Course details

Data Sources: Implementing Edge on the Cloud

Data Sources: Implementing Edge on the Cloud


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

To become proficient in data science, users have to understand edge computing. This is where data is processed near the source or at the edge of the network while in a typical cloud environment, data processing happens in a centralized data storage location. In this 7-video course, learners will explore the implementation of IoT (Internet of Things) on prominent cloud platforms like AWS (Amazon Web Services) and GCP (Google Cloud Platform). Discover how to work with IoT Device Simulator and generate data streams with MQTT (Message Queuing Telemetry Transport). You will next examine the approaches and steps involved in setting up AWS IoT Greengrass, and the essential components of GCP IoT Edge. Then learn how to connect a web application to AWS IoT by using MQTT over WebSockets. The next tutorial demonstrates the essential approach of using IoT Device Simulator, then on to generating streams of data by using the MQTT messaging protocol. The concluding exercise involves creating a device type, a user, and a device by using IoT Device Simulator.



Expected Duration (hours)
0.5

Lesson Objectives

Data Sources: Implementing Edge on the Cloud

  • Course Overview
  • identify the approaches and the steps involved in setting up AWS IoT Greengrass
  • recognize the essential components of GCP IoT Edge
  • connect a web application to AWS IoT using MQTT over WebSockets
  • demonstrate the essential approaches of using IoT Device Simulator
  • generate streams of weather data using the MQTT messaging protocol
  • create a device type, a user, and a device using IoT Device Simulator
  • Course Number:
    it_dsidsedj_02_enus

    Expertise Level
    Intermediate