Goal & Aims

This Do-it-Yourself (DIY) course is designed to provide a basic grounding of the Internet of Things (IoT).

• The aim is to equip students with the Data Science skills in order to complete basic IoT-scenario's.
• Providing students with templates and a data-toolkit (code), which can be implemented through popular single board microcontrollers (Arduino / Raspberry Pi).
• Use of Generative AI [Gen-AI] such as Co-Pilot or ChatGPT is encouraged. It's important to make sure that other people are aware that these technologies were used. This can be done by including references or citations in the code or documentation, or by making a statement in the README file or other documentation that the project relies on these technologies. Additionally, it's also a good practice to include information about the limitations and potential biases of the technology in the documentation or code comments.

Required Hardware

See: https://github.com/robvdw/CMIDAT01K-DATA-SCIENCE-for-IOT/blob/master/Required_Hardware_2021.md

Scope

A hands-on introductory course exploring the Internet of Things form a (Human-Centered) Data Science point of view.

Creating your own IoT data pipeline

https://github.com/robvdw/CMIDAT01K-DATA-SCIENCE-for-IOT/blob/master/IoT-Pipelines/data_pipeline%20example01.png

Learning objectives

• Become familiar with Data Science concepts surrounding IoT applications
• Prepare a (Rapid) prototype for an Internet of Things (IoT) data-pipeline scenario's
• Learn to design and develop simple lightweight IoT-prototypes
• Learn to report on IoT projects (inclusive prototypes + data-pipelines).

This course teaches you the basics of electronics and GPIO interfacing with Python. You will build and experiment with simple electronic circuits that are controlled using Python, and combine this learning to build a simple yet complete internet-controllable IoT application with aid of Data Science concepts and IoT middle-ware such as Thingspeak and dweet.io.

Lessons

The content of each lesson will become available each week as a PDF document via:

https://github.com/robvdw/CMIDAT01K-DATA-SCIENCE-for-IOT/tree/master/Lessons

Locatie: Wijnhaven 103/105 lokaal:WD 00.034

START dinsdag 14 februari 2023

lesson	week OP3	content
Lesson 01	week 02	Discovering the IoT Data Science Domain
Lesson 02	week 04	Defining project requirements
Lesson 03	week 05	Learn to write code
Lesson 04	week 06	Data Science: How to start your own IoT Project
Lesson 05	week 07	IoT Platforms & MiddleWare
Lesson 06	week 08	Core IoT Concepts + setting-up your IoT-device
Lesson 07	week 09	Explaining Grading + Summary + Q & A
---------	week 08/09	Self study & Project Completion + een-op-een feedback op verzoek via Teams

Delivearbles & Deadline

• A working prototype that includes software (code), hardware and electronics elements.
• Code (commented) for the application
• Documentation of the project (contributed to a personal GitHub Repository).
• An online demo (video or IoT Platform implementation) of the completed IoT data-pipeline/project.

DEADLINE ===> week 10 OP03 (donderdag 01 februari 2024) collegejaar 2022-2023 <==== OPLEVERING VIA OPDRACHTEN in BRIGHTSPACE CMIDAT01K-2023-VT-OP2 zoals zal worden gecomuniceerd via E-mail en via BrightSpace

Grading

This course wil be graded according to the rules and defintions as oulined in:

https://github.com/robvdw/CMIDAT01K-DATA-SCIENCE-for-IOT/blob/master/Docs/BEOORDELINGS__DSforIoT_OP3_JAN_2024.pdf

Data Science Beyond the IoT

For those who want to keep up with novel delelopments within the Data Science domain see my Medium.com Blog: https://robfvdw.medium.com