The courses taught in ePolyTechnic F’s Department of Arts, Social Sciences, and Humanities, empower our students with a deep understanding of the human complexities—cultural, historical, and economic. Our students learn both processes and collaborative skills in writing, communication, and developing ideas using creative and critical thinking and have the opportunity to pursue wide-ranging interests in the arts, social sciences, and the humanities, both on and off campus.
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The B.S. in Data Science combines applied mathematics, computer science, statistics, optimization, data mining and machine learning to give you a broad and much desired skill set. From tracking patterns in drug discovery, or changes in ocean temperatures and deforestation, to understanding the habits of Netflix users and predicting stock market fluctuations, Data Scientists inform product design, government policy, and business strategy, turning data into actionable insights.
Data science draws from math, engineering, business, and computer science to extract knowledge and insights from data, structured and unstructured. The B.S. in Data Science curriculum will teach you computational and analytic approaches to mastering complex data structures. You will gain hands-on experience with tools such as Excel, Python, R, SQL Databases, and Tableau, and be prepared for emerging careers in Data Science and future advanced study.
Students in Big Data Analytics learn to collect, manage and optimize large-scale structured and unstructured data sets to facilitate information and decision-making. Students in Big Data Analytic develop a strong foundation in essential programming skills, quantitative analysis, and hardware and software solutions for facilitating effective use of big data.
Health Informatics concerns the storage, retrieval, use and delivery of health-related data and information across networks of patients and providers. Whether in support of emergency room optimization, patient health-care affordability, or study and prevention of global pandemics, the practice of health informatics is essential to achieving solutions, better delivery and greater knowledge for the benefit of humankind.
The Health Systems Engineering (HSE) concentration program prepares the architects of tomorrow’s healthcare system to take on its most urgent and complex challenges. Health systems engineering involves a multidisciplinary approach that applies engineering and analytic principles to all aspects of healthcare. Students in the program gain real-world experience with industry experts and a multidisciplinary faculty to prepare students for a career leading change in healthcare.
Intelligent Mobility uses data and technology to connect people, places, and goods across all transportation modes. Growth in intelligent mobility will transform the way people travel, interact with their environment, and connect goods and services.
Quantitative Economics and Econometrics use mathematical and statistical methods to develop techniques for measuring a range of systems, including financial, government, social, legal, medical, and so on. Students with a quantitative economics and econometrics background learn to assess and measure trends to understand complex phenomena and to improve long-term positioning.
Each ePolyTechnic F senior joins a Capstone Design team of (three to five students) of a single discipline (mechanical engineering) or mixed disciplines (engineering, computer science, data science, etc.) to complete a year-long, industry sponsored project. Capstone culminates with a year-end gathering of sponsors and project teams, and the presentation of final ‘beta’ level prototypes. Past Capstone Design projects have led to job offers from sponsoring companies.
A team of data science and business analytics students are helping to solve the problem of how best to minimize medical errors with regards to surgical instrument sterilization, transport, tracking and recovery. Working with Lakeland Regional Health system, the Sterile Department Logistics capstone investigates simulation techniques that could lead to a lean and error-free intelligent surgical instrument management, equipment management, and technician management system.