A multidisciplinary field, data science has been getting popular in various industries and sectors. Data science techniques are now being used in a wide variety of fields—from business management to theoretical science. And, it is in high demand today. Also, it pays well. According to the US Bureau of Labor Statistics (2020), the median annual wage of data scientists is $98,230 in the country.
In this article, we will look into how online master’s degrees in data science programs compare to on-campus traditional programs. In this way, you will be able to decide which track to take to further your knowledge and skills.
Online Master’s Degree in Data Science Table of Contents
Yes, you can get a degree completely online. Platforms like Coursera offer legit degree courses from well-known universities. Moreover, universities themselves make online data science degrees available to prospective applicants. This is done through internal learning management system (LMS) platforms.
Online degrees, in general, have become more accepted in today’s society. If tech workers can effectively work from home, data science students can also effectively study and complete courses remotely.
Remote work, especially for those in tech, is likely not going anywhere. Sure, some face-to-face interactions after the pandemic will be required (and would be nice). However, around 80% to 90% of workers never want to work in a physical office full-time again. Aso, 46% of employees would rather work remotely most of the time or all the time (Herd, 2021).
Online graduate degrees related to computers and information technology (IT) are quite popular. In fact, in 2020, 14% of graduate students and 11% of undergraduate students in these fields are working on their degrees completely online (Wiley, 2020).
In fact, there are many people who work in large tech companies who have no college degrees (Eadicicco, 2020). And, looking for exceptional people with the right skills but with no college degree has been the approach of tech giants like Google and Apple.
In 2014, Lazlo Bock, a former senior vice president of people operations in Google, told The New York Times that “people who don’t go to school and make their way in the world, … are exceptional human beings… And we do everything we can to find those people” (Bock in Eadicicco, 2020).
Marc Cenedella (in Eadicicco, 2020), the founder and CEO of a job search and career advice Ladders Inc., added, “We don’t need signals of a college admissions department from 10 years ago to tell us whether or not someone is good. We can do that inspection and assessment ourselves.” This was in reference to Google and Apple as noted by Eadicicco (2020).
However, generally, people with college and graduate degrees earn more than those without (Torpey, 2018).
2. Will employers take my online degree seriously?
Firstly, when respected universities give out diplomas and certificates, they do not explicitly state whether it was earned online or fully on campus. And, online degrees, especially in data science, have little difference from traditional degrees in terms of the level of difficulty of coursework and assignments (Study.com, 2021). Generally, online degrees are being taken seriously by many employers nowadays. There has been a shift in preference as shown in the previous section.
Source: North Eastern University, 2019
3. Are online degrees recognized all over the world?
Yes. Online degrees are generally accepted all over the world, especially when they are given by respected institutions. Top institutions provide excellent online degree programs in a wide variety of disciplines. Also, with the acceptance of work-from-home arrangements today, online education will likely become more prevalent and maybe even normal in the future. Of course, there are other disciplines and tracks that require face-to-face instruction or hands-on training. However, these are not much of a prerequisite for data scientists in training. As mentioned, there are professional data scientists who have no data science degree.
4. Online vs. Traditional Master’s Degree in Data Science
A Master’s Degree in Data Science helps and trains individuals to understand how to curate and manipulate data for insights—actionable or theoretical. Learning these cutting-edge methods will allow graduate students to pursue their interests and use data science techniques to contribute to their fields or places of work.
The main difference between a traditional master’s degree and an online degree is the method of delivery. In traditional programs, students are required to attend classes, lectures, discussions, and group assignments.
On the other hand, online data science programs allow students to work both independently and collaboratively with their professors and peers. It is only that they do it via web-based learning platforms provided by a third party or the university itself. Popular third-party platforms include Coursera and EdX.
Online vs. On-Campus Learning Experience
Because of the medium of delivery, there are several major benefits and disadvantages when taking the online degree route.
Let us start with the benefits.
Benefits of Online Education
For one, online education affords students flexibility. So, parents and those with normal jobs may still be able to further their education. They will be able to study and build skills relatively at their own paces but not totally. This is because just like on-campus traditional classes, online classes have fixed deadlines for assignments and projects. The same goes for quizzes and exams.
Secondly, choosing the online route may also let learners save money and not just time. For instance, students could save on room and board. This is especially true for undergraduates. In the pre-COVID 2018 to 2019 academic year, the average cost for room and board reached $11,216.
Graduate students with jobs and living off-campus, on the other hand, can save on travel expenses and, of course, time.
