Masters in Data Science Online Degree Programs of 2022

Master's Degree in Data Science Career Options & Salary

A master’s degree is the degree you earn directly after earning an undergraduate degree. This is after a bachelor’s degree but before a doctorate. The length of time it takes to earn a master's degree depends on the program, the school, and the student’s time commitment. Generally, it will take two to three years to complete, but there are accelerated programs that can take as little as 15 months. The number of credit hours can also vary, but 36-60 hours is the norm. That’s a wide range but, again, it depends on the number of classes required and the number of credit hours assigned to each course. This can vary wildly depending on if you are completing an MBA or a master’s in engineering, for example. Master’s degrees are usually a continuation of what you studied in your undergraduate – you’d earn an MBA after attainting a bachelor’s degree in business or business administration, for example - but they can also be complementary degrees as well. A person who graduated with a bachelor's degree in English could earn a master’s in legal studies if they are interested in focusing on legal writing. Whichever path is taken, the master’s degree is meant to be additional upper-level education for a person looking to further their career.

What are the Best Online Master's in Data Science College Programs?


1

University of California-Berkeley

  • Net Price: $19,329
  • Retention Rate: 96%
  • Graduation Rate: 92%
  • Total Enrollment: 42,327
  • Undergrad Students: 30,799
  • Graduate Students: 11,528
  • Grads Salary: $92,000
  • Student-to-faculty: 19:1
  • University of California-Berkeley
2

University of Virginia

  • Net Price: $19,043
  • Retention Rate: 97%
  • Graduation Rate: 94%
  • Total Enrollment: 25,628
  • Undergrad Students: 17,310
  • Graduate Students: 8,318
  • Grads Salary: $81,000
  • Student-to-faculty: 15:1
  • University of Virginia
3

Northwestern University

  • Net Price: $28,344
  • Retention Rate: 97%
  • Graduation Rate: 95%
  • Total Enrollment: 22,603
  • Undergrad Students: 8,559
  • Graduate Students: 14,044
  • Grads Salary: $85,000
  • Student-to-faculty: 6:1
  • Northwestern University
4

Stevens Institute of Technology

  • Net Price: $40,303
  • Retention Rate: 93%
  • Graduation Rate: 88%
  • Total Enrollment: 7,257
  • Undergrad Students: 3,791
  • Graduate Students: 3,466
  • Grads Salary: $92,000
  • Student-to-faculty: 12:1
  • Stevens Institute of Technology
5

New Jersey Institute of Technology

  • Net Price: $18,328
  • Retention Rate: 89%
  • Graduation Rate: 70%
  • Total Enrollment: 11,652
  • Undergrad Students: 9,084
  • Graduate Students: 2,568
  • Grads Salary: $83,000
  • Student-to-faculty: 15:1
  • New Jersey Institute of Technology
6

Indiana University

  • Net Price: $13,191
  • Retention Rate: 91%
  • Graduation Rate: 80%
  • Total Enrollment: 43,064
  • Undergrad Students: 32,986
  • Graduate Students: 10,078
  • Grads Salary: $70,000
  • Student-to-faculty: 16:1
  • Indiana University-Bloomington
7

Northeastern University

  • Net Price: $37,738
  • Retention Rate: 97%
  • Graduation Rate: 90%
  • Total Enrollment: 22,905
  • Undergrad Students: 15,156
  • Graduate Students: 7,749
  • Grads Salary: $80,000
  • Student-to-faculty: 14:1
  • Northeastern University
8

California State University-Fullerton

  • Net Price: $8,322
  • Retention Rate: 89%
  • Graduation Rate: 69%
  • Total Enrollment: 42,051
  • Undergrad Students: 36,975
  • Graduate Students: 5,076
  • Grads Salary: $71,100
  • Student-to-faculty: 27:1
  • California State University-Fullerton
9

University of Maryland-Baltimore County

  • Net Price: $16,868
  • Retention Rate: 87%
  • Graduation Rate: 70%
  • Total Enrollment: 13,497
  • Undergrad Students: 10,932
  • Graduate Students: 2,565
  • Grads Salary: $76,000
  • Student-to-faculty: 17:1
  • University of Maryland-Baltimore County
10

Regis University

  • Net Price: $27,785
  • Retention Rate: 73%
  • Graduation Rate: 67%
  • Total Enrollment: 6,310
  • Undergrad Students: 3,197
  • Graduate Students: 3,113
  • Grads Salary: $83,000
  • Student-to-faculty: 11:1
  • Regis University
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Where Do You Earn a Master’s Degree?


