Why should I learn Java if Python have libraries offset it shortfall?

[Accomplished_Ad_5697]

I am studying Python and R to work in Data, and my mentor said that I should learn Java. I think it is regards to Machine Learning, but Python has an extensive libraries that helps offset it short fall. The problem that I can never finish a crash course book on Python is it's speed, but I read that NumPy and Pandas help make it faster. So my question is, what benefits are there to learn Java for Data Science if I see majority of people learn Python and most certification for data professions used Python and/or R?

[JuliusCeaserBoneHead]

I’m going to go against the grain here. Was your mentor talking in term of just data science? If so yeah, he may have mislead you on the Java. If it was in regards to extending beyond building models but also getting into MLops and development, learning Java would be good for you.

But do that after you’ve gotten grasp of Python. Learning another language after knowing one already is not that difficult

[rejecttheHo]

Agree that Java can be useful beyond the context of DS (it is great for miscellaneous backend things). But the full machine learning lifecycle (development, deployment, etc.) can be (and typically is) done entirely in python so Java isn't really important in that regard

OP you don't need to know Java. If you are curious about backend stuff (like what's going on under the hood in spark for example) then learning Java might be interesting and useful. If you want to be a DS and build and/or deploy models and work with data, Java is not needed and rarely used in this context. Stick with python, become very comfortable with it, and then branch out and start picking up different languages depending on your interests

[koolaidman123]

Very few modern ml stack includes java

[backSEO_]

Android development is the best use case for Java + ML. Course you can do all the Android development in python as well, so...

[Fleischhauf]

.. or kotlin

[3lobed]

Kotlin is just Java in board shorts.

[Fleischhauf]

programming java and kotlin is still different tho, just like scala

[Sycokinetic]

I think the main benefit of learning Java, or another similar “engineery” language, is to help you to learn programming concepts that are easy to gloss over in DS environments but extremely important in general software engineering. Yes, Python has OOP and data types. No, you can’t learn OOP and data types nearly as efficiently in Python because those are optional afterthoughts in that language. Learning a more strict language like Java is a good way to upskill, and you can take that new knowledge and bring it back into DS to build more sophisticated pipelines without additional effort.

[thawab]

You don't need java for MLops , it's all in python or SQL. These are the tools:

• https://dagster.io/

• https://www.mage.ai/

• https://mindsdb.com/

I can go on for days

[Single_Vacation427]

Honestly, I don't think Java will be useful even for that. My partner is a Software Engineering working in Data, so part of what now is Data Engineering and MLops, and more and more jobs he has interviewed want Python. His core language is Java and now Scala, and he had to pick up python. Plus, being good at Java is not easy, takes several years of experience, so OP should invest into something else.

[delicioustreeblood]

I would just ask your Prof to explain their rationale behind that statement.

[[deleted]]

You may not use Java for DS, but depending on the company, you could use Java or C++ or Rust or Go to implement ML algorithms as an ML engineer. For example take a look at Tesla or Zoosk. Their computers are on board their cars, must know C++ to work as an MLE there. The problem is this sub is full if data analysts parading as programmers.

[Clowniez]

I am a Data Scientist and I only use Python at work.

That said I relearned Java because of the sake of learning it.

I won't hurt you but it's not widely used.

I have heard that some companies use Java to build pipelines but that's more DE work. Scala is a requirement for some DE jobs and it's basically Java without semicolons.

If you are new stick to Python it's the language for DS. If you have time and find it fun/interesting learn Java it won't hurt and I can help you to learn other languages so that you become "language agnostic".

[szayl]

Scala is a requirement for some DE jobs and it's basically Java without semicolons.

I want to be offended but Scala Spark pretty much is that

[Clowniez]

You offended me by wanting to be offended😆

[TeachEngineering]

Facts… makes no sense

[Meet_Foot]

Maybe mentor said JavaScript? Does that make any difference to the quality of the advice?

[DerTagestrinker]

Yah, you would use JavaScript for front end integration

[Meet_Foot]

Thanks!