Thirdly, for many, because of the amount of independence and self-motivation required for an online-only route, students will get challenged. And, in many data science courses, they will be able to learn by doing. This does not only instill the self-reliance usually needed to be a good data scientist but also helps students exercise and improve their creativity.
Of course, this is not for everybody. For those who thrive better in a social environment, this might just be very difficult. This brings us to the disadvantages of taking the online-only route.
Disadvantages of an Online Education
An article by High Focus Centers (2020), a provider of structured outpatient psychiatric treatment and substance abuse programs, raised concerns with distance learning students. It has been found that negative mental health effects can be caused by (i) social isolation, (ii) increased stress and anxiety, and (iii) virtual learning fatigue.
Also, for graduate students who have full-time jobs, having online classes can also be a cause for stress. Having a good life-work-study balance may be hard to come by for those who are quite busy, especially those who are in management positions and high-pressure jobs.
Moreover, a good deal of self-discipline and self-motivation is required to fare well when taking online classes. Many who are not self-starters will mightily struggle. Distractions at home or just the difficulty of the courses may faze them.
Furthermore, without access to school facilities, online graduate students need to use their own devices for learning and building up skills. For data science students, many courses require a good deal of computing power to learn practical skills or programming languages. So, this can be an additional cost that some people may forget to factor in after getting enrolled.
However, not all online classes are built the same. For instance, a professor may opt for live streaming of lectures and discussions. They might even throw in collaborative group projects. On the other hand, other professors and instructors may take a less hands-on approach using pre-recorded videos and digital course materials more often. Also, instead of live group discussions, they might even choose to have scheduled consultation sessions, making taking their courses less flexible for students.
These are part of the many human factors that can negatively affect online education. It is good to note that some educators are just better at teaching than others using digital tools. This does not only include the necessary technical skills—that data science educators already have—but also the communication skills that also take years to build, especially when one is not used to online course delivery.
Is an online degree as good as a regular degree?
Generally, this depends on various factors and on different standards. For instance, when it comes to finding employment, there are companies that may prefer candidates with on-campus experience. This might be a huge factor when they are looking to hire people who would fit their highly social organizational culture.
Many times, professional data scientists are required to report their work and insights to a lay audience working in various business functions, from marketing to logistics. So, a good degree of social skills is required for a post just like this.
Other companies, on the other hand, look for self-starters who work best in isolation with lesser requirements for social interactions. They would rather hire people with great talent in using data science techniques without much data storytelling involved. This is especially so when the company employs expert data storytellers.
However, data storytelling might just be the next chapter in analytics as Stackpole (2020) of MIT Sloan pointed out.
On the other hand, when it comes to the actual learning and building of skills, there is virtually no difference between on-campus and online learning in data science. As mentioned, the level of rigor and difficulty of online data science programs are not that different from their on-campus counterparts. So, students who take the online track will have more or less the same proficiencies as those that choose traditional setups.
Percentage of US Graduate Students Enrolled in Online Degree-Granting Institutions in the US
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Source: National Center for Education Statistics, 2021
5. How much does an online Master’s Program in Data Science cost?
The quick answer is it depends on the school and the platform. This is similar to traditional education. In on-campus data science programs, the average tuition ranges from $8,856 per year to $46, 216 according to pre-COVID data (Digital Science Degree Programs Guide, 2019).
And, these are taken from the ten best Master’s Programs in Data Science in the United States.
The costs of the most affordable online Master’s Degrees in Data Science range from $170 to $665 when it comes to the hourly tuition rate (Online Course Report, 2021). Of course, as mentioned, there are many additional or hidden costs like having the appropriate hardware for computationally heavy task requirements.
Is an online data science degree worth it?
For self-motivated individuals, an online data science degree is worth it. Firstly, it is in high demand with a wide variety of applications. This means graduates can take jobs in many types of industries. And, big companies like Microsoft, Walmart, Mastercard, Hulu, Snapchat, and Tiktok are hiring.
On Indeed.com alone, there are more than 15,000 jobs posted for data scientists. On LinkedIn, there are more than 200,000 jobs posted and 7,361 are newly posted. These figures are accurate as of May 25, 2021.
The field is also quite young compared to others. This could mean better career advancement opportunities. Moreover, it still has a ton of potential for creative innovations. Lastly, the pay is good as mentioned by Glassdoor (2021) pegging an annual salary of $81k to $160k and Salary.com (2021) putting it at $110k to $160k.
