Best Online Master's in Data Science

Sharpen your critical thinking skills and expand your mathematical knowledge with an online master's in data science. This degree can help you qualify for advanced positions or switch roles, launching a new career in a fast-changing field.

In data science online master's programs, you can focus on general data science or emphasize an area of specialization such as statistical analysis, computational linguistics, or information visualization. Once you graduate, you can qualify for jobs such as data engineer, database architect, or statistician, which earn higher-than-average salaries.

Use this guide to learn more about the top online master's in data science programs, benefits of earning your degree online, and career paths you can follow after graduation.

Top Online Master's in Data Science Degrees

Why Should You Get a Masters in Data Science Online?

As demand grows for data professionals across industries, earning a master's in data science can help you stand out in the job search. This degree equips you with the skills to extract insights from data.

Online data science programs typically offer increased flexibility, allowing you to balance your studies with work or other commitments. They often provide access to the same quality education as on-campus programs. Some online degrees even operate in an accelerated format, allowing you to graduate in twelve or fewer months.

What Jobs Can You Get With a Master's in Data Science?

Professionals with a master's degree in data science can pursue an array of careers in mathematics, statistics, and data science. For example, you can become a data engineer, software analyst, or machine learning engineer. Common jobs for data science master's graduates include:

Database Administrators or Architects

Database architects build data management systems, which database administrators then manage. These professionals often work in computer systems companies or for insurance and finance agencies.

• Required Education: Bachelor's degree
• 2022 Median Annual Salary: $112,120
• Job Outlook (2022-32): 8%

Data Scientist

Using analytic techniques, data scientists mine meaningful information from raw data. They collect, categorize, and analyze information; create data models; present their findings; and make business recommendations. These professionals may work in computer systems, finance, insurance, or scientific research companies. With experience or a master's degree, data scientists can become managers.

• Required Education: Bachelor's degree
• 2022 Median Annual Salary: $103,500
• Job Outlook (2022-32): 35%

Mathematicians and Statisticians

Using math and statistics to solve problems, mathematicians and statisticians collect and analyze data. These professionals design surveys and mathematical models, interpret data, and create data visualizations. They work in industries like government, healthcare, research, and higher education alongside engineers, scientists, and other specialists.

• Required Education: Master's degree
• 2022 Median Annual Salary: $99.960
• Job Outlook (2022-32): 30%

What Can You Expect From an Online Data Science Master's Program?

While enrolled in online master's in data science programs, enrollees learn to use advanced statistical and computational techniques to extract valuable insights and make informed decisions from data. The goal of these programs is to produce professionals who can effectively collect, analyze, interpret, and visualize data to solve complex problems and drive innovation across industries.

Data science master's students take courses in general data science, business analytics, machine learning, and data ethics. They may also complete a capstone project or master's thesis to culminate their degree. Many programs require 30-36 credits, so full-time learners taking 9-12 credits per semester can finish their degree in 12-24 months of study. Some accelerated programs move even faster.

Cost varies based on factors like location, student state residency, and public or private institutional status. Some schools charge less than $10,000 in tuition for an entire program, while others are more expensive.

What Are the Admission Requirements?

Each school establishes its own admission requirements for master's programs. Typically, stipulations include a bachelor's degree from an accredited institution with a minimum GPA of 3.0.

Applicants with a degree in a field other than mathematics or computer science may need to demonstrate their preparation for the program through their resume or the completion of prerequisite courses. Some schools may also require GRE or GMAT scores, letters of recommendation, personal statements, and application fees.

Which Courses Will You Have to Take?

Data science programs offer a variety of courses in computer science, business, and data. Common classes in this field include:

• Data Analytics in R: This course delves into advanced statistical modeling in the R programming language. It involves a comprehensive exploration of linear and logistic regression, examining additional regression and classification methodologies while maintaining a dedicated focus on practical applications.
• Data Manipulation: This course explores the acquisition, transformation, processing, refinement, aggregation, and structuring of data through programming languages like Python.
• Information Visualization: This course teaches students to tell stories through data. Learners craft actionable dashboards, empowering their organizations to make data-driven decisions. Enrollees often use tools like Qlik and Tableau to visualize data.
• Foundations of Machine Learning Models: A comprehensive introduction to machine learning, this class unravels the concept of machine learning, its purpose, its domains, and its limitations. Students learn concepts such as k-nearest neighbors, support vector machines, decision trees, and principal component analysis.
• Data Science for Business: This course explores the diverse applications of data and scientific methodologies within business environments. Students focus on using data for informed decision-making within the realm of business operations.

How Much Does an Online Master's Degree Cost?

For the 2020-21 school year, the average tuition for graduate programs was $19,749, according to the National Center for Education Statistics (NCES). Tuition ranged from a low of $8,910 among the bottom quartile of public institutions to a high of $42,910 among the top 25% of private schools.

Many other factors affect the price of higher education, including a school's prestige, students' state residency, and whether the program is on campus or online. In addition to tuition, applicants should budget for other educational expenses like required hardware or software, internet access, and student fees.

Financial aid can help cover the cost of a graduate degree. While Pell grants are not available to master's-level learners, scholarships, employer reimbursement, private grants, and veteran assistance can help learners pay for their degree.

How Do You Choose an Online Master's in Data Science Degree?

Choosing the best online master's in data science means looking at each program's accessibility, affordability, and utility in the marketplace. Consider these factors:

• Admission: Have you taken any required prerequisite courses? Does your GPA meet the school's minimum? Have you taken the GRE or other required standardized tests?
• Student-to-Teacher Ratio: Schools with lower student-to-teacher ratios can offer more opportunities for individualized instruction and mentorship from faculty.
• Staff Credentials: What degrees do professors in each prospective program hold? Where did they earn those degrees? Which faculty members hold career experience in the field? What research have they done, and where are they published?
• Cost and Financial Aid: Compare available financial aid with total degree cost to find a school that fits your budget.
• Alumni Network: Schools with robust alumni networks can help you find employment in the data science sector after graduation.
• Research Opportunities: Does your school's data science lab allow online students to participate on research teams? Are professors willing to collaborate with online learners who want to do research?
• Accreditation: Your university of choice needs to hold institutional accreditation from an approved organization.

FAQ About Online Master's in Data Science Programs

Is a master's in data science hard?

Data science students explore technical concepts like advanced statistics, algorithms, and machine learning. Enrollees who struggle with these topics may find a data science degree more difficult than learners who excel in these areas.

Is an online data science master's degree credible?

Credible degrees come from accredited colleges or universities. Your school should hold institutional accreditation from accrediting agencies like the Southern Association of Colleges and Schools or the Northwest Commission on Colleges and Universities.

Do I need a master's degree to be a data scientist?

A master's degree is just one way professionals can pursue data science jobs. Though many careers in this field only require a bachelor's degree, earning a master's in data science can help graduates qualify for advanced roles or transition into data science from other academic backgrounds.

What is the difference between data science and big data?

Data science is concerned with making sense of data and using it to drive informed decision-making. "Big data" refers to massive volumes of data, which experts in this field often cannot analyze using traditional methods. While data science can certainly work with big data, its focus is on deriving meaningful insights from data rather than solely dealing with large volumes of information.

What is the difference between data science and data analytics?

Data science and data analytics both involve extracting knowledge and insights from data. Data science is a broader, more interdisciplinary field that combines techniques from statistics, computer science, and domain expertise. These tools help professionals extract insights and predictions from complex, often unstructured data.

While data analytics may involve basic statistical analysis, it generally doesn't involve the advanced statistical modeling and machine learning used in data science.

All rankings and school descriptions on this page were created and reviewed independently by the TBS Rankings Team.