Master
2021/2022
Industrial IoT on Google Cloud Platform
Type:
Elective course (Internet of Things and Cyber-physical Systems)
Area of studies:
Infocommunication Technologies and Systems
Delivered by:
School of Electronic Engineering
When:
2 year, 2 module
Mode of studies:
distance learning
Open to:
students of all HSE University campuses
Instructors:
Ilya Ivanov
Master’s programme:
Internet of Things and Cyber-physical Systems
Language:
English
ECTS credits:
3
Contact hours:
2
Course Syllabus
Abstract
Industrial IoT on Google Cloud Platform https://www.coursera.org/learn/iiot-google-cloud-platform Welcome to the Coursera course, Industrial Internet of Things (IoT) on Google Cloud Platform (GCP) brought to you by the Google Cloud team. I’m Catherine Gamboa and I’m going to be your guide. This course covers the entire Industrial IoT network architecture from sensors and devices to analysis. The course discusses sensors and devices but the focus is on the cloud side. You'll learn about the importance of scaling, device communication, and processing streaming data. The course uses simulated devices in the labs to allow you to concentrate on learning the cloud side of IIoT. The course is a little different than most Coursera courses because there is very little video. Most of the learning is done with short readings, quizzes, and labs. This course takes about two weeks to complete, 11-12 hours of work with 6 of those hours spent in labs.You'll learn and practice these skills in 7 labs. Then you'll have an opportunity to test yourself in an optional capstone lab using simulated devices or Cloud IoT Core Inspector.
Learning Objectives
- By the end of this course, you’ll be able to: create a streaming data pipeline, to create registries with Cloud IoT Core, topics and subscriptions with Cloud Pub/Sub, store data on Google Cloud Storage, query the data in BigQuery, and gain data insights with Dataprep.
Expected Learning Outcomes
- 1. Welcome to Industrial IoT on GCP
- 2. Foundations of GCP Architecture
- 3. Sensors, Devices, and Communication
- 4. Google Cloud IoT Platform
- 5. Creating IoT Data Pipelines
- 6. Analyzing Data with BigQuery
- 7. Analyzing IoT Dataprep and Data Studio
Course Contents
- 1. Welcome to Industrial IoT on GCP
- 2. Foundations of GCP Architecture
- 3. Sensors, Devices, and Communication
- 4. Google Cloud IoT Platform
- 5. Creating IoT Data Pipelines
- 6. Analyzing Data with BigQuery
- 7. Analyzing IoT Dataprep and Data Studio
Assessment Elements
- Самостоятельная работаThe results of the final testing must be provided no later than the start time of the exam in accordance with the schedule of the session. Lecture notes and presentations of practical exercises must be submitted no later than a week (7 calendar days) before the start of the exam in accordance with the session schedule. If the results of the final testing, lecture notes and presentation of practical exercises are not provided within the specified time, the final grade may be reduced by 1 point or more.
- Exam (Экзамен)The results of the final testing must be provided no later than the start time of the exam in accordance with the schedule of the session. Lecture notes and presentations of practical exercises must be submitted no later than a week (7 calendar days) before the start of the exam in accordance with the session schedule. If the results of the final testing, lecture notes and presentation of practical exercises are not provided within the specified time, the final grade may be reduced by 1 point or more.
Bibliography
Recommended Core Bibliography
- Cloud Standards Customer Council. (12 C.E., May 2017). Cloud Standards Customer Council Announces Version 3.0 of Practical Guide to Cloud Computing. Business Wire (English).
- Dive, P., & Gornalli, N. (2018). DevOps for Salesforce : Build, Test, and Streamline Data Pipelines to Simplify Development in Salesforce. Birmingham: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1905961
- Fraden, J. (2016). Handbook of Modern Sensors : Physics, Designs, and Applications (Vol. Fifth edition). Cham: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1081958
- Риз Дж. Облачные вычисления (Cloud Application Architectures). - Санкт-Петербург : БХВ-Петербург, 2011. - 288 с. - ISBN 978-5-9775-0630-4. - URL: https://ibooks.ru/bookshelf/26340/reading (дата обращения: 12.10.2020). - Текст: электронный.
Recommended Additional Bibliography
- Nihtianov, S., & Luque, A. (2018). Smart Sensors and MEMS : Intelligent Sensing Devices and Microsystems for Industrial Applications: Vol. Second edition. Woodhead Publishing.