Data Science

The 9 Best Reasons to Earn a Part-Time Data Science Master’s Degree

The 9 Best Reasons to Earn a Part-Time Data Science Master’s Degree
If you have an aptitude for statistics, computers, mathematics, and problem-solving, data science could be the career for you. Most data scientists hold a graduate degree, so if you're considering this opportunity, you should also think about earning your master's. Image from Pexels
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Tom Meltzer February 1, 2021

Part-time study allows you to keep working while you earn your master's. That's one good reason to pursue your degree part-time; we have eight more.

Data Science Programs You Should Consider

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The COVID-19 pandemic introduced a new term to the popular lexicon: “social distancing.” According to public health experts, social distancing—coupled with the wearing of surgical masks—represented the best pre-vaccine defense against the spread of this dangerous virus.

How effective is social distancing? To find the answer, data scientists studied cell phone geolocation data to determine where people were—and weren’t—following good social-distancing procedures. By tracking phone users’ movements and correlating them to reported coronavirus cases, data science arrived at a definitive conclusion. The data demonstrated that “as person-to-person interactions… increased, there was a corresponding increase in confirmed COVID-19 cases.”

This is just one of many, many examples demonstrating how data science can be used to understand our world and formulate better strategies. With digital devices gathering data on everything from your shopping habits to your physical activity to population-wide trends, data science is positioned to play a crucial role in business, government, health policy, and education. It’s hard to see how that trend could reverse any time soon.

If you have an aptitude for statistics, computers, mathematics, and problem-solving, data science could be the career for you. Most data scientists hold a graduate degree, so if you’re considering this opportunity, you should also think about earning your master’s.

Many universities offer this degree in both full-time and part-time programs. Which is right for you? In this article, we explore the nine best reasons to earn a part-time data science master’s degree by addressing the following:

  • What is a master’s in data science?
  • What will you learn in a data science master’s program?
  • Why get a part-time master’s in data science?
  • Top master’s in data science programs
  • Top online master’s in data science programs
  • Least expensive master’s in data science programs
  • Least expensive master’s in data science programs

What is a master’s in data science?

A master’s in data science is a graduate-level degree with a data science designation, such as:

  • Master of Science in Data Science (MSDS)
  • Master of Data Science (MDS)
  • Master of Information and Data Science (MIDS)

Because data science is a new field that combines a number of disciplines, it is possible to work in data science with a related degree, such as:

As the field of data science establishes itself, the distinctions among these different degrees will grow clearer. For now, all can funnel into data science careers.

What is data science?

Data science is an interdisciplinary field that combines coursework in mathematics, statistics, computer science, business administration, and healthcare. And that’s just the tip of the iceberg;
according to Dr. Ganapathi Pulipaka, Chief Data Scientist at Accenture, data science blends“software engineering, predictive analytics, machine learning, deep learning, HPC, supercomputing, mathematics, data mining, databases (SQL, NoSQL), Hadoop, streaming analytics platforms for live analysis (Apache Kafka, Apache Flink, Apache Spark, Apache Impala), IoT platforms, edge computing, fog computing, networks, statistics, web development, cloud computing, data engineering, and data visualization.”

By collecting, sorting, and analyzing Big Data sets, data scientists can draw valuable insights about the past and use them to project future outcomes. It’s not hard to figure out how that can be useful to decision-making in everything from marketing to public health policy to sports management. Wherever large amounts of data collect—which is pretty much everywhere these days—data science is potentially useful.

What jobs fall under the category of data science?

Job titles for data scientists with a master’s degree can include:

  • Artificial intelligence researcher
  • Applications architect
  • Big Data solutions architect
  • Bioinformatics analyst
  • Business intelligence analyst
  • Computational finance manager
  • Cyber security analyst
  • Business systems analyst
  • Data engineer
  • Data modeling specialist
  • Data strategist
  • Data warehouse engineer
  • Enterprise architect
  • Machine learning engineer
  • Machine learning scientist
  • Robotics research scientist
  • Statistician

Do I need a master’s to work in data science?

