Valid for: 2024/25
Faculty: Faculty of Engineering LTH
Decided by: PLED I
Date of Decision: 2024-04-16
Effective: 2024-05-08
Main field: Technology
Depth of study relative to the degree requirements: First cycle, in-depth level of the course cannot be classified
Mandatory for: I2
Language of instruction: The course will be given in English
The course begins with an overview of basic data wrangling and visualisation. With a focus on the student's ability to identify and illustrate important features of the data.
Then important methods in statistical learning are introduced. Emphasis is given supervised and unsupervised learning. Issues arising from fitting and evaluating multiple models as well as the methods relationship to linear regression are discussed. Computer based labs and projects form an important part of the learning activities.
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
Grading scale: UG - (U, G) - (Fail, Pass)
Assessment:
Passing grade on all written lab reports and attendance on at least one scheduled lab per lab report.
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: 0123. Name: Computer Lab 1.
Credits: 2.0. Grading scale: UG - (U, G).
Assessment: Reporting of the lab.
The module includes: Data handling and visualisation.
Code: 0223. Name: Computer Lab 2.
Credits: 2.0. Grading scale: UG - (U, G).
Assessment: Reporting of the lab.
The module includes: Continuous prediction (regression).
Code: 0323. Name: Computer Lab 3.
Credits: 2.0. Grading scale: UG - (U, G).
Assessment: Reporting of the lab.
The module includes: Classification.
Admission requirements:
Course coordinator: Linda Hartman,
linda.hartman@matstat.lu.se
Director of studies: Johan Lindström,
studierektor@matstat.lu.se
Course administrator: Susann Nordqvist,
expedition@matstat.lu.se
Course homepage: https://www.maths.lu.se/utbildning/civilingenjoersutbildning/matematisk-statistik-paa-civilingenjoersprogram/