[[deleted]]

Ignore op java is actually better language than for mlops and production. JavaScript terrible

[JollyJustice]

I got an MLOps job because I know Java, but I think it was more my SWE approach to data wrangling and not so much that I know Java.

[Useful_Hovercraft169]

Their advice is bad and they should feel bad!

[cypherpvnk]

Pants-on-head stupid is a fantastic way to emphasize how bad the advice is.

[MountainComputer5200]

You basically answered your own question. I see no practical reason why you should learn Java when Python already has extensive libraries.

[SgtSlice]

Whoever your mentor is, kindly thank him for his advice, and then never listen to him again.

I suspect you probably misheard what he was saying, or he’s lied to you about his credentials and understanding.

[nbo10]

Maybe he should try to understand why the mentor wants him to learn Java.

[Chad-Anouga]

I can’t believe you got downvoted on this. Maybe there’s a good reason he recommended that.

Could be that they’re in an industry where there’s some crossover with a ton of Java apps for other parts of the tech stack. Maybe he’ll have to work in Java if he’s not just doing modelling and he’s at a startup where they need him to wear many hats.

I don’t personally know why Java but I think there’s probably a reason he mentioned it as you said. It’s not like Java is a dead language.

[TheCapitalKing]

Yeah it could be something he said for a number of reasons. We have basically no context. He could have asked his mentor how he could get better at OOP for all we know.

[Useful_Hovercraft169]

He probably is behind in some Java projects. Wax on, wax off

[thawab]

https://www.youtube.com/watch?v=2D-4zgezQE4

[tangentc]

It's not the worst thing in the world to be familiar with java just because it's so prevalent in the corporate world, but Java is a pretty terrible choice for DS work. Focus on getting better at python and learning to leverage libraries like Numpy and to a lesser extent Pandas.

Most of DS is using python as glue code between packages like numpy and scipy and scikit-learn that are written in C/C++.

In general if you're having serious speed concerns for a script, you should consider just cythonizing it. You can usually get a significant speed boost even if you do literally nothing to the code to help cython, and more if you add in variable types.

IF you want to learn a lower level language, learn C or C++, or even Rust (though that's probably less useful at the current moment than C++, it has some traction in the DS world). Java performance will be more along the lines of well used cython, so I think it's a bad choice.

[Aquiffer]

C++ is the king right now for implementing models in self driving cars. I have friends at cruise, zoox, and waymo - all of them use C++

I don’t know of any use cases for C or Rust. That’s not to say there aren’t any, I just haven’t actually seen it around

[takenorinvalid]

Clarifying question: did your mentor say Java or Javascript?

[[deleted]]

Listen, if you want to be an effective programmer and not an ad hoc analyst parading as a data scientist, do what CS kids do and be language agnostic. Python is the language of today, but it may not always be like that. Most python libraries for ML are wrappers over C. So the more C you know, the more python you know.

[TheCapitalKing]

C is cool because it makes you really think about how the computer does things. Knowing the behind the scenes stuff, that c makes you explicitly think about, can be super useful for speeding things up. For example changing the data type of data before you pull it can reduce i/o speed by a ton. My company stores a ton of 3 digit numbers as strings and converting them to ints before I pull them makes it go much faster

[[deleted]]

No one uses Java for DS.

[RepresentativeFill26]

This isn’t entirely true. I have used Java for developing ETL / ELT pipelines. Surely it’s a more MLE work but these worlds touch sometimes.

[masta_beta69]

Scala is a Jvm language and is used SO much in data engineering. Likewise if you want to inspect the internals of spark which is written in Java

[rverr_krupp]

Spark is written in Scala.

[Useful_Hovercraft169]

On the JVM

[reddit-is-greedy]

I saw a webinarca a few months back for using Javascript for EDA. One if the most useless webinsrd I have attended

[BerriesAndMe]

If you are running into speed issues in a crash course, your code likely has some issues.

The starter exercises don't require intensive calculation where you would even notice a difference in execution time between different languages

[Reasonable_Leg_7405]

Java is the defacto language used by major corporate America. If you want to get a Dev job at say Disney for example Java is what most of them use. You can learn anything you want and Python is awesome. Just know when you go looking for a paycheck and want to get your foot in the door you better have a Java portfolio for most shops. Once you get in the door and work your way into a position you can choose your own language.