A 2018 report from Burtch Works indicated that 43 percent of all data scientists hold a master’s degree as their highest degree. OK, you say, that’s less than half; that means you have still have a pretty good chance of getting a job with just a bachelor’s degree.

We hate to burst your bubble, but sit down: the other shoe is about to drop. Another 48 percent of data scientists hold a PhD as their highest degree. Only one in ten data scientists currently scrapes by with only a baccalaureate. And the other data scientists probably make them clean up the conference room after meetings.

Not all of those graduate degrees are data science degrees per se. One-quarter are in mathematics or statistics. One in five is in computer science. 20 percent hold a degree in the natural sciences, and nearly as many—18 percent—have engineering degrees.

You don’t technically have to have a graduate degree to become a data scientist, but your chances are much, much better if you have one. That’s a trend that should only grow more pronounced as more graduate-level data scientists enter this increasingly complex field.

Do I need a doctorate to work in data science?

You don’t have to have one, but nearly half of all data scientists do (See Do I need a master’s to work in data science? above for details). Some companies—Google, for one—pride themselves on the number of PhD-level data scientists they employ.



University and Program Name Learn More

What will you learn in a data science master’s program?

Each data science master’s program offers a unique curriculum. All, however, focus to some extent on:

  • Computational means of collecting and organizing large data sets
  • Statistical and mathematical processes for analyzing and interpreting data
  • The use of artificial intelligence, machine learning, and language processing to automate data science processes

The online data science master’s program offered by the University of Virginia (Main Campus) includes the following courses:

  • Programming and Systems for Data Science
  • Linear Models for Data Science
  • Foundations of Computer Science
  • Data Mining
  • Exploratory Text Analytics
  • Big Data Analytics
  • Practice and Application of Data Science
  • Ethics of Big Data
  • Data Science Capstone Project Work
  • Bayesian Machine Learning
  • Machine Learning

New Jersey’s Stevens Institute of Technology offers an online data science master’s with a similar curriculum:

  • Linear Algebra
  • Probability
  • Statistical Methods
  • Numerical Linear Algebra for Big Data
  • Advanced Optimization Methods
  • Applied Machine Learning
  • Deep Learning
  • Dynamic Programming and Reinforcement Learning
  • Natural Language Processing
  • Database Management
  • Time Series Analysis
  • Distributed Systems and Cloud Computing

Some data science master’s programs offer students the opportunity to specialize in a more specific field. After completing required core courses, students develop their specializations, or concentrations, through elective courses. Specialization areas include:

  • Artificial intelligence
  • Big Data and data analysis
  • Bioinformatics
  • Computational finance
  • Cyber security
  • Data engineering
  • Data modeling
  • Machine learning

Why get a part-time master’s in data science?

Once you decide to pursue a master’s in data science, you still face a significant question: should you attend a full-time program or study part-time? Each has its compelling reasons. Below we explore nine reasons why part-time study makes sense to so many.

1. You can continue to work, gaining experience and earning money while you learn

Full-time graduate school degree programs are as advertised: they require a full-time commitment. As a full-time student, you may find time for a bit of project work or a part-time job, but chances are you will be fully occupied with school work. Yes, you’ll complete the program sooner, but while you’re studying, that’s pretty much all you’ll do.

Part-time students can, and typically do, continue to work full-time. As a result, they don’t forfeit the one- to two-years of income that full-time students forgo. And—assuming they work at a data-science-related job—they will have the opportunity to apply their classroom learning to real-world applications as they learn it. Part-time study provides unique opportunities to practice and reinforce school skills, a process that promotes retention.

