Data Mining (HWS 2021)

The course provides an introduction to advanced data analysis techniques as a basis for analyzing business data and providing input for decision support systems. The course will cover the following topics:

  • The Data Mining Process
  • Data Representation and Preprocessing
  • Clustering
  • Classification
  • Regression
  • Graph Mining
  • Text Mining

The course consists of a lecture together with accompanying practical exercises as well as student team projects.  In the exercises the participants will gather initial expertise in applying state of the art data mining tools on realistic data sets. The team projects take place in the last third of the term. Within the projects, students realize more sophisticated data mining projects of personal choice and report about the results of their projects in the form of a written report as well as an oral presentation.

The webpage about the HWS 2020 edition of this course is found in the lecture archive.

Exam Review

  • Detailed information about the exam review will be announced after the exam
  • Instructors

  • Time and Location

    • Lecture: Wednesday, 10.15 – 11.45, Room A 001 (B 6, Bauteil A) + Zoom (Dr. Tobias Weller)
    • Exercises:

    The Zoom Links for the Lecture and Exercise are available in ILIAS.

    Note: The lecture will be offered as a hybrid course. Students can attend the lecture either in the lecture hall in compliance with the current Covid-19 regulations and hygiene policy or via Zoom. The Exercise is offered entirely online via Zoom.

  • Final exam

    • 75 % written exam
    • 25 % project work (20% report, 5% presentation)
  • Registration

    • For attending the course, please register for the lecture in Portal 2. The course is limited to 90 participants. There will be no „first come – first serve“. Students in higher semesters and students that have failed the course in FSS2021 will be preferred, equally ranked students will be drawn randomly.
    • You don't have to register for the Exercise.

Lecture Videos, Slides and Exercises

Materials will be uploaded in ILIAS.

 

Outline

WeekWednesdayThursday
08.09.2021

Lecture: Introduction

Exercise: Introduction to Python / RapidMiner

15.09.2021Lecture: RegressionExercise: Regression
22.09.2021Lecture: Classification I – Logistic Regression Exercise: Classification I
29.09.2021Lecture: Tuning ML ModelsExercise: Tuning ML Models
06.10.2021Lecture: Classification II – Decision TreesExercise: Classification II
13.10.2021Lecture: Classification III – Neural NetworksExercise: Classification III
20.10.2021Kick Off Team Project 
27.10.2021Lecture: Text MiningExercise: Text Mining
03.11.2021Lecture: Clustering

Exercise: Clustering

10.11.2021Team Project Feedback

 

17.11.2021Lecture: Graph Mining

Exercise: Graph Mining

24.11.2021Team Project Feedback

 

01.12.2021Results Presentation 
08.12.2021Exam FAQ 

Final Exam: Monday, 20.12.201 (Duration: 60 Minutes). The location will be announced in time.