Data Science Master's Degree Without a GRE

Oct 04, 2019

Students who have not completed the GRE exam and would like to pursue a graduate degree program in data science may still be able to study at certain accredited universities. Continue reading for more information courses and admissions requirements.

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The GRE exam is a general test that is designed to assess proficiency in a number of areas and a passing score may be required by many graduate degree programs. There are a number of master's degree programs in data science, including online programs, that do not require scores on the GRE test for admission. The absence of GRE results in the admissions process does not affect the nature of the degree program and some of the courses that students will complete will be similar to those that require a GRE.

Common Courses in Master's Degree Programs for Data Science

These are the courses that students would likely take when enrolled in data science master's degree programs.

Management of Data

The ways in which data is managed and stored are vital parts of data science. When taking courses like these, students will learn about databases and the systems that usually employ them. Students will also learn how to tune databases and optimize them.

Statistics

The use of statistical techniques is relevant to the area of data science that handles data analysis. With this in mind, these courses tend to cover topics such as probability and types of variables. Students can expect to learn about expectations and their properties as well.

How Machines Learn

Machine learning classes are designed to delve into the advanced areas of computer systems. The courses usually cover material related to regression and vector machines. Other topics that would be covered are algorithms and types of learning techniques.

The Relationship Between Humans and Data Science

Students will take a more hands-on approach to explore the relationship between humans and data science. Courses may cover topics such as user experience design, artificial intelligence, and relevant analytical methods. Students may also learn about the ethics that govern keeping data private as well as how to treat intellectual property.

Tools and Technologies of Data Science

Data science uses a number of tools and technologies in order to obtain and process data. As such students must learn about cloud services and computer programming languages. Students will also learn how to understand the structure of data.

Admission Requirements for Master's Degree Programs for Data Science

Students are required to hold an undergraduate degree with a minimum GPA of 3.0, while this does not need to be in the same field of study, this is preferred. If students do not hold a bachelor's degree in the same field, then they are expected to have some relevant work experience. Applicants may also need to have covered prerequisites in calculus, linear algebra, and computer programming to meet the requirements of certain master's programs. Applicants will need to submit their school transcripts and other documents such as a current resume, letters of recommendation and a statement of purpose may also be required.

While the options for a master's degree programs that don't require a GRE test score for admission may be fairly limited, students will still gain the same education to those programs that require a GRE. More important than the GRE in these programs is the previous education or work experience.

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