Degrees Are Not Vocational Trainings

There is a growing misunderstanding about what a university degree is meant to do. Specially in the IT industry. Many people expect degrees to work like vocational training programs. This expectation creates frustration for students, employers, and educators alike.

A degree is academic by nature. Its primary goal is to provide academic value, not to train someone for a single, specific job role. Degrees focus on building strong foundations: critical thinking, problem-solving, theory, and long-term understanding of a field.

This does not mean degrees are useless for careers.

Some degrees are designed to produce professionals for clearly defined roles. A good example is MBBS, which leads to a specific profession. However, this is not how most degrees work. Especially in fields like IT, engineering, or management.

At the same time, it is also incorrect to say that degrees only deliver theory with no relevance to jobs. Degrees aim to prepare students for a range of job roles within an industry, not one guaranteed position. They provide a broad academic base that allows graduates to adapt, learn, and grow over time.

What Are Vocational Trainings?

Vocational training programs are different by design.

They focus on training people for specific job roles. These roles usually exist in industries with stable and predictable demand. Examples include plumbers, welders, carpenters, electricians, and mechanics.

Vocational courses are practical, role-focused, and short-term. Their success depends on how stable and clearly defined the job market is.

IT Is Different

The IT industry does not work like traditional vocational industries.

Technology changes fast. Job roles evolve quickly. Tools, programming languages, and frameworks rise and fall within a few years. Because of this, it is very difficult and even impossible to design a long-term vocational training that guarantees relevance.

What is in demand today may be outdated tomorrow.

This is why IT degrees focus on fundamentals: algorithms, systems, logic, design thinking, and problem-solving skills that survive technological change.

Misunderstood by Both Companies and Students

This confusion affects both sides of the industry.

Many IT companies expect IT degrees to train graduates exactly for their internal job roles.
Many students expect degrees to train them for a specific role and guarantee employment.

Both expectations are unrealistic.

Degrees are not job-role factories. They are foundations for lifelong learning.

A Shift in Mindset Is Needed

If we want a healthier IT ecosystem, we need to change how we think.

Degrees should be respected for what they are: academic programs that prepare people to think, not just to follow tools.
Job readiness comes from continuous learning, not from degrees alone.

Understanding this difference benefits everyone including students, employers, and the industry as a whole.

What does “learning fundamentals” actually mean in practice?

“Learn the fundamentals so you’ll succeed in your endeavor” This is a common piece of advice people often give. You’ll frequently hear it when asking how to secure your career or how to learn a new technology, etc.

In today’s world, overflowing with knowledge and information. This advice is vague and it leaves us with unanswered questions. What exactly should I learn as fundamentals? How can I be sure I’m learning the right things?

So when someone says “learn the fundamentals”, the right response is:

“Which fundamentals, and how deep, based on what I’m building?”

Physics & Electronics (Atoms, Electrons, Gates, etc.)

Necessary if you’re doing hardware design, building compilers, or working with embedded systems. Not necessary for typical software developers.

Computer Architecture & Operating Systems

This area consists of concepts CPU cycles, memory hierarchy (RAM vs cache), processes, threads, virtual memory, file systems.

This is necessary if you’re into systems programming, performance tuning, or OS development.

Programming Language Theory & Compilers

This is about syntax, parsing, type systems, interpreters vs compilers.

This is necessary if you’re building tools (like linters, and transpilers), designing new languages, or deep into back-end design.

Data Structures & Algorithms

Concepts and implementation of arrays, linked lists, trees, hashmaps, sorting, recursion, time/space complexity.

This is essential for all developers. They underlie everything, from efficient code to debugging performance issues.

Networking Basics

This is about the theory of HTTP, TCP/IP, DNS, client-server model.

This is necessary if you build web apps, mobile apps, APIs, etc. But you don’t need to know TCP flags or OSI model layers deeply unless you’re in DevOps or network engineering.

Databases & Querying

This is about the design of databases, SQL, indexing, normalization, and transactions.

Learning databases is essential for most types of app developers. You can’t avoid data persistence.

Version Control, Build Tools, Deployment

This is about learning Git, CI/CD, testing, and packaging tools.

It is required for modern software development in teams and production settings.

Software Architecture

Software architecture becomes fundamental once you move from building apps that “just work” to systems that are “designed to last.” Architecture is essential at certain points in a developer’s or engineer’s journey. especially when working on large-scale, long-lived, or team-based systems.

Linear Algebra, Statistics, Programming (Python) and ML Theory

The fundamentals required for AI vary depending on the role you’re aiming for.

whether you’re a machine learning engineer, data scientist, AI researcher, ML ops engineer, or even a developer using AI APIs these are the core knowledge areas required for that.

Final thoughts:

My list is limited to few common IT and Computer related fields. There are many more.

When learning fundamentals, you don’t need to “boil the ocean” of computer science. As a practical use, go just deep enough to understand what your tools abstract away. And just go deeper when things break, or performance matters.