Data science is a field of study that mixes computer science, statistics, mathematics, and information science in order to analyze and understand different kinds and sets of data. A degree in data science can prepare you for a career as a data scientist or data analyst where you will be collecting and organizing data, creating algorithms for machine learning, and extracting insights from data. There are two types of data science degrees, which we will discuss in-depth below.
Data Science Master's vs. PhD
Master's in Data Science
Master's-level programs in data science will require anywhere from 12-30 credits and can take 1-2 years to complete, depending on the specific program and your individual pace through that program. There will be some common topics and coursework found in each program, which you must complete in order to earn your master's in data science. Some of the core courses you could take will include subjects such as big data, machine learning, statistics, general data science, and data mining. You will also be required to take elective courses that could be related to computer science, advanced probability or algebra, or engineering. Most, yet not all, programs will also require a capstone research project or a thesis project. A limited number of programs will allow you to specialize within the field of data science by choosing concentrations such as data engineering or artificial intelligence.
PhD in Data Science
The PhD in data science is a step beyond the master's degree. For a PhD-level program, you will need to earn anywhere from 60-78 credits with the exact number varying by program. A PhD program in data science will also take several years to complete, including the first 1-3 years spent on coursework and the remaining year, or years, spent on exams and developing a dissertation. Like the master's-level programs, your coursework for the PhD will include such topics as managing big data, data mining, probability and statistics, and research methods. The qualifying exams could be written, oral, or both, and will test you on the concepts and specific area of data science you have chosen. The dissertation process will include a proposal and a defense.
Common Admission Requirements
There are several common admission requirements for both the master's and PhD in data science that include an application, transcripts, GRE scores, letters of recommendation, and a personal statement. Because of the mathematics and computer science elements of advanced data science degrees, some, but not all, programs will require that you have completed coursework in advanced mathematics, such as calculus or statistics, or hold a relevant bachelor's degree. PhD in data science programs will most likely want to see a background in math or computer science while that kind of background will be a plus for master's programs.
Both kinds of graduate degrees in data science will allow you to pursue a career as a data scientist in the world of academia or in the private sector. The master's and PhD degrees in data science will teach you how to structure, interpret, and understand data.