Internet Technology

Web Analytics

Seminar, 2.00 ECTS


Course content

Lecture topics are methods to gather and analyse web data. The seminar is divided in three major parts:
1) Statistical analysis of data from available data sources like server logs or user tracking records
2) Analysis and Reporting on dynamic Online data sources
3) Usage of integlligent algorithms for data mining and gathering like Recommender systems

Learning outcomes

Students are able to analyze existing log data of web servers and user behavior.
Deeper knowledge about different approaches of programming languages (for example, procedural, object-oriented, functional, parallel) are obtained. In particular, special speech details (memory allocation, pointer arithmetic under C) are used. Among other things, he / she is able to use pattern matching with regular expressions for efficient word processing as well as the automation of sequences using dynamic scripting languages.

Recommended or required reading and other learning resources / tools

Books: The C Programming Language. Brian W. Kernighan, Dennis Ritchie, Prentice Hall
Programming in Python 3. Mark Summerfield. Addison-Wesley Longman 2008
Dive Into Python 3. Mark Pilgrim, APres; HTML5: Up and Running, Mark Pilgrim O'Reilly 2010

Mode of delivery

3 ECTS Seminar

Prerequisites and co-requisites

Web Engineering 4, Software Engineering 4

Assessment methods and criteria

Continuous Assessment