The rise of computers and digital businesses has revolutionized the world. However, to keep up with advancing technologies, businesses continually need skilled workers with backgrounds in data science. With a online master’s in data science, individuals set themselves up to enter a lucrative, fast-growing field. Computer and information research scientists, a common landing spot for those with a master’s in data science, make an annual median wage of $122,840, according to the Bureau of Labor Statistics (BLS). The BLS also projects a 16% growth rate for computer and information research scientists from 2018-2028, much faster than the average growth rate for all jobs.
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Earning a graduate degree does not have to be expensive. Affordable online data science programs teach the same skills and methods and more expensive in-person programs, only at a lower cost to the learner.
The best online master’s in data science programs prepare graduates for successful careers, often offering some of the best outcomes in the industry. We rank the best online data science programs based on these outcomes, along with other factors including tuition rates, curriculum, accreditation, and renown.
Understanding an Online Master’s in Data Science Program
In an online master’s in data science program, students learn to communicate computer science concepts and information, create and manage new strategies, compile analytics at an advanced level, and lead teams to meet organizational goals. Most students have professional backgrounds in data science and want to advance their careers.
Common Specializations for an Online Master’s in Data Science
As a specialized field, many master’s in data science programs do not offer specializations. However, students can focus their education through elective courses, studying topics related to their desired role within data science.
Area of Focus
Careers This Concentration Prepares For
Big data, also referred to as big data systems, teaches students to design, implement, and interpret complex data sets, then adjust systems based on analytics.
Data scientist, data architect, database administrator, data engineer, software development engineer
Big Data Analytics
Similar to big data, big data analytics places an emphasis on analyzing existing data sets for valuable insights. This focus also emphasizes decision making and leadership.
Data scientist, database manager, data analytics, data engineer, computer systems analyst
A fast-growing field for all industries, a focus in data analytics teaches data science students to gather useful data through cutting-edge tools, compile the data, then develop new business strategies based on analytics.
Data scientist, data analytics, operations analyst, database architect, database manager
Similar to data analytics, data mining works closely with large data sets. Data miners learn to use a combination of statistics and machine learning to discover patterns in large data sets, then advise future action based on the data.
Data scientist, data analyst, data engineer, database manager, business intelligence analyst
A machine learning focus teaches students to model large data sets and process unstructured data sets for information, all with the assistance of artificial intelligence.
Machine learning engineer, business intelligence analyst, data scientist, database manager, computer system analyst
Predictive analytics uses data sets to try and predict future trends. Students learn methods including machine learning, predictive modeling, and data mining.
Data analysis, data scientist, business operations specialist, database manager, chief data officer
Online Master’s in Data Science Admission Requirements
Admissions into master’s in data science programs are competitive, so applicants should do what they can to improve their applications, including going beyond these admission requirements.
Bachelor’s Degree: Regardless of experience, all master’s degree applicants must hold a bachelor’s degree from a regionally accredited institution. Most programs prefer candidates with a bachelor’s in computer science or a related field and a 3.0 GPA or higher.
Experience: Many programs do not explicitly state experience requirements, though all master’s in data science degrees require students to demonstrate proficiency in programming languages. Students with 2-3 years of relevant professional experience might receive preference.
GRE Scores: While not required for all master’s in data science programs, strong GRE scores boost applications. Students with lower GPA scores on transcripts should consider taking the GRE.
Professional Resume: Applicants’ professional resumes include previous education, work experience, and other useful pieces of information. A strong resume demonstrates background and interest in data science.
Statement of Purpose: Competitive graduate programs only select applicants who demonstrate an interest in data science. The statement of purpose is an applicant’s chance to prove why they’re a good candidate for the program.
Curriculum for an Online Master of Data Science Program
While specific core and elective courses vary by program, many programs offer the following courses, sometimes with slightly different course titles and subject matter.
Database Systems and Data Preparation: This course introduces the fundamentals of database systems and data preparation, including relational database systems, relational modeling, and structured query language. Most programs require this course early on to introduce more complicated topics later.
Practical Machine Learning: Practical machine learning introduces machine learning techniques, resampling techniques, and various methods of grouping and analyzing data. Some programs include the use of open-source software, a common practice for data science.
Statistics for Data Science: A necessary course for data scientists, statistics for data science teaches various quantitative methods of research for analyzing data. This course combines traditional statistics material with large data sets.
