Degree, Boot Camp or MOOC? How to Pick a Data Science Program
In a session at the Data Science Innovators Conference 2023, Sasha Tomic of Boston College's Woods College of Advancing Studies compared degrees, boot camps and MOOCs for analytics careers. He shared job-posting data on master's requirements and a checklist of questions to ask any program.
By The AI Enterprise Magazine Team4 min read
Key takeaways
- Start with your objective. Entering the field, switching careers and managing teams call for different programs.
- A bachelor's is the floor. Citing Lightcast postings, Tomic said most statistician and data scientist roles ask for a master's or PhD.
- Build on a degree. Boot camps and MOOCs work best when paired with an underlying degree.
- Check reputation locally. A regional school can carry more weight than a famous one in its home market.
- Ask relentlessly. Questions on faculty, class size, placement and career services separate strong programs from weak ones.
In a session at the Data Science Innovators Conference 2023, Sasha Tomic, program director at Boston College's Woods College of Advancing Studies, laid out how aspiring and working data professionals should choose between degrees, boot camps and MOOCs. Tomic, who also serves as associate dean for strategy, innovation and technology and runs master's programs in applied economics and applied analytics, said his goal was to help attendees "ask better questions" rather than hand out answers.
What should you decide before choosing a program?
Tomic said the first decision is the type of credential: a for-credit degree or certificate, a not-for-credit course (anything from university-run courses to LinkedIn Learning or a boot camp), or a MOOC. Then comes the format, whether face-to-face, hybrid or online. Online options are far more popular after the pandemic, he said, but they raise their own questions.
The starting point is the objective. Are you entering or switching into the field, or already established and managing teams? Do you want to be a better individual contributor or manager? Are you short on technical skills, soft skills or both? And what education do you already have?
Do you need a master's degree for data science?
Tomic noted at the outset that he runs two master's programs and was not making a sales pitch. He showed U.S. data on education attainment over 20 years, with master's degrees growing most dramatically. Citing Lightcast job-posting data, he said most postings for statisticians and data scientists ask for a master's or PhD, while roles such as database analyst and BI developer more often ask for a bachelor's.
In his reading, a bachelor's is the bare minimum, and he said despite news stories on dropping degree requirements, there is no huge inflow of sub-bachelor's qualifications in these jobs. He showed salary data suggesting considerable returns to master's and PhD levels, with little difference between the two for data science. Tomic advised attendees to strongly consider a master's.
What are the pros and cons of degrees, MOOCs and boot camps?
For degrees, Tomic listed well-established credentials, broad education in communication and critical thinking, dedicated faculty, career services and alumni networks. The cons are time (a master's can take one to three years), monetary cost, non-monetary cost for people who are working or caring for family, and programs that can be too theoretical, too fast or too slow.
MOOCs such as Coursera, LinkedIn Learning and Udemy are topical, self-paced, cheap or free, and timely. Their downsides are no real guidance, evolving recognition, no direct faculty contact and usually no career support.
Boot camps sit between the two, Tomic said. They offer faster completion, strong industry connections, practitioner faculty and often lower cost, though some run into the tens of thousands of dollars. Recognition is still evolving. He described a math PhD who attended a boot camp afterward and then moved into data science as a winning combination: a well-recognized degree plus practitioner appeal.
What questions should you ask a program?
Tomic offered a checklist for any format. Ask about the institution's reputation, and whether it is local, national or international. He said research shows reputation is the first thing employers look at, and that a local school can beat a famous one in its home region. Also ask about full-time and part-time options, whether faculty are researchers or practitioners, student engagement and satisfaction, class size, placement record, career services, and how the program stays timely.
For online programs, ask whether the degree is treated as equivalent, whether courses are synchronous, whether courses are taught by their creators or by facilitators, how available faculty are, and how university resources reach online students.
How can you verify a program's reputation?
In the Q&A, an attendee asked how to check reputation objectively. Tomic suggested rankings such as U.S. News and World Report, but said the better step is research: look on LinkedIn at where people in the jobs you want went to school, set up informational interviews, and contact alumni. On big-tech certifications, he said they work best paired with a degree and noted people hitting a wall moving into management without at least a bachelor's.
The bottom line
Tomic said there is no correct answer to the questions he posed. His summary: have at least a bachelor's, consider a master's, treat boot camps and MOOCs as valuable when built on an underlying degree, and choose the format honestly. His final advice was to be relentless: "If they can't answer these questions, run away."
Where to continue learning
AI Connect continues to host education and career-focused conversations alongside its enterprise programming. The 2027 schedule includes 24 free live webinars in four series: the AI x Enterprise Panel Series, AI Demo Days, Agentic AI Showcases and the Plug & Play Series. Details are at /webinars/, and registration for 2027 events is coming soon.
Frequently asked questions
Do you need a master's degree for data science?
Tomic cited Lightcast job-posting data showing most statistician and data scientist postings ask for a master's or PhD, and advised attendees to strongly consider a master's.
Are boot camps worth it?
He said boot camps offer speed and industry ties but have evolving recognition, and work best on top of an underlying degree.
What are the downsides of MOOCs?
Tomic listed little guidance, evolving recognition of credentials, no direct faculty contact and usually no career support.
What should you ask about an online program?
Whether the degree is treated as equivalent, whether classes are synchronous, whether courses are taught by facilitators, and how available faculty and university resources are.
This article is based on remarks by Sasha Tomic, Program Director, Boston College - Woods College of Advancing Studies at Data Science Innovators Conference 2023 on April 12, 2023. More coverage: More AI Connect Events.
Filed under: People, Culture & Leadership