A master’s degree is earned from a college or university that is accredited to offer graduate degrees. This means that most community colleges cannot offer these degrees. However, some community colleges offer space at their school for satellite graduate program courses. In many cases, the college or university where the undergraduate degree is attained also offers graduate programs in those same majors. If you anticipate getting your master’s degree directly after finishing your bachelor's degree, then choosing a school that offers both programs could be an option worth considering. Otherwise, you’ll need to conduct a search for a college or university that offers an accredited program in the discipline you are seeking. Online programs are also an option, whether you choose an online program from an online only university or the online version of a brick-and-mortar university.

Online Vs. Traditional Education in Data Science


When online courses first became available, online programs were looked down upon in both academic circles and the workplace as inferior to traditional programs. But, as programs and schools have improved their offerings and delivery methods, as well as there being an increasing number of traditional schools offering online options, that stigma is decreasing. The major difference between online and on-campus programs is location. For an online program, you do not have to physically visit a classroom. All classes are held online, either through a message board system or webinars. With the webinar format, some require a live webinar setting, meaning each course meets at a scheduled time, while others are prerecorded webinars that a student can watch when it is more convenient for them. These are synchronous or a-synchronous formats.

Data science lends itself well to an online setting and there are many online programs for data science offered from both traditional and online colleges and universities. So, whether you want to attain a degree in a traditional collegiate setting or you want to take courses online for whatever reason, both are an option from schools with accredited and respected programs. For the most part, the stigma of an online degree being inferior to one achieved at a brick-and-mortar school has been eliminated.

What Are the Prerequisites for a Master’s Degree?


The main prerequisite for a master’s degree is a bachelor’s degree, but there are a few other requirements as well.

To apply for a graduate degree, you will need the following information and documents:

  • Transcripts for all colleges attended
  • Proof of complete a four-year degree from an accredited college or university
  • A completed application to the school and programs and the application fee, if there is one
  • Letters of recommendation from former employers, instructors, or other advisors, if required
  • Copies of GRE or GMAT scores if the exam(s) are required for admission into the graduate program
  • A letter of intent that details why you want to attend that school, major in your chosen discipline, and what your future plans might be
  • Transcript from the high school you graduated from or proof of completion of a GED if you did not graduate from high school

Requirements vary by school, so it’s best to contact the school of interest and attain their specific requirement for admission.

Why Earn a Data Science Master’s Degree?


The main reason to earn a master’s degree is to further your career. In many professions, a master’s degree is a requirement to enter into management positions. There are also special certifications and licenses that cannot be obtained without a graduate degree. For some, the desire to attain further education in their chosen career is the main motivation, especially if they are interested in getting a terminal degree in the future. In other words, a bachelor's degree can get you started but, if you want to continue climbing the corporate ladder, a master’s degree is the next step. Although a person can get far with a bachelor's degree, especially when it is combined with experience and a stellar work history, a master’s degree makes moving up in the ranks easier, even when it’s not required. And, although a master’s degree requires work and some serious dedication, the increase in pay and promotion opportunities a graduate degree promises makes the sacrifice worth it for many people.

If you are the kind of person who enjoys not just answering questions but finding and answering the questions no one has asked yet, then data science is a good field to consider. Data scientists take raw data and manipulate it to solve problems, answer questions, and even prevent issues from occurring. They don’t just answer the “whys”, they look at the material and create the questions that lead to the whys. And then they answer them. Data science is the basis for inventions, preventions, and warning platforms.

Every industry uses data science in one form or another. This means there will always be a need for people to examine the data and create solutions; in some cases, to problems we didn’t even know existed. It’s an important part of our society, not just business and economics, but healthcare, the legal system, and even our political landscape. It’s an important industry and it needs more people willing to dedicate their time, experience, and expertise to it. Data scientists often start with bachelor’s degrees, but progress to graduate level degrees in order to conduct experiments in labs or enter into managerial positions.

What’s Involved in a Master’s Degree in Data Science?


Most data science master degree programs are 30-40-hour programs, depending on the school. This means you can finish your graduate degree in 15-24 months, depending on your course load. And the good news is that, if desired, many graduate data science programs can be completed entirely online.

Common Courses

Some of the courses you might take as part of a data science master degree program include the following.

  • Fundamentals of Data Science
  • Principles of Python Programming
  • Introduction to Statistical Modeling
  • Data and Database Management with SQL
  • Data Analytics in R
  • Foundations of Machine Learning Models
  • Applied Machine Learning
  • Information Visualization
  • A capstone or final project

Some programs might offer a comprehensive final exam instead of a capstone project. This varies by school.