6. What are the requirements of an online Master’s in Data Science Program?
As mentioned, the degree of difficulty, depth, and required homework in such courses have no virtual difference from those offered by traditional programs. The admission requirements are also similar.
For instance, the University of Washington’s Master’s Degree in Data Science requires applicants to have completed introductory-level programming courses that are equivalent to the university’s CSE 142 and 143 offerings. Also, it is a prerequisite for applicants to have completed Calculus III and Linear Algebra courses that are equivalent to Washington’s MATH 126 and 128. Furthermore, applicants have to meet the 3.0 minimum GPA for their previous 60 graded semester credits or their last 90 graded quarter bachelor degree credits.
University of Illinois online Masters of Computer Science in Data Science degree program is offered on Coursera. Application has similar requirements. For instance, applicants are required to have a 3.2/4.0 or higher GPA in the last two years of their undergraduate courses. Also, a strong background in object-oriented programming is also required.
Application requirements from these two programs are stringent. Delivered virtually, they are just as strict.
Bachelor’s degree from an accredited institution in the United States or a comparable higher-learning institution degree abroad
Completion of foundational math and statistics courses like calculus and linear algebra
Proficiency in programming software and languages (some accept entry-level)
Minimum GPA requirement (varies per university)
Recommendation letters (varies how many)
Statement of Purpose
Some require General Record Examination (CRE)
For international students, the TOEFL and IELTS Exams are required.
What are the technological requirements of students for online learning?
For a start, better-than-average computer hardware is required. There will be many courses that require computation-heavy tasks and assignments. And, of course, as everything will be online, one needs a great internet connection.
7. Courses to Expect in Online Master’s Degree Programs in Data Science
There are many requirements in the daily job of data scientists. Plus, data science inherently uses a multi-disciplinary approach. Given that data science is employed in different companies and a wide range of industries, there are many things to specialize in. So, there are many online degree courses for data science that you can take.
Some universities focus on specific business functions like supply chain management like Purdue University. Others have more general social science, business, and biomedical science offerings. However, there are common courses.
Common Courses in Online Masters in Data Science Program
Machine Learning. This course teaches students how to set up computers to learn by themselves through algorithms. Machine learning techniques are being applied in many innovations from self-driving cars to data-driven drug discovery in the biomedical sciences.
Data Mining. Data scientists are required to gather and make sense of data. And, in this course, students will learn how to gather relevant information to look for valuable and actionable data-driven insights. This has many applications, including business analytics.
Natural Language Processing. This course introduces students to deeper topics and cutting-edge techniques in improving human-computer interactions through natural language. Natural Language Processing (NLP) is used in tech products for translation, question answering, and grammatical error correction, to name a few.
Data Cleaning. Students in this course will learn how to deal with corrupt or incorrect records. They will be introduced to various data structures like tables and databases with the intent to detect inaccurate and irrelevant inputs.
Optimization. In this course, put simply, students will learn how to maximize or minimize real functions. Generally, this teaches them to find the best or optimal “route” or choice given different alternatives. Applications are many, including engineering, operations research, economics, and, of course, computer science.
Data Curation. Students in this course will learn how to organize and integrate data from various sources like databases. In this way, they will be able to acquire the knowledge and skills to create, manage, control/maintain, and validate data elements.
Data Visualization. This course allows students to explore techniques in visualizing data, in many cases, using a specific platform like Python and Tableau. Topics range from visual analytics to data storytelling.
Text Information Systems. Closely related to NLP, courses on text information systems provide students with knowledge, tools, and techniques in managing and analyzing text data en masse. Text information system techniques are used in many fields and businesses for social media recommendations and predictive analytics.
Database Systems. This course teaches both theoretical and practical learning about different kinds of databases, including relational and NoSQL ones. Students will familiarize themselves with techniques in using database systems like Google BigQuery, Amazon Redshift, SQL Server, and MySQL.
Deep Learning. In this course, students will get to know deep learning techniques in machine learning using deep neural networks that use multiple layers from raw data input. This has many applications, ranging from military decisions to financial fraud detection.
Programming Languages and Software. There are many different programming platforms and languages being used by data scientists across various industries today. So, expect that online Master’s in Data Science Programs offer many options. These courses range from developing general proficiency to deep specializations with particular uses. An example would be a data visualization course using Python exclusively.