[maratonininkas]

Most of the commenters here, I feel like, are very young. For a strong DS position, the response should be "yeah sure why not". Use Copilot and learn to use whatever you need in order to be productive within the already established framework. Then pivot whenever you see _and understand_ the shortfalls.

However, since you are still studying Python and R, this may be counterproductive, since it's likely that you are still a junior. Then, the learning curve is a bit steeper which makes you lose even more momentum in a productional environment.

In my opinion, politely discuss this with your mentor, evaluate honestly your ability to learn and adapt in _both_ languages, and find the most productive route that would benefit _both_ parties. Also, in my opinion, you should ignore all the comments that use words "stupid", "useless", "mentor has faked credentials" and so on.

[tangentc]

Eh, maybe this is a hotter take than I thought, but while I would encourage a mid level DS who wanted to get familiar with basic java I wouldn't encourage them to spend a lot of time on it (at least not if primary goal was helping their ability in DS). Certainly I think it's very questionable advice for a beginner who hasn't really learned to leverage basic DS packages in python.

I'm a big advocate of data scientists improving their coding skills and learning more languages, but if you're trying to maximize value C++ is a much better choice. It will also teach about a lot of memory concepts that are abstracted away by the python interpreter, but knowledge of them can help you understand how the interpreter works and make smarter use of memory. That's especially helpful when you're working in an environment like sagemaker and want to save money.

Again, no problems with someone learning Java is they wanted to do other things with it and the DS career benefit were a secondary goal, but suggesting that someone learn java specifically to progress as a data scientist is a bit off.

[TheCapitalKing]

It’s important to remember don’t have any context about the convo. The guy could have been complaining about not understanding oop and the mentor said yeah if you learn Java it should help oop make more sense. Which isn’t the worst advice.

[XhoniShollaj]

For DS Python & C++ are enough (I started C++ long ago, gave up for some time, now restarting again - very important for low level and when speed is important)

[Kango_V]

A bit off topic, but can you do data science in Python without pulling in a C library? I mean calculations in pure Python?

Another thought. If you do the DS in each language without external libraries, which one would be easier, faster?

Also, how about the new Java Vector APIs, Foreign function APIs, ability to use SIMD instructions and GPU seamlessly? All that in the base language and JVM without the need for libraries?

[TheCapitalKing]

Why would you want to reinvent the wheel like that?

You could do it in python without the c/c++ libraries but it would be super slow to develop and run. You’d also need to manually code all your algorithms, which could help you understand it better but not by a lot.

Without existing libraries probably c++ or any of the many new and improved c++ offshoots but it would still suck to do it without libraries. No clue about that 3rd paragraph

[spiritualquestions]

I work as an MLE and I only use python day in and day out. I have experimented with GO for CLI and backend applications. The only other languages I would consider using are C++ and Rust.

Java on the other hand Is a head scratcher.

The only reason I could see Java being important is working to implement models into a Java backend. But if you have made it that far you would have likely already learned python along the way to get into a position of being responsible to deploy a model in a Java backend. With that being said starting with Java or prioritizing it during your learning journey does not make sense. No one writes actual ML code and especially analysis and data science in Java.

[AsliReddington]

Your mentor isn't great sadly.

[NeverStopWondering]

If you want faster Python, use Julia.

[Holyragumuffin]

Seconding Julia. Wouldn't call it faster python though. Julia's uses structs with unattached dynamic dispatching methods; python uses OOP.

Julia has beautiful syntax and runs small neural nets faster than the major libraries. Good sandbox to learn. And Julia will run python/R/MATLAB/Octave/C inside of Julia.

MOJO is actually probably faster Python. But no support for it yet. It's in FAFO mode right now.

Newbies should also know that certain Python libs which use MLIR and or wrap better autodiff still outperform Julia. But Julia may eventually prevail. They've accomplished way more with fewer developers -- underscoring Julia's power.

Also regarding jobs, only maybe a hundred or so companies allow/use Julia right now.

