A vast amount of data is currently being collected and accumulated at an ever-increasing rate. Consequently, there is a need for new strategies and tools to assist humans in extracting useful information from this constantly growing body of digital data.
This task can be accomplished using various data science techniques, which allow for the integration of information and the discovery and extraction of patterns that are not initially apparent. Furthermore, the application of these tools makes it possible to generalize, characterize, classify, segment, and associate data of different kinds, as well as to study the evolution of various patterns, visualize information, and extract knowledge from diverse sources. In particular, the application of machine learning methods enables the explanation of various phenomena and the generation of predictions based on new observations.
In the field of biomedical sciences, this translates into support for decision-making by experienced professionals, who will be able to use data science and associated algorithms in various applications, such as predicting susceptibility to certain medications, the possible evolution of diseases, estimating the margin of benefit for a certain clinical treatment, analyzing epidemiological patterns, among others.
The objective of this program is to provide an introductory theoretical and practical framework of concrete applications of data science in real clinical cases, so that students develop critical thinking about its use and visualize the benefits of integrating this knowledge into their professional practice.
Biomedical science professionals (doctors, biologists, pharmacists, biochemists, or related fields).
The course will consist of theoretical and practical classes. The first half of each class will be dedicated to explaining basic concepts of data science and machine learning algorithms, which will serve as a theoretical framework for implementing them with public domain databases. The second half will be dedicated to running scripts in Google Colaboratory, where the operation of the different algorithms will be explained.
The following topics are intended to be covered:
The Faculty of Engineering of the Universidad Austral will issue the Academic Certificate of course completionIntroduction to Data Science in Biomedical Sciences"to those who comply with the promotion regime."
La Universidad Austral is #1 in Argentina
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