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Best Online Data Science Master's Programs

Review top schools with online data science master's programs and how much they cost. Explore what data science programs consist of, how long they take, and what careers they can lead to.

Best Schools with Online Data Science Programs

Online data science master's programs are offered by many schools throughout the United States. When choosing a program, it's important to consider cost, requirements and time to completion. Listed below are some of the best schools that offer online data science master's degree programs.

1. University of Colorado Boulder

Location Tuition & Fees (in-state)
Boulder, CO $13,246

The University of Colorado Boulder has a Master of Science in Computer Science program that can be completed entirely online. Students can choose a concentration in data science and engineering, enabling them to gain a deeper understanding of data science topics. The program includes courses in data architecture, linear programming, data analytics, and data mining. With the data science sub-plan, students are required to complete 45 credit hours of coursework, and the program has a total tuition cost of $37,530.

2. University of Illinois at Urbana-Champaign

Location Tuition & Fees (in-state)
Champaign, IL $18,126

Students of University of Illinois at Urbana-Champaign can earn a Master of Computer Science in Data Science online in two years or less of full-time study. The program consists of 32 credit hours and includes courses in data mining, machine learning, and cloud computing. The non-thesis program allows students to transfer in up to 12 credit hours of approved coursework. The total program tuition cost, without any transfer credits, is $21,440. The Grainger College of Engineering here boasts several computer-science related programs that regularly rank in the top 5 in the country.

3. Oklahoma State University-Main Campus

Location Tuition & Fees (in-state)
Stillwater, OK $8,460

Oklahoma State University-Main Campus has a Master of Science in Business Analytics and Data Science program that can be completed entirely online. The program consists of 33 credit hours and allows students to choose a customized concentration using their elective courses (15 credits) or choose a concentration in marketing analytics, advanced data science, health analytics or cybersecurity analytics. Students use quality analytics programs and software to practice data analysis and understand how data can be used to solve problems in business. The total tuition cost for in-state residents of the MSBAnDS program is $13,367.

4. Saint Joseph's University

Location Tuition & Fees (in-state)
Philadelphia, PA $16,992

The Master of Science in Business Intelligence & Analytics program at Saint Joseph's University can be completed online in 1 to 1.5 years of full-time study or around 2 years of part-time study. Students can choose a concentration in data science, which explores programming languages and machine learning within business and business intelligence. Students will take courses in database management, data mining, enterprise data, and machine learning. The program consists of 30 credit hours and has a total in-state tuition cost of $32,250.

5. Duquesne University

Location Tuition & Fees (in-state)
Pittsburgh, PA $23,112

Duquesne University has a Master of Science in Analytics & Information Management (STEM) program that offers online and hybrid course options. Students learn to use methods of analysis as well as various models and tools to create discernments for better decisions in business. The program consists of 10 classes (30 credit hours) and has a total tuition cost of $29,160. The curriculum mirrors that of many data science programs and includes courses in data sourcing, data analytics, data structures and artificial intelligence.

Rank School Name Location Tuition & Fees (in-state)
6 Creighton University Omaha, NE $17,376
7 University of the Cumberlands Williamsburg, KY $5,970
8 Rockhurst University Kansas City, MO $16,060
9 Davenport University Grand Rapids, MI $15,126
10 Elmhurst College Elmhurst, IL $31,667

All table statistics provided by the National Center for Education Statistics, tuition based on 2018-2019 school year

Learn.org's school ranking methodology categorizes and assesses data from schools and other reliable sources, such as the U.S. Department of Education, and weighs the information based on quality, cost, value and other factors critical to students' academic decisions.

Online Data Science Master's Degree Overview

Online master's degree programs in data science may be a Master of Science in Data Science or one of many other degrees in computers with a data science concentration. Data science is a combination of statistics, mathematics, and information technology. Data scientists use various programming languages, and data retrieval methods to collect, analyze, hold, process, and communicate information. In data science programs, students learn to acquire, enter, clean and process data, as well as how to mine, analyze, and report that data.

Data science programs can be completed entirely online without any on-campus visits, and can usually be completed within one or two years of full-time study. Because of the technical nature of these programs, students may be required to have earned a bachelor's degree in a computer science or related field, and/or pass an entrance exam that demonstrates an understanding in certain topics (such as programming languages). Students who do not have the required prerequisites and knowledge will likely need to complete some bridge coursework to ensure they're ready to begin the graduate coursework.

Students may also need to complete an introductory online course or tutorial to familiarize themselves with the online learning platform. Depending on the school and program, students may use their learning portals for assignments, forums, communication and exams. In addition, some courses may allow students to log in at their convenience while other courses may require some or several scheduled logins for activities such as lectures and exams.

How to Choose an Online Data Science Master's Program

As you consider schools for an online master's program in data science, there are a few things that you should keep in mind. Several important program considerations are listed below.

Programs Offered

When reviewing your school choices, it's imperative that you make sure they fit your needs. For example, some programs may require you to have a bachelor's degree in a computer science field and/or have certain prerequisites. In addition, some programs lead to Master of Science in Data Science degrees while other programs may lead to related degrees such as an MS in Business Analytics with a data science concentration. While the curriculum is similar, you should decide which degree program fits your background and career objectives.