Computer Vision: Offered as an elective course, computer vision teaches a specialized method of deep learning through images, including the creation of digital representations of x-rays, sensor images, and hand-written documents.
Capstone Project: Many master’s in data science programs end with a capstone project. The capstone project usually groups students together to teach leadership and communication skills while providing graduates with real-world experience.
Online Master’s in Data Science Program Length
Most master’s in data science programs take 30-36 credits and 1-1.5 years to complete, though numerous factors influence program length. Factors include:
Online vs. On-Campus: Online students have more flexibility than on-campus students and complete courses at their own pace. Some online students graduate faster than on-campus students.
Part-time vs. Full-time: Part-time students take roughly 2-3 years to complete a master’s degree, though part-time students can continue working while studying.
Transfer Credits: Students with certifications, significant work experience, or previous graduate school experience could earn transfer credits, immediately reducing the length and cost of the master’s degree.
How to Pay for a Master’s in Data Science Degree
Tuition continues to be a hurdle for incoming students. Fortunately, master’s in data science students have plenty of methods for reducing tuition costs beyond the FAFSA.
Techniques for Financing a Online Master’s in Data Science
Not only do internships often pay students for their work, but some programs also convert hours worked in an internship into college credits, ultimately reducing the cost of the degree.
Fellowships, such as the Data Incubator Fellowship Program, submerse students in multi-week programs and pay students for their work. Fellowships also help graduates form professional connections and gain experience.
The remaining costs of a degree can be paid down through financial aid. Financial aid includes scholarships, grants, and student loans. Contact schools and programs to learn more about specific financial aid opportunities available.
Scholarships for Online Master’s in Data Science Students
One of the best ways to help finance education is through scholarships. Some scholarships are only available to master’s in data science students, and some require students to begin a program before applying, so keep checking for opportunities.
Society of Women Engineers ScholarshipWho Can Apply: Women at all levels of college may apply for this scholarship. The award goes to applicants pursuing a degree in engineering, technology, or computing, and applicants must demonstrate financial need. Amount: Varies depending on the number of award winners
UPE Scholarship Who Can Apply: The Upsilon Pi Epsilon award goes to applicants who are also Association for Computing Machinery members. Winners are selected based on need, academic records, and recommendations. Amount: $1,000 – $2,500
Remote DBA ScholarshipWho Can Apply: All students pursuing a career in data science or a relevant field may apply for this award. Applicants submit a themed essay and include their cover letter. Amount: $1,000
Strong Data Science ScholarshipWho Can Apply: Available to undergraduate and graduate students, applicants find a public dataset, find an interesting research question, then produce an analysis, visualization, and interpretation of the data. Amount: $1,000
Future Leaders of IT ScholarshipWho Can Apply: The Connect Worldwide Scholarship Fund offers awards to students who demonstrate potential leadership in the world of technology. Applicants submit recent college transcripts. Amount: Up to $2,000
Masters in Data Science Online Free Programs
Graduate students continue to seek out affordable options for college, but did you know that there are some programs that are free? While there are no full master’s programs for free, that are accredited, there are some programs that allow students to watch lectures from past sessions and free courses from reputable institutions. Students won’t get a masters diploma from these courses but they can learn on par with masters students. All of this for free and 100% online. Explore the following programs below: Coursera: Coursera offers many courses in Data Science and lets students “read and view” for free. Udacity: Udacity has many course in Data Science for beginners, that are free. edX.org: edX.org has real college courses from institutions such as Harvard, MIT and other top universities. Most of the courses are free. Open Source Data Science Masters: The Open Source Data Science Masters is a great resource that offers many Data Science lectures, videos for free.
Resources for Online Master’s in Data Science Students
Before graduating or after earning a master’s degree in data science, students should take advantage of professional organizations. These organizations provide members with networking opportunities, career development, and other useful resources.
INFORMS: INFORMS is a fast-growing international association for research and analytics professionals. Members receive access to professional development opportunities, industry tools, and an extensive professional network.
Association for Computing Machinery: The Associations for Computing Machinery (ACM) connects industry leaders in data science working in all fields. ACM’s network of over 100,000 global professionals helps data science graduates find new careers.
ASIS&T: ASIS&T combines information science and research, accepting members in fields from data science to content management. Student members receive career services and access to networking opportunities.
Research Data Alliance: The Research Data Alliance connects European, United States, and Australian professionals to encourage the open sharing of data. Students can access valuable industry information through the Alliance’s website.
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