105.707 Advanced Methods for Regression and Classification
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2023W, VU, 3.0h, 4.5EC
TUWEL

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise
  • Format: Hybrid

Learning outcomes

After successful completion of the course, students are able to

  • explain and formulate theoretical concepts of important dimension reduction techniques and methods for linear and nonlinear regression and classification
  • identify the strengths and weaknesses of the different statistical methods and tools and to use them in practice

Subject of course

During the past decade there has been an explosion in computation and information technology. With it has come vast amount of data in a variety of fields such as medicine, finance and marketing. The challange to understand these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning and bioinformatics. This lecture describes the important ideas in these areas in a common conceptual framework.

Teaching methods

Examples with data, software environment R

Mode of examination

Written and oral

Additional information

The practice part of this VU will be held online via zoom.

12.10.2023 - 25.01.2024, 11:30-12:30

For details see TUWEL course.

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed08:00 - 10:0004.10.2023 - 24.01.2024HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu11:30 - 12:3012.10.2023 - 25.01.2024 Zoom Link in TUWELÜbung
Advanced Methods for Regression and Classification - Single appointments
DayDateTimeLocationDescription
Wed04.10.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Wed11.10.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu12.10.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed18.10.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu19.10.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed25.10.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Wed08.11.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu09.11.202311:30 - 12:30 Zoom Link in TUWELÜbung
Thu16.11.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed22.11.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu23.11.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed29.11.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu30.11.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed06.12.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu07.12.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed13.12.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu14.12.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed20.12.202308:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser
Thu21.12.202311:30 - 12:30 Zoom Link in TUWELÜbung
Wed10.01.202408:00 - 10:00HS 17 Friedrich Hartmann - ARCH Vorlesung Filzmoser

Examination modalities

Solving examples in R, oral exam

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Thu12:00 - 14:0014.03.2024Sem.R. DA grün 02 C - GEO written&oral29.02.2024 13:00 - 12.03.2024 23:59TISSOral Presence Exam AMRC

Course registration

Begin End Deregistration end
31.08.2023 09:00 15.10.2023 12:00 15.10.2023 12:00

Curricula

Literature

No lecture notes are available.

Miscellaneous

Language

English