Masters Degree in Data Science
What is Data Science?
"The coming century is surely the century of data" (Donoho, 2000). Data Science is emerging as a new, transformative paradigm in science and technology. With large volumes of data being generated every day from multiple sources (including business data, biomedical data, educational data, science data, engineering data, and personal data), the importance of systematic and rigorous approaches to understanding and putting these large volumes of data to good use is now well recognized. With this explosion of data, there is a significant demand for experts in industry, government, education, healthcare, etc., that have requisite skills to collect, process, and analyze data. Indeed, demand for Data Science master's degrees has exploded in the last couple of years as indicated by the fact that the number of master's degrees awarded in this area has quadrupled from around 5,000 to around 20,000 between 2016 and 2018. Furthermore, Data Scientist has been consistently ranked as the most promising job (defined by high salary, high demand, continual growth, and potential for advancement) by major job search websites such as Glassdoor.
REFERENCE: Donoho, D.L. (2000). High-Dimensional Data Analysis: The Curses and Blessings of Dimensionality. Lecture Delivered at the "Mathematical Challenges of the 21st Century" Conference of the American Math. Society, Los Angeles.
About the Program
The Masters degree in Data Science offers interdisciplinary training in the area of Data Science in order meet booming demand in the job market. Indeed, the importance of systematic and rigorous approaches to understand and take advantage of large and diverse volumes of data is well recognized. Furthermore, Data Scientist has been consistently ranked as the most promising job (defined by high salary, high demand, continual growth, and potential for advancement) by major job search websites such as Glassdoor.
The nature of the program includes core courses in theoretical foundations of Data Science, i.e., Computer Science and Statistics, and elective courses in discipline-specific quantitative analysis methods. The elective courses are clustered in specific disciplines such as Economics or Biomedical. Students attending the program will acquire a wide range of Data Science competencies including: (1) basic system administration, programming, and computational data processing, (2) basic mathematical and statistical concepts for data analysis, (3) advanced computational statistical and machine learning skills for big data analysis, (4) ethical aspects, security, reproducibility /provenance aspects of Data Science, and (5) Data Science problem solving conceptual model and process (meta-competencies).
Teaching and research assistantships are available for qualified applicants. These assistantships include a tuition waiver and a monthly living stipend. To learn more about available opportunities, contact email@example.com.