2. Your employer will recognize your commitment to improvement

If your employer has any interest in keeping you around long-term, they want to see you working to improve your skills and knowledge. There’s no better way to do that than to pursue a graduate degree, particularly in a field with so many applications in the workplace. Not only will you show your boss that you’re ambitious, you’ll also get the chance to demonstrate your ability to manage your time, handle a heavy workload, and succeed at difficult challenges. All of those are huge plusses that can only help your career.

3. Your employer may contribute to cost of degree

Most employers encourage their employees to improve their skills through professional development, trainings, certifications, and graduate programs. Some do more: they offer to kick in to help defray the cost of learning. Some even foot the entire bill. Check with your employer to learn whether they offer an education benefit. You could be sitting on a free pass to a data science master’s degree program.

4. You’ll have a less-intense academic load

There’s a lot to learn in a data science graduate program: lots of mathematics, lots of statistics, lots of computer science. You’ll need to memorize vast amounts of information and learn how to put it to practical use. Not everyone is comfortable learning at the firehose pace set in full-time programs. Part-time programs parcel out the learning in smaller chunks so you have more time to absorb it, practice it, and incorporate it into your repertoire of skills.

5. You’ll have more time to develop interests and specializations

Taking a longer time to earn your degree doesn’t just reduce the intensity and pressure of the learning experience. It also gives you more time to absorb your learning and to see where it takes you. With the luxury of a few extra semesters, you’ll have time to develop an interest in, and aptitude for, artificial intelligence or data management or predictive modeling, and to tailor your study to pursue that interest. That’s less likely to happen during a shorter, concentrated full-time program.

6. You’ll benefit from convenient class scheduling

Full-time programs typically meet on weekdays, during the day. Part-time programs don’t, because they are designed for working students. Classes are scheduled for students’ convenience: in the evenings and on weekends.

Online programs offer even more flexibility and convenience. If you enroll in an online program that holds synchronous (i.e., live) online classes, live sessions typically meet once or week, and in some cases even less often than that. And some online programs are entirely asynchronous, meaning students complete online courses entirely on their own schedule. Pre-recorded lectures, assignments, and other content are accessible 24/7, so students can work anytime anywhere they have access to the internet. Are you a night owl? An early bird? Want to grab a quick 15-minute study session during your lunch break? With online study, that’s doable.

7. Lower per-semester cost

Part-time study spreads school costs over a longer period, reducing the financial hit you take each time you pay your tuition. It may even keep per-semester costs low enough to obviate the need to take student loans. Reducing the financial burden of school should help reduce the stress of the graduate school experience.

8. The same reason for earning a full-time degree: to improve your skills, knowledge, and resume

Earning a part-time data science master’s degree means earning a data science master’s degree, and that means you’ll get all the same benefits full-time students derive from their degrees. You will develop expertises and skills you never before had, and the confidence to use them. And you’ll have an impressive degree to show your employer and other prospective employers

9. As with a full-time degree, you’ll network with faculty and fellow students

Full-time students don’t have a monopoly on access to faculty, peers, and alumni. Prestigious schools earn their reputations in large part for the networks into which they introduce students. You’ll belong to that network and derive the same benefits as full-time students.

Top master’s in data science programs

Among the nation’s top Master of Science in Data Science programs are:

Top online master’s in data science programs (100)

You’ll find excellent online Master of Science in Data Science programs at:

Least expensive master’s in data science programs

Relatively inexpensive Master of Data Science can be found at:

Least expensive online master’s in data science programs

You’ll find affordable online Master of Data Science programs at:

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About the Author

Tom Meltzer began his career in education publishing at The Princeton Review, where he authored more than a dozen titles (including the company's annual best colleges guide and two AP test prep manuals) and produced the musical podcast The Princeton Review Vocab Minute. A graduate of Columbia University (English major), Tom lives in Chapel Hill, NC.

About the Editor

Tom Meltzer spent over 20 years writing and teaching for The Princeton Review, where he was lead author of the company's popular guide to colleges, before joining Noodle.

To learn more about our editorial standards, you can click here.


Data Science Programs You Should Consider


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