineering concepts and streaming data architecture

Course Number:
cl_gcde_a13_it_enus

Expertise Level
Intermediate