Data Mining and network analysis IDN0110

Fall 2017/2018

IDN0110: Data Mining and network analysis Taught by: Sven Nõmm EAP: 6.0

 Lectures: Wednesdays      16:00-17:30  ICT-A1
 Labs:     Thursdays       16:00-17:30  ICT-401

Consultation: by appointment only Thursdays 17.30-18-30 Additional information: sven.nomm@ttu.ee

Overview

The course aims to provide knowledge of theory behind different methods of data mining and develop practical skills in applying those methods on practice. Is is spanned around four "super problems" of data mining:

• Clustering
• Classification
• Association pattern mining
• Outlier analysis

Main topics of the course:

• Data types and Data Preparation
• Similarity and Distances, Association Pattern Mining,
• Cluster Analysis, Classification, Outlier analysis
• Data streams, Text Data, Time Series, Discrete Sequences,
• Spatial Data, Graph Data, Web Data, Social Network Analysis

Evaluation

• 2x mandatory closed book tests. Each test gives 10% of the final grade.
• 3x mandatory home assignments (Computational assignment +short write up.) Each assignment gives 10% of the final grade.
• final exam (gives 50 % of the final grade): Written report on assigned topic + discussion with lecturer.

Exam prerequisites: both closed book tests are accepted (graded as 51 or higher), all 4 home assignments are accepted (graded as 51 or higher).

Moodle environment will be set up after the second lecture.

Lecture 1: Introduction

Slides

XLSX file R Example