Information Management Course 2013-14

General Informations

Homepage of previous editions

Lecture topics and slides

• Lecture 01 (Oct 2nd '13): Introduction to Information Management and Data Mining (slides in LibreOffice and (slides in pdf format); motivation and examples; big data and analytics; main issues in data mining.
• Lecture 02 (Oct 2nd '13): Know your data (slides in LibreOffice and slides in pdf format); data objects and attribute types, basic statistical descriptions of data, measuring data proximity.
• Lecture 03 (Oct 9th '13): Data preprocessing - part 1 - (slides in LibreOffice and slides in pdf format); the quality of data; data cleaning, integration and reduction.
• Lecture 04 (Oct 9th '13): Exercise session 01 - Introduction to R (list of topics ; dataset: Breast Cancer Wisconsin ). An R IDE can be downloaded from the R Studio homepage .
• Lecture 05 (Oct 16th '13): Data preprocessing - part 2 - (slides in LibreOffice and slides in pdf format); data transformation and discretization.
• Lecture 06 (Oct 16th '13): Excercise session 02 - Data Preprocessing in R: implementing similarity measures and statistical correlation analyses.
• Lecture 07 (Oct 23th '13): Online Analytical Processing, Data Warehousing and Data Cube technology (slides in LibreOffice and slides in pdf format).
• Lecture 08 (Oct 23th '13): Principal Component Analysis (slides in LibreOffice and slides in pdf format).
• Lecture 09 (Oct 30th '13): Excercise session 03 - Implementing and experimenting PCA in R ( dataset for Lab experiments)

Pointers to related material

• The reference textbook for the course is "Data Mining: concepts and techniques" by J. Han, M. Kamber and J. Pei (3rd edition).
• The former editions of the Information Management course were held by prof. A. Tettamanzi: you can find syllabus and slides at the corresponding website.