Published on: 28th June 2017
13 - 17 November 2017
About the Course
Applications are now open for the course 13 November – 17 November 2017.
Data scientists working in healthcare are called to deal with problems involving classification and pattern recognition. The objective of this module is to provide the essential theory and practical aspects of widely used machine learning software.
Examine the basic framework of data mining in general and machine learning in particular and their relationship with different clinical encoding and classification systems.
Compare and contrast basic data summarization models developed within the field of data mining (such as classification, prediction, clustering and association models).
Design and apply data mining models to representative problems often encountered in health applications.
Employ key scientific packages used in healthcare to apply classifiers to clinical data.
Evaluate the impact of clinical classification and encoding schemes on data quality and classification performance.
Critique research publications.
Who should attend
This is a technical course designed for beginners or individuals who may have had some involvement with databases through typical roles in a data analysis environment and are seeking to expand their knowledge and understanding of manipulating healthcare related data through relational databases.