Learning the theory behind the application with the MS in Data Analytics Engineering
As a working analytics engineer with a bachelor of arts in behavioral psychology from the University of Maine, Marta found herself craving further education that would be relevant to her career path. After considering degree options like an MBA, she recognized the value of filling in the gaps in her theoretical knowledge with a more technical degree. Marta refers to this as “credentializing” what she already knew.
A technical program with easy admissions and flexible learning
Having had prior success with free courses on Coursera, Marta looked into potential opportunities to earn her degree online. While her initial search was for business-focused degrees on the platform, she quickly took an interest in the Northeastern Master of Science in Data Analytics Engineering (DAE), given it’s more of a technical degree. She recalls, “The admissions process was super easy. It’s nice that you could pay as you go, too.” As a learner with a full-time job, Marta also recounts, “The flexibility that was presented was really enticing to start the program. Just the fact that there’s so many start times was really beneficial.” Having vetted the degree, spoken with enrollment counselors, and noted friends and mentors who were proud Northeastern graduates, Marta ultimately made the decision to enroll.
Taking advantage of performance-based admissions as a lifelong learner
Enrolling in the DAE program was easy for Marta largely due to performance-based admissions. For learners with a STEM background, like Marta, this means skipping the formal application and jumping right into two introductory courses from the program. Upon receiving a B or better in both courses and providing proof of a bachelor’s degree, learners earn admission to the full DAE program. Initially a bit intimidated by this process, Marta advises other lifelong learners like herself, “Just try it! Worst case, if you don’t get into the program, I think it’s nice that you’re still learning something.”
Self-paced technical learning and advice for non-technical students
Now one semester into the program with three to go, Marta is taking courses like Python and Data Visualization. The first coding assignment was an eye-opener, in which she could test her skills and receive immediate feedback from TAs. She found the flexible, self-paced learning environment immensely helpful and appreciated the consistent feedback throughout the semester, especially due to the rigorous coursework. Marta notes spending 25–30 hours per week when taking two courses at a time. Even non-technical learners can confidently jump in, make mistakes, and learn as they go. Like Marta says, “Don’t worry about messing up your computer—everything is saved somewhere.” She also encourages non-technical learners to complete the weekly readings, dive into office hours, and lean into help that can be gained from fellow students. She believes these resources are a goldmine for gathering insights and building confidence.
Looking toward the future as a DAE graduate
Marta’s journey speaks to the power of pursuing a formal education to enrich self-taught skills and open new professional avenues. Her desire to take her prior knowledge and “credentialize it” is already growing her confidence, capabilities at work, and future career potential. For those contemplating a similar path, her story serves as an inspiring blueprint.
