Precision Health is an emerging field that takes a big data approach in an attempt to precisely identify individual needs and conditions to enhance health and wellness through disease prediction and prevention. It shifts the healthcare paradigm from the traditional “reactive” approach, where a person is treated after a disease is diagnosed, to a newer “proactive” approach where disease prediction and prevention are emphasized. IoT (Internet of Things) technology from search engines, health/fitness apps and websites, to wearable technology (i.e. Fitbit, Apple Watch) provide boundless data and endless opportunities for personalized medicine.
Although the use of big data in creative industries is relatively nascent, it is in high demand. There are plenty of career options for graduates with specialized training. Future occupations include, but not limited to the following:
● Bioinformatics scientist
● Computational biologist
● Bioinformatics programmer
● Clinical analyst
● Health informatics specialist
● Healthcare IT project manager
● Health informatics consultant
● Privacy analyst
● Healthcare data analyst
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The BS in Data Science is a 125-semester credit curriculum with three major components: major requirements (77 credits), core general education courses (42 credits), and free electives (6 credits).
|DAS461||Directed Study: Career Development||2|
|CIS341||Cloud Computing and Big Data||3|
|CIS335||Machine Learning and Artificial Intelligence||3|
|CIS211||Introduction to Discrete Mathematics||3|
|CIS105||Data Structure and Algorithms||3|
|CIS102||Introduction to Computing||3|
|STA345||Nonparametric Statistics||3 (Elective)|
|STA341||Survival Analysis||3 (Elective)|
|STA335||Stochastic Processes||3 (Elective)|
Design and Analysis of Experiments and |
|MAT207||Calculus III||3 (Elective)|
|STA331||Applied Regression Analysis||3|
|STA211||Statistical Theory and Methods||3|
|STA101||Principles of Probability and Statistics||3|
Statistical Computing and Graphics |
(R or SAS)
|DAS341||Introduction to Computational Biology||3|
|DAS342||Health Data Analytics||3|
|BMS231||Public Health & Epidemiology||3|
|BMS245||Introduction to Precision Health||3|
|BSC221||Genetics & Biotechnology||3|
The College requires that all undergraduate students, regardless of major, complete core general education courses in nine distributions. Students of the Data Science program can meet the Quantitative Reasoning distribution requirement through their major courses. As a result, 42 general education credits from the Liberal Arts and Sciences program will be required.
Students are free to choose 6 credits from any college level courses offered by the College.