What a Degree in Public Health Taught me about Data Science. Why graduate programs in public health are worth your consideration
I’ve seen countless articles, blog posts, and tweets arguing fervently for or against the idea of pursuing an advanced degree in order to enter the data science field. I think that this debate is far too context-dependent to have a winning side, but pursuing an advanced degree after college was the right path for me. Typically, the only degrees I’ve seen included in these conversations are master’s and PhDs in data science, computer science, and statistics. While all of those degrees have obvious value and relevance to data science, I would like to introduce degrees in public health to the conversation.
The field of public health is all about protecting and improving the health of the public, and it has a wide array of sub-fields. Two of these, epidemiology and biostatistics, are highly quantitative and have much in common with data science. Epidemiology is the study of the distribution and determinants of disease and other health-related states and events, while biostatistics is, unsurprisingly, largely focused on statistical methods relevant to health and medicine. I completed a two-year Master of Public Health (MPH) in Epidemiology and gained invaluable skills and conceptual knowledge during the course of the degree.
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The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
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A data scientist/analyst in the making needs to format and clean data before being able to perform any kind of exploratory data analysis.