There are a number of accredited higher education institutions that offer both graduate certificates and graduate degrees in data science. The main differences between the two can be found in the requirements for admission as well as the coursework that students are expected to cover. This article will present information pertaining to the two program options.
Differences Between a Graduate Certificate and a Master's Degree in Data Science
Information About a Graduate Certificate Program in Data Science
It may be helpful to have a mathematical background for a graduate certificate program but it's not always necessary as some programs offer introductory math courses as a part of the program. Some of the topics that graduate certificate programs offer, cover materials related to data science, data mining, statistics, machine learning, and other mathematics-based courses. For persons who want flexibility in their learning environment, there are some graduate certificate programs that are offered completely online or as part-time evening classes. In order to complete a graduate certificate program, candidates may need to complete twelve credit hours in as little as nine months. In some cases, the courses offered in the graduate certificate program are a part of a master's degree program and so persons can easily transition to a graduate degree by completing the rest of the required courses.
Information About a Master's Degree Program in Data Science
In order to be considered for a master's degree in data science, candidates will not only need an undergraduate degree from a similar field, but they must also have completed prerequisite programs in mathematical subjects such as algebra and calculus. Master's degree programs will generally have more in-depth courses than graduate certificate programs and will cover topics related to statistics, data analysis, probability, computer systems, and computer science. Some master's degree programs in data science are offered online but it may take longer to complete than if done on campus or at a learning center. The credit requirements to complete a master's degree program range from nine to thirty credits and students may complete the required courses in as little as nine months or as much as two years. Some master's programs will also offer a real-world project that enables students to contribute practical applications of data science to actual scenarios.
General Admission Requirements for Graduate Certificate and Master's Degree Programs in Data Science
While master's degree programs in data science usually require an undergraduate degree in data science, statistics or a mathematical field, some graduate certificate programs for data science make allocations for persons without prior data science academic achievement by including a prerequisite course. With master's degree programs, students must submit official transcripts of their undergraduate degree to prove a minimum GPA of 3.0 as well as letters of recommendation, a statement of purpose, a resume, passing scores on a proficiency test such as the GRE and proof of work experience. Some graduate certificate programs do not have any admission requirements while others need the applicant to submit official transcripts, a statement of purpose and a resume.
While the graduate certificate programs in data science may be more open and accommodating to persons who have little or no previous knowledge of the area, some of the courses offered only cover certain aspects of data science. The master's programs, on the other hand, have more stringent admission requirements but offer more in-depth courses related to data science.