Course syllabus

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

EITP40, 7.5 credits, A (Second Cycle)

Valid for: 2024/25
Faculty: Faculty of Engineering LTH
Decided by: PLED C/D
Date of Decision: 2024-04-16
Effective: 2024-05-08

General Information

Depth of study relative to the degree requirements: Second cycle, in-depth level of the course cannot be classified
Elective for: C4-ks, D4-is, D4-ns, E4, F4, I4-pvs, MMSR2, MWIR1
Language of instruction: The course will be given in English

Aim

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.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must

Judgement and approach
For a passing grade the student must

Contents

Examination details

Grading scale: TH - (U, 3, 4, 5) - (Fail, Three, Four, Five)
Assessment: Approved laboratory assignments give grade 3. An approved final project is required for grades 4 and 5.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Modules
Code: 0122. Name: Laboratory.
Credits: 7.5. Grading scale: UG - (U, G). Assessment: Approved laboratory sessions give grade 3.

Admission

Assumed prior knowledge: Programming, Basic probability, statistics, and algebra.
The number of participants is limited to: No

Reading list

Contact

Course coordinator: Amir Aminifar, amir.aminifar@eit.lth.se