Flexibility

Many online data science master's programs allow students to choose between full-time and part-time study, but some may only offer one or the other. Depending on your time restrictions and desired finish date, you may want to tackle your program part-time or full-time, or perhaps you may decide switch between the two. Check with your school choices to see if their programs are flexible or only offered in one format. Also review the course delivery to see if courses require synchronous learning (scheduled), in-person elements or if you can complete it at your leisure.

Cost

Online programs can vary significantly in cost depending on the school and the student's educational background. Some students may be able to transfer in courses to save time and money, while other students may need to complete some bridge courses. The cost of an online master's degree in data science can cost $13,000 to $30,000 or more. Consider how much you can afford before committing to a program. And, keep in mind that there are various types of financial aid available for graduate programs.

Accreditation

When choosing an online program in data science, make sure that the school is properly accredited. There are various accreditation bodies that can accredit universities, including the Higher Learning Commission and Association to Advance Collegiate Schools of Business. Accreditation shows that the university has been reviewed by a neutral party and passes various requirements. A program provided by a school without accreditation may not provide a quality education, or be recognized by future employers as a qualifying preparation.

Faculty

Data science programs are very technical and require an extensive understanding of various scientific, theoretical and analytical topics. When reviewing programs, check to see that the faculty has sufficient experience and expertise. Another thing to ask your school choices is what degree the faculty are made available, and how long it takes to receive a response to any communications that you may send in. You want to make sure that they can effectively answer any questions that you have in a timely manner.

What You'll Learn in an Online Data Science Master's Program

Some data science master's programs have a specific set of courses while other programs have a set of core courses and allow students to select some data science electives. Listed below are several classes that are commonly found in master's degree data science programs.

  • Data Mining: Students learn the methods and applications of data mining which may include cluster analysis and pattern discovery. After completing this course, students should be able to identify what methods apply to specific mining tasks, compare mining methods and have an extensive understanding of specific mining patterns and classifications.
  • Data Visualization: This course explores tools and methods for visualizing data and may include the development of website graphics. Students develop a deeper understanding of how to communicate and manipulate data with a variety of applications so that viewers are able to effectively understand the information presented.
  • Machine Learning: Students learn to create systems that are able to adapt and learn, and may review how these systems relate to other topics such as data mining. Topics covered by courses like this include reinforcement learning, decision trees, and various other algorithms and machine learning models.
  • Cloud Computing: In a cloud computing course, students explore tools used to manipulate and understand distribution systems such as peer-to-peer systems. Other topics covered may include security, measurement, failure detectors, communication, control, and consensus.
  • Database Management: Students review theories of database operation and design, including applications and normalization. Students may learn how to employ common applications for database management such as SQL (Structured Query Language) within this course.
  • Predictive Analysis: Students further develop their understanding of data mining by reviewing how to apply data mining principles to predict outcomes of data. Topics covered may include scoring, model assessment, decision-making and statistical patterns in data.

What Can You Do with an Online Data Science Master's Degree?

There are a variety of careers that data science graduates are prepared for, many of which are listed below and summarized in the following table. Some positions may hire data science graduates for entry-level positions immediately after graduation, while other positions may require some experience prior to entering an upper-level role.

Job Title Median Annual Salary (2018) Estimated Job Growth (2018-2028)
Computer Systems Analysts $88,740 9%
Computer and Information Research Scientists $118,370 16%
Operations Research Analysts $83,390 26%
Database Administrators $90,070 9%
Computer Programmers $84,280 -7%
Computer Network Architects $109,020 5%
Actuaries $102,880 20%

Salary and outlook information provided by the U.S. Bureau of Labor Statistics

Computer Systems Analysts

Computer systems analysts review the procedures and technological systems used within an organization to identify ways they can be improved. Analysts use various methods in their analysis, including data modeling and testing, and may create useful applications for organizations.

Computer and Information Research Scientists

These individuals create new routes for data and computer processes, and may work in robotics, programming or data science. They may work with algorithms, cloud computing processes, and machine learning systems during the creation and improvement of software. Each of these scientists may create network and system architecture that enables organizations and processes to operate more efficiently.

Operations Research Analysts

Operations research analysts apply analytical and mathematical processes and methods to find ways to solve issues and improve operations for organizations. They may utilize software to analyze, predict, and simulate data. These roles require significant skills in statistics, database software, and data analysis.

Database Administrators

Database administrators organize and maintain data using specifically tailored software, and may also control user and accessibility settings. Some database administrators may write programs, modify and test databases, and maintain database security. Database administrators are required to have a firm understanding of various databased processes (such as SQL).

Computer Programmers

Computer programmers create, test, and implement code that enables programs and applications to run properly. They use various computer languages (such as Java and C++), collaborate with developers, and maintain libraries of code. Computer programmers may work in specific fields, such as accounting, and typically need to be fluent in several programming languages.

Computer Network Architects

Computer network architects create networks for data communication which may include intranets, local networks, and wide networks. They design, implement, test, maintain, and revise networks, and need an understanding of database design and network security.

Actuaries

Actuaries use statistics, mathematics, and theories to analyze the monetary costs of uncertainty and risk. They collect data, design and test various policies and present reports on their findings. These roles require extensive familiarity with mathematics, statistics, databases, and programming languages as well as business and finance.