Data Preprocessing
Kontakt
***Note***
Due to the Coronavirus, many things are unclear. For the period that the university is closed because of Coronavirus, we will have online lectures. The Kick-off Meeting as planned will be held on 15/04/2020 10:30-12:00 and we will have an online lecture. More details about the online platform will be sent by email. Note that participation in this lecture is still mandatory.
Organizational Information
- Room: 2010, Seminar room Chair of Process and Data Science, Ahornstr. 55, 52074 Aachen
- Prof. Dr. Wil van der Aalst
- Coordinating teaching assistant: Mohammadreza Fani Sani, M.Sc., Anahita Farhang Ghahfarokhi M.Sc
- Registration: During the central registration process in February 2020.
- Language: English
Important Dates
Kick-off Meeting: 15/04/2020 10:30 – 12:00
Room 2010, Seminar room Chair of Process and Data Science, Ahornstr. 55, 52074 Aachen
Seminar Details
The learning objective of this pro-seminar is twofold, first to train students to improve their critical thinking through understanding research methodology and instructing them on how to write a scientific paper. Also in this pro-seminar, we will employ data preprocessing as a group of algorithms that enables students to become more familiar with data analysis and data science.
This pro-seminar briefly introduces fundamentals of data preprocessing which is one of the main steps in any data science project that involves transforming raw data into an understandable format. Real data is generally noisy, incomplete, inconsistent, and/or lacking certain behaviors. Data preprocessing comprises a series of techniques that resolve issues and their causes in order to produce more accurate and trustable results.
The following major topics are selected as working materials during this course:
Data cleaning/cleansing
- Noisy Data
- Missing Values
Data Integration
- Redundancy and correlation Analysis
- Data Value Conflict Detection and Resolution
Data Reduction
- Attribute Subset Selection
- Clustering
Data Transformation
- Normalization
- Discretization
- Decision Tree
Concept
Each participant will work on one of the above topics and summarize it in a short paper (maximum 15 pages), using LaTeX completed with an oral presentation of 20 minutes.
All topics will be introduced in the introductory session at the start of the pro-seminar. Participation is mandatory throughout the course. In the introductory session, topics will be assigned to the students and the deadline for submitting the presentations will be discussed.
The language of the course is English; therefore, both the presentations and summaries shall be prepared in English.
Prerequisites
Basic computer science skills and knowledge.
References
References for the specific topics will be given in the first session of pro-seminar.