Guide to Online Master’s in Data Science Programs

Data science combines principles from computer science, artificial intelligence, statistics, and other relevant fields to draw actionable insights from large datasets. A data scientist creates meaning from raw data, sifting through vast amounts of information and providing analysis to help stakeholders understand trends and decide on future courses of action.

Working in an inherently interdisciplinary field, data scientists combine methodologies from multiple domains. Many data scientists build, test, and update predictive models, algorithms, and visualizations to ensure accuracy, leveraging coding languages like Python, R, and SQL along the way.

If you enjoy solving analytical problems, working in multiple disciplines, and advising business leaders, an online master’s in data science can prepare you for an exciting career. Continue reading to learn more about the top data science master’s programs.

An online master’s in data science program teaches individuals the skills to pursue careers in the field. Master’s-level graduates demonstrate to employers that they have the programming, data gathering, and analysis knowledge necessary to work in data science. Data science program applicants can choose between in-person and online programs.

Prospective enrollees should consider the potential benefits and drawbacks of each option. Online programs offer increased flexibility and allow students to attend nationwide courses without having to relocate. However, distance programs may provide fewer opportunities for networking and one-on-one interactions with professors.

A data science master’s degree equips graduates for roles like data scientist and statistician. However, the skills gained over the course of the degree are applicable to a wide variety of roles in different industries.

Computer and information research scientists, for example, solve problems relating to computing systems, while economists study the flow of resources in society. Additionally, actuaries leverage data and statistics to assess risks in industries like insurance.

Some graduates decide to pursue further education. If you are particularly studious, you can contribute original research to the field in a doctoral program.

Data science programs help enrollees develop academic and practical literacy in computer science and business by examining real-world problems. Graduates learn multiple programming languages to gather data and use statistics to gain valuable insights.

Most full-time data science programs take 1-2 years and require 30-45 credits. Program tuition can range from $20,000-$70,000, which does not include additional fees for books, extracurriculars, or the cost of living.

Data science, a broad term, includes many subfields. Prospective data scientists can often choose from data science specializations, including analytics, artificial intelligence, and technology entrepreneurship. Enrollees engage in core, analytical, programming, and business courses.

Some master’s in data science programs require a capstone project or research paper. Institutions may allow students to choose between these pathways. Schools typically have the same costs, courses, and graduation requirements for online and in-person programs, though they may apply additional distance learning fees.

Students who must complete capstone projects can implement their cumulative skills to program and generate real-world business plans. Enrollees completing thesis requirements can demonstrate their knowledge of data science, research, and analysis.

Admission requirements for master’s in data science programs vary among institutions. Generally, an applicant must hold a bachelor’s degree from an accredited institution with a 3.0 GPA or higher. Individuals do not need to hold bachelor’s in data science or computer science degrees but may need to demonstrate relevant skills or take prerequisite courses.

Candidates can start the application process by confirming eligibility, completing an online application, submitting official transcripts, and paying an application fee. Programs typically require each applicant to submit a statement of purpose, a resume, letters of recommendation, and/or a writing sample. Many schools do not require GRE/GMAT scores, but prospective enrollees should always research this requirement before applying.

Data science programs offer various curriculums, electives, and specializations. However, most schools explore similar fundamental knowledge and core courses. The list below includes some of the most common courses in online master’s in data science programs.

Master’s in data science tuition can range from around $20,000-$70,000 for the entire program. In-person and online costs are approximately the same. Tuition costs depend on factors like school prestige, program length, and in-state vs. out-of-state residency. Attendees should also budget for necessities like housing, food, a computer, and any tech requirements.

Applicants can take advantage of financial aid programs to assist with their online master’s in data science program. Scholarships and grants, like the Great Minds in STEM scholarship and the Department of Defense Scholarship-for-Service program, do not need to be repaid, making them ideal sources of funding.

Enrollees who do not receive scholarships can apply for private and federal loans, which require repayment. Students can receive federal and local aid by filling out a Free Application for Student Aid (FAFSA) form, which will determine eligibility.

Data science program applicants should only attend schools that hold accreditation. Accredited institutions have undergone voluntary evaluation by third-party agencies recognized by the Council for Higher Education Accreditation and/or the U.S. Department of Education to ensure that they meet a certain standard of education.

Departments and programs within institutions can also hold accreditation. The primary accreditor for data science programs is ABET’s Computing Accreditation Commission, but the agency does not offer the status to graduate programs.

When selecting a data science master’s program, be sure to check your prospective school’s accreditation status. Accredited schools undergo third-party review to ensure that they offer rigorous and valuable education to learners.

An online program offers several benefits. Students can complete a degree from any location with an internet connection and don’t need to relocate for school. An online program may be a good fit for students who want to study while working full time.

Keep in mind that some online courses are more flexible than others. Asynchronous courses allow students to listen to lectures and complete work on their own schedule, while synchronous courses require attendance for online sessions that occur at fixed times. Many online programs use a mix of both methods.

Also, consider other ways that your prospective program can provide opportunities for you. Research the internships and field experiences typically offered in your prospective program. Additionally, schools with robust alumni networks can give you an advantage when searching for work as a new graduate.

Data science uses individuals to filter and analyze data, while machine learning automatically learns by using past data. Data scientists can excel with strong business and analytical skills — machine learning engineers focus more on programming.

Online master’s in data science programs usually take 1-2 years to complete. A student’s timeline to completion depends upon their amount of transfer credits, courseload, and full-time vs. part-time enrollment choice.

Not all data science jobs require applicants to hold master’s degrees in data science. However, master’s degree-holders may receive preference among other job candidates and demonstrate their hard skills and commitment to the industry.

Data science requires coding to gather, clean, and organize data. Data scientists can use multiple programming languages, including Python, R, and SQL.

Individuals interested in data, analytics, and business may find data science master’s programs to be worthwhile ventures. Prospective data scientists often must take on a significant financial burden to learn necessary skills but can pursue roles that align with their skills and interests after graduation.