University vs training programs: Which route is best?
Updated: Jun 9, 2025
The data industry is booming and it needs a new wave of talent.
From machine learning to cloud engineering, and from sustainability analysts to cyber security professionals, the world of data is full of career paths that didn’t exist a decade ago. But as demand grows, so does the big question for aspiring professionals:
What’s the best way in?
For years, the default answer was simple: go to university, get a degree, land a graduate job. But that pathway is no longer the only (or even always the best) option.
With tech trainee schemes and alternative learning programs on the rise, the data industry is finally starting to value skills and experience over credentials. So which route should you choose: university or training program?
The case for university
University is still the most traditional route into the data industry.
Pros:
Deep academic grounding: University degrees (especially in computer science, mathematics or data science) offer a strong theoretical base that can give you an edge in complex or research-led roles.
Access to networks: University life often comes with access to alumni groups, career services and research projects, all of which can open doors.
Versatile qualifications: A degree is still a prerequisite for some specialised roles, particularly in data science, AI and quantitative analysis.
Cons:
High cost: Tuition fees and living expenses can leave students in significant debt.
Delayed work experience: Many students graduate with little to no work exposure.
Not always aligned with industry needs: Tech evolves fast. Academic curriculums? Not so much. Some grads find they still need to “retrain” to meet job expectations.
The case for training programs
Trainee schemes in tech and data are exploding in popularity, and with good reason.
Pros:
Learn while you earn: Paid experience in your chosen field from day one.
No student debt: Programs are fully funded, so you can build your skills without taking on loans.
Industry-ready skills: Trainees often learn on the tools, languages and platforms employers are using right now.
Faster career progression: By the time uni grads are finishing their degrees, trainees may already have two to three years of experience and promotions under their belt.
Cons:
Specialising early: Some training programs are narrowly focused, which could limit future flexibility unless supplemented with further learning.
Harder to switch fields later: Without a broad academic background, moving into research or pivoting roles may require more self-funded study.
Limited availability: Not all roles or companies offer training options yet, although that is changing.
If the training route is calling your name, check out STACK’s newly launched data center programs in Italy, Norway and Switzerland, that are welcoming a fresh intake of talent in 2025.
So… which is the "best" route?
The truth? There’s no one-size-fits-all answer.
Instead of asking, “Which is best?”, ask: “Which is best for you?”
Answer these questions:
Do you enjoy structured academic learning, or thrive more with on-the-job experience?
Can you afford university or would earning while you learn be a better fit?
Do you already know what industry you want to pursue, or are you still exploring?
Are you someone who learns better through theory or practice?
The industry perspective: Skills over school
Today’s employers generally don’t care where you learned, it’s more about what you can do.
Whether you come with a degree or a training program under your belt, what matters most is your:
Problem-solving ability
Technical skillset (Python, SQL, cloud platforms, etc.)
Willingness to keep learning
Communication and teamwork
In fact, companies like Google, IBM, EY and STACK have dropped degree requirements for many roles altogether, focusing instead on practical tests, portfolios and experience.
The hybrid route
More and more learners are taking a hybrid approach:
Starting with a training program, then topping up with part-time degrees or certifications
Going to university, but adding internships, bootcamps and freelance work along the way
This blended path combines depth and experience, and it’s increasingly becoming the norm.
Final takeaway
There’s no “right” path into the data industry, only the right path for you.
Whether you choose to start in lecture theatres or data centers, the industry is wide open and hungry for talent. So long as you’re willing to learn, adapt and apply your skills, there’s room for you at the table.
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