The education mission of the department is to train and prepare students and postdoctoral researchers to become leaders in the field of biomedical informatics and shape the informatics research and applications to advance health care.
CS 595 Topics in Computer Science: Data Analytics Software - Stacks
Course Overview:
This reading course will cover data analytic applications, infrastructure and analytic methods. Students will have the opportunity to analyze real (de-identified) health care datasets and with spatio-temporal and molecular datasets drawn from cancer research. Each class session will include discussions of applications, infrastructure and algorithms. Students will present papers, we will also have a variety of talks from visiting experts.
Applications: Methods and issues related to data analyses arising from many classes of applications including those drawn from healthcare, science, engineering and commerce.
Infrastructure: MapReduce, NOSQL and column oriented databases, semantic web methods and databases, high end file systems, systems to optimize IO and memory hierarchy performance, stream software and languages.
Algorithms: Machine learning, graph analysis, sensor/image analysis and statistical analysis algorithms discussed in the context of the applications and infrastructure.