What to Consider When Choosing a Master’s Program in Data Science


Accreditation


When choosing a master’s degree program in data science, one of the most important aspects you must consider is accreditation. You want to choose a school that has regional accreditation from the US Department of Education’s agency the Council of Higher Education Accreditation, or CHEA. If you want to receive any sort of financial aid to help pay for your education, you’ll need to attend a school whose accreditation is recognized by CHEA. This is also important because, as you progress in your career, certifications you might want to pursue often required a degree from a school that is accredited by CHEA.

There are six regional accreditation agencies that CHEA recognizes:

  • Higher Learning Commission (HLC)
  • Middle States Commission on Higher Education
  • New England Commission on Higher Education
  • Northwest Commission on Colleges and Universities
  • Southern Association of Colleges and School Commission on Colleges
  • WASC Senior College and University Commission

When picking a school, check if the school is accredited by one of these agencies. They are usually based on geographic location, but if you don’t see a school accredited in a logical regional agency, check the others as well. Most colleges and universities that are regionally accredited state this fact somewhere in their information materials.

Further Data Science Education


MBA


Many people with data science undergraduate degrees opt to get a master's degree in business administration (MBA). This degree offers students a deeper understanding of how a business functions, different managerial techniques, and how to deal with the psychology of running a business and your employees. This is especially important for those who want to enter management and focus on the back end of running a business. For those who want to continue on the path of a data scientist, a master’s degree in data science is the more prudent approach. Some data scientists opt to get both degrees, which makes them very well rounded in the industry.

Doctorate or PhD


For those who want to reach the upper echelon in a data science career, a doctorate degree in data science is necessary. With a doctorate, a person is qualified to run their own labs, manage other data scientists, and teach at the university level. A PhD in data science can take five to seven years to complete and consists of both classroom and experimental training. A dissertation on a data science subject is also required as if the successful defense of the dissertation.

Certification


There are many different certifications you can get as a data scientist. Here are just a few examples of certifications you can achieve.

  • Amazon AWS Big Data Certification – Must have two years of experience working in AWS

    • Big data skills
    • Both big data and data analytic skills
    • Business applications
  • Cloudera Certified Associate (CCA) – An exam that measures your knowledge as a developer.
  • Cloudera Certified Professional: CCP Data Engineer – The next level of certification after Cloudera Certified Associate

    • Complete an entry- and advanced-level statistics course
    • Complete the data science certification course
    • Data analytics skills
    • Data management and analytics
  • Data Science Certificate – Harvard Extension School – To achieve this certification, you must complete the following:

    • Earn a minimum of a B in four certification courses in three years
  • Microsoft Certified Solutions Expert (MCSE) – This certification covers a range of IT specializations and skills.
  • Oracle Certified Business Intelligence – This certification trains you to make data-driven business decisions
  • SAS Academy for Data Science – this certification includes three programs

Potential Careers for Graduates


Data science is a field where job opportunities are varied and plentiful. Here are a few examples of jobs in the data science field.

  • Data Scientist
    Data scientists find, clean, and organize data for organizations. They are experienced in analyzing data that is both raw and processed in an effort to find patterns that will assist an organization in making strategic business decisions.

  • Applications Architect
    These professionals correlate how applications a business uses affects its interactions with other users. Using this information, architects develop applications that increase positive interactions and eliminate as much of the negative aspects as possible.

  • Enterprise Architect
    This individual’s job is to align an organization’s strategy with the technology they use to run a business.

  • Data Engineer
    These individuals take raw or stored data and process it, either in batches or real time, while also building pipelines for stored data. Basically, they set up the framework data scientists use to complete their work.

Salary Expectations


The average salary for a data scientist is $97,250. The top 10% of data scientists (those with work experience and additional education and certifications) earn closer to $136,000 per year, while a starting salary for data scientists is $68,000. Data scientists will make more money than many other people starting out with a bachelor’s degree, and it’s obvious that the salary potential exists for a comfortable income. And this is just the base salary. Many data scientists also earn commissions when their data is successfully incorporated into a project, as well as many organizations offering profit sharing, bonuses, and other incentives for higher-level employees and managers. Many data scientists also moonlight in other areas, such as teaching or offering private research for individuals or non-profit organizations. Also, it’s important to note that, with additional education and experience, income potential increases as well.

Outlook


According to the US Bureau of Labor Statistics, those employed in the computer and information research industry (in which data scientists are included), the outlook for employment between now and 2030 is good. The need for data scientists is expected to increase 22%, which is must faster than the average of 8%. Between now and 2030, it’s estimated that over 7,000 more data scientists will be needed to meet this demand. The need is anticipated to reach across all industries, so jobs will be available in many industries, including both the private and public sectors. Most of the positions will require a master’s degree, but government jobs often only require a bachelor's degree, so this could be a good starting point for anyone who is just starting their education in data science.