Master's in Data Science Online With No GRE

Nov 28, 2019

If you want to attend a master's program in data science but don't want to take the GRE, there are several program options available to you. Learn about the coursework and entrance requirements for online data science master's degree programs.

The interdisciplinary field of data science encompasses the study of computer science, applied mathematics, and statistics. It's possible to attend an online master's degree program in data science without having to take the GRE. In this article, we will explore that common coursework that makes up a data science master's program curriculum as well as the various entrance requirements for admission to these programs.

Common Courses for Online Master's Degree Programs in Data Science

Online master's degree programs in data science could require anywhere from 8-15 total courses, and some programs may require a thesis. Although your exact coursework depends on your chosen program, the below course descriptions are representative of the types of classes you might take during your online degree program.

Data Visualization

Data visualization is the study of how to present data in a visual way. In a course like this, you may learn how to create interactive graphics and web-browser based data presentations. These courses usually also include the study of human psychology in terms of how people perceive and process information.

Machine Learning

Machine learning is the study of how to enable artificial systems to learn from their experiences. In a class of this type, you might study different models of learning, including supervised, unsupervised, and semi-supervised learning, as well as various algorithms for model discovery and knowledge. You might also study how to assess machine learning performance. Last, some courses might require you to write programs that include machine-learning techniques.

Data Mining

Data mining is an interdisciplinary subfield of data science that explores the different methods for preprocessing, understanding, and visualizing data so that insights can be extracted from that data. Data mining spans the study of artificial intelligence, mathematical modeling, and machine learning. In a data mining class, you could study methods for classification, such as the Bayes Decision Theory and Support Vector Machines, and could learn about data mining software, such as Weka and R.

Algorithms

Courses like these aim to teach you about the different kinds of algorithms as well as the techniques behind designing algorithms. These courses also usually focus on algorithm analysis, including the techniques of asymptotic notion, the correctness of algorithms, and recurrences. Other topics you may cover include graph algorithms, data transformations, and computational complexity.

Programming Foundations

You might also take a class that centers on developing your skills and knowledge about the principles of programming. Usually, this will be a broad course that introduces such concepts as logical structures, subprograms, data types, expressions, and structured data types. You could also learn how to write algorithms, use C++, Java, and PHP, and build database-driven websites.

Natural Language Processing

Natural language processing is a field of study that concerns creating algorithms that teach computers how to understand human language. In a course of this kind, you could study the statistical, linguistic, and probabilistic underpinnings of natural language processing as well as the different algorithms used within the field. Other topics you may study are the key elements of human language technologies, such as sentiment analysis, machine translation, information extraction, and question answering.

Admittance Information for Online Master's Degree Programs in Data Science

There are several online data science master's degree programs that don't require the GRE for admissions. However, many online programs, but not all, do require that you have completed prerequisite coursework in calculus, statistics, and/or programming. Other application requirements include holding a bachelor's degree with some programs requiring a GPA of 3.0. You must also submit an application, transcripts, a resume, and letters of recommendation.

Data science master's degree programs typically include a range of coursework on analyzing and presenting big data, programming, and algorithms. Many online programs of this kind don't require GRE scores but may require prerequisite coursework.

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