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Top 10 Most Wanted Data Science Skills in the US on LinkedIn
Top 10 Most Wanted Data Science Skills in the US on LinkedIn Python: 76.13
Top 10 Most Wanted Data Science Skills in the US on LinkedIn SQL: 58.87
Top 10 Most Wanted Data Science Skills in the US on LinkedIn R: 57.92
Top 10 Most Wanted Data Science Skills in the US on LinkedIn Jupyter Notebooks: 53.41
Top 10 Most Wanted Data Science Skills in the US on LinkedIn Unix Shell/Awk: 48.55
Top 10 Most Wanted Data Science Skills in the US on LinkedIn AWS: 38.17
Top 10 Most Wanted Data Science Skills in the US on LinkedIn TensorFlow: 34.64
Top 10 Most Wanted Data Science Skills in the US on LinkedIn Tableau: 27.67
Top 10 Most Wanted Data Science Skills in the US on LinkedIn C/C++: 24.31
Top 10 Most Wanted Data Science Skills in the US on LinkedIn Hadoop/Hive/Pig: 21.26
Source: Software Strategies Blog, 2019
8. Things to Look for in an online Master’s Degree Program in Data Science
There are many things to consider when choosing an online Masters in Data Science Programs. But, probably, the most important thing to consider is choosing a program that would prepare you for the field of specialization that you want.
If you already are employed and wish to contribute more as an analyst for your organization, this basically narrows down your choices. But, if you just graduated in a related field and still have little idea of what industry you want to work in, then, maybe, it is better to choose a program with a more general approach.
And, while you are at it, it is also best to double-check each program’s accreditation. Usually, however, online Master’s in Data Science programs are accredited regionally and internationally.
Secondly, it is important to consider the reputation of the programs that you shortlist. For this, you can check out many resources. These include the university’s website. Their websites usually include profiles of notable graduates and where they work.
Moreover, if you choose to take your online course over a third-party platform like Coursera or EdX, you will easily find reviews and testimonials there. And, you can also ask questions on sites like Quora or Reddit to ask former or current students to gauge the quality and reputation of the program. You can also get on field-related forums to fish for organic answers and opinions. You will be surprised by how many people offer helpful and truthful answers.
In this way, you will not only get to know the program a little bit more but also build connections and relationships with data scientists that can help you as you go along.
Of course, the third yet probably the most important aspect to consider is the price and payment options. This will ultimately narrow down your choices as you have to work on a specific budget. And, in relation to this, you have to consider the length of program completion. This is a major consideration for work-life-study balance and long-term career planning.
Online Master’s Degree Programs in Data Science Are Worth It
Considering the demand for data scientists, a degree, from traditional or online programs, is totally worth it. The pay is well and would cover up the cost of education should you approach it right. And, more importantly, good online Masters in Data Science Programs will equip you with all the skills you need to start your journey as a data scientist.
Major companies and even SMEs are now building on expertise and skills on how to handle data and extract insights from them. And, in our highly digitalized world where tons of data are being created every day, institutions need more people to make sense of it.
Also, as mentioned multiple times, taking a Master’s Degree in Data Science, whether online or on-campus, are not really that different at all. An online student will build the same skills and knowledge that their on-campus counterparts will.
Of course, there is always value in face-to-face instruction. Intuitively, learning can be a bit easier as communication will be easier. Instructors and professors can point out things to work on easily and you can also get to ask questions and interact with them faster.
However, with the COVID-19 pandemic still rearing its ugly head, online education is the only choice left for many. And also because of the pandemic, online education delivery has also been improved when it comes to the quality of instruction, interaction, and accessibility. So, do not be surprised if online education becomes more popular and normal in the future.
If you are setting up for a business track in data science, you should also check out our business degree guide. Majors related to data science like data analytics and research analysis are becoming more in demand.
Bureau of Labor Statistics. (2021, March 31). Data scientists and mathematical science occupations, all other. Bureau of Labor Statistics.
Data Science Degree Programs Guide. (2021, April 2). 30 best master’s in data science degree programs 2019. Data Science Degree Guide.
Eadicicco, L. (2020, October 8). Apple and Google are looking for new ways to hire people without college degrees — but experts say college might still be your best bet for landing a high-paying tech job. Business Insider.
Glassdoor. (2021). Salary: Data scientist. Glassdoor.
Herd, C. (2021, March 4). Remote work 1 year later: The pandemic sent tech workers home — when and how will they return? GeekWire.
High Focus Centers. (2020, November 20). Online learning & teen mental health. High Focus Centers.