Course Syllabus for

Machine Learning for Internet of Things (IoT)
Maskininlärning för sakernas internet (IoT)

EITP40F, 7.5 credits

Valid from: Autumn 2022
Decided by: Maria Sandsten
Date of establishment: 2022-10-10

General Information

Division: Electrical and Information Technology
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: EITP40
Teaching language: English


The purpose of the course is to provide an introduction to artificial intelligence and machine learning techniques for IoT systems e.g. wearable sensors for health monitoring.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must

Course Contents

Introduction to IoT systems and the challenges and opportunities in this domain Introduction and foundation of machine learning and deep neural networks in the context of IoT systems e.g. for wearable devices and sensors for health monitoring and medical informatics; Machine learning for IoT systems and distributed resource-constrained platforms.

Course Literature

Instruction Details

Types of instruction: Lectures, laboratory exercises, exercises, project

Examination Details

Examination format: Oral exam
Grading scale: Failed, pass

Admission Details

Assumed prior knowledge: Programming, Basic probability, statistics, and algebra.

Further Information

Course Coordinator: Amir Aminifar

Course Occasion Information

Contact and Other Information

Course coordinators:

Complete view