University student: Finished Python OOP basics. Which path is actually "future-proof" in 2026?

Posted by PutridFly7386@reddit | learnprogramming | View on Reddit | 17 comments

Hey guys,

I’ve just wrapped up my "foundational" phase with Python. I’ve got a solid grasp of the basics and I’m comfortable with OOP.

Now I’m at a crossroads and honestly, a bit overwhelmed by the options. I’m looking for a path that’s "future-proof" (I’m studying at university right now so I will try to enter the job market soon).

I’m torn between:
-AI/ML engineering,
-Data engineering,
-Backend dev.

For those working in the industry right now – where are you seeing the most growth for juniors/mids? If you were starting over today with just OOP knowledge, which rabbit hole would you jump into first?

Thanks for any advice!

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nomoreplsthx@reddit

The idea of anything being future proof is absurd.

History is governed by random and capricious chance. Technological and scientific innovations are completely unpredictable and can obsolete entire industries. Economic and geopolitical forces are inherently chaotic and cannot be predicted in the long term. Nations plunge into war because a leader was in a bad mood. An untimely death can collapse an empire. Markets are so close to random most experts think they literally cannot be predicted. Most explanations are comforting stories. And even when we can explain things after the fact, the past provides little guide to the future.

And this is to say nothing of the absurdity and randomness of individual lives - death, accidents, changes of heart or character.

You could pick a field and it could be gone in 5 years. You could pick a field and it could be the most in demand field in the world in 5 years.

Seek to be a good person - to live the kind of life you would be proud of living even if everything went wrong. Don't do things because of the future advantage you think they will get you. Do things because of their worth right now. Anything else is chasing a fantasy.

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Grand-Resolve-8858@reddit

This is beautiful and all but pretty sure OP still needs to pick something to study next semester lol

Look man between those three options backend dev probably gives you most flexibility. You can always pivot into data engineering later since there's overlap and ML stuff you can pick up on side projects. Starting with backend gives you solid foundation that transfers everywhere

I picked backend first too when I was deciding and it worked out well. Much easier to move between different areas once you understand how systems actually work at scale

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Mother-Influence-815@reddit

Nothing is future proof. Nobody can tell you what will happen in the future.

The only thing you should really learn is how to learn so you can adapt and keep up with the changing world

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Tempmailed@reddit

Brutally honest, future is pretty unstable. Especially the CS market. Man that's going get tougher. Even the seniors with decade of experience find it hard get into market and it seems to get worse over time.
Luck at the end

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babaqewsawwwce@reddit

Use those new found skills to start building then take a university introductory business or management course. Read the sections dedicated to scanning the environment for threats and opportunities(changes to the business landscape) and stay relevant with your skills.

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Any-Cardiologist1641@reddit

Honestly , In my opinion all 3 future paths have good scope.
What matters the most is what you enjoy in doing:
Backend - building systems/API
Data engineering - handling large data pipelines
AI/ML - Models , Analytics
Since you already know OOPS in Python backend development will be the smoothest part for you to work on real projects and get good internship. You can later pivot to AI/DATA because string backend fundamentals are valuable everywhere.
Instead of chasing future proof path , become really strong in one stack.

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Formal_Wolverine_674@reddit

Backend plus strong fundamentals is honestly still one of the safest paths because it teaches transferable skills that also help later in AI, ML and data engineering

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pastpresentproject@reddit

If you have a foundation in OOP, then just jump into Data Engineering and you're guaranteed to land a spot, man. It's not as overpowered as AI and you'll avoid the cutthroat competition in traditional backend development. Just add some SQL and Spark and you'll be raking in the money, man!

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SnooDoubts8688@reddit

To set some expectations, AI/ML engineering will require a ton of math, and you will likely need to do a Masters, even a PhD. It's an entirely different type and level of beast compared to Python OOP basics.

Fact of the matter is, currently it is difficult to see any growth for jr/mids. The only growth is happening around AI, which is dominated by people with Masters/PhDs, which by the time you graduate with the credentials may be less in demand. No one knows. In the future datacenter technicians may be more in demand because we need to manage all the datacenters. Or electricians, who knows.

Maybe you realize you like stats and drawing conclusions from numbers, data engineering can be a good fit. Maybe you enjoy low-level languages like C, or enjoy seeing your software translate into hardware, embedded or networking could be a good fit. Heck, even robotics are on the rise these days, so maybe look into that too. But in essence SWE will look a lot different as time progresses, so just be open to wear many different hats.

Good luck!

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bird_feeder_bird@reddit

Purely in terms of job security, probably embedded, firmware, and systems programming. Especially in the medical or defense indistries.

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sch0lars@reddit

Not sure I would recommend embedded software engineering. I worked as an embedded SWE for awhile and it’s an incredibly small, highly competitive area and most of the people with whom I worked had EE backgrounds. It may be stable, but there are not a lot of jobs for it and electrical engineers have the upper hand there.

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LeeRyman@reddit

Be a sponge for knowledge on a breadth of topics, and practise first principles every day. Nothing says someone I can rely upon no matter the product, application, or situation than someone who demonstrates adaptability and understanding of fundamentals and ability to apply those to solve problems.

I would also want to see good business analysis and communication skills, good planning, versioning, test and release practices (I.e. engineering rigor). All this can be practiced at uni during your assessments and team projects.

I think I graduated having done assignments in ASM, Java, C on various archs, MSVC COM, VB6 (yes, I'm old), PLSQL, VHDL. We looked at DS&A, data modelling, entity-relationship modelling, OS and memory archs, distributed computing, networks and protocols, UI, not to mention other integration stuff (my degree involved electrical and electronics).

If I was hiring, it would be a very rare event where I would want someone who is a boffin in one language or topic only, I would rather have someone who specialises in two or three, demonstrates engineering processes, but is also a generalist in technology.

When picking courses, I think there should a ballance between those that are fun and interesting, and strategic choices that will expose you to practical and transferrable skills. The bandwagon of today will always be different tomorrow, so don't worry too much about those.

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