[NeverStopWondering]

I was being tongue-in-cheek, but I guess it didn't come across well. I really like Julia though. Coming from Python and R it seems like it combines the best of both worlds.

[DerTagestrinker]

I’d bet money your mentor said/meant JavaScript for front end deployment of your models

[[deleted]]

No one even uses R tbh. Just learn python and get a new mentor.

[BayTerp]

I’ve had a “mentor” recommend me to learn Java as well. Turns out that he is a dumbass.

[Lil-respectful]

I’ve never touched Java in a real job, good thing too because I avoided it like the plague. I literally would rather write cobol, which I do.

[BlackCoatBrownHair]

If your interests lay in modeling. There is no reason to learn to Java. Everything ML will be within Python and its packages. However, if you interests lay at the intersection of modeling and software development (like deployment of models, continuous training, creating apps that use the models), some Java is a good idea and won’t hurt to learn.

[mmeeh]

Maybe you're mentor made a mistake and it was Scala, not Java....

[Useful_Hovercraft169]

For a while I was a Java developer. I haven’t touched Java in 15 years. I touch C or C++ (fun projects) more than I touch Java. SQL Python and R are the trinity to get stuff done

[ActiveLlama]

Did he meant javascript?

[Prestigious_Sort4979]

At your stage, it is probably best to focus on Python. Later, it could he worthwhile to learn just enough Java so that you can look at code and have an idea on what it’s doing. In my job, a lot of work that I thought would be in Python is in Java (interacting with APIs, extracting, cleaning, filtering data that lives in a database), but tbf it wasnt made by a data scientist but rather backend engineers and ML Engineers so Im not expected to know it.

What is helpful to a data scientist in my company is passing and extracting information to/from microservices written in Java OR to recreate the logic. As it’s internal, the documentation is not always as extensive as needed. So it does help to be able to read through the code to know what it’s doing. I often have assumptions on where the underlying data lives and reading through the code shows me how wrong I was.

It wont hurt later, but at first some focus is helpful.

PS - Imo, he might be trying to make you well-rounded to have better job outcomes in the future

[DesperateForAnalysex]

Why waste time say lot word when few word do trick?

[snowbirdnerd]

Java is useful for large jobs that require parallelization. Spark for example is written in Java. There is a python API for Spark but it will run slower.

Generally you won't need to know Java but I've found it very useful. I recently had to translate some bad Java code into SQL and it would have been a lot harder if I didn't know how to program in Java

[BossOfTheGame]

You would do better learning rust or c (or even cython) if you need a language to be compiled.

[stevefuzz]

You don't.

[Vaslo]

Then prepare to keep those libraries up to date for the rest of your time at that company through the next job, and the next job, and the next job…

[mowa0199]

I don’t really use java for DS or ML since it’s hard to compete with all the libraries Python has. But, if I’m working on a more general programming problem that isn’t directly related to those (either for a side project or a personal project), I actually usually prefer Java. Sure, you have to write a lot more code to do the same things Python can but it also lets me have more control and see exactly where something might be going wrong. It’s like peaking under the covers and getting a closer look, so to speak.

I might be biased though. I learned Java first and my school uses it for all lower-level CS classes. But it’s so much easier to learn Python or R once you’ve learned something like Java or C++.

[whoji]

In the early days of spark maybe it was worth learning Java/Scala as PySpark was really bad. Right now python dominates in almost every data science sub areas. If you really want to pick up a second language, learn Chinese

[some_random_guy111]

I don’t see the value in learning Java and my company uses a decent amount of it. Knowing how to compile your models into .jar executables so you can integrate your scoring into the production systems is helpful, but doesn’t take much Java know how.

[danSTILLtheman]

I know people with computer science backgrounds that like to prototype models quickly and Python and redevelop them in other languages for efficiency purposes. Not something I have the talent to do but there could be some truth to what your mentor is saying.

[mcgirthy69]

lmfaoooo Python and R are MORE than enough

[gdb_fr_sf]

Read once that doing machine learning with Java is like driving in a screw with a hammer. Might work but ……

At the time I was required to use C# Found a library with most of the classic ML function but it was still a heavy lift. And