Course Description
Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.
Data science is helping scientists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.
At present, there is a lack of formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience in order to build a complete skill-set.
At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.
Data science is helping scientists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.
At present, there is a lack of formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience in order to build a complete skill-set.
At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.
Professors: Peter Fox, Thilanka Munasinghe
Course Goals
To instruct future scientist how to sustainably generate/ collect and use data for their research as well as for others. Participants will learn and be evaluated on the full life-cycle of data and relevant methods, technologies and best practices.