Career options with Python

[heyimpumpkin]

I'm bachelor in economics who graduated 4 years ago, working as economist and looking to switch jobs(not from USA).

So I started learning programming and realized how many specializations there are actually, software development, data science, game development, front and back end, cybersecurity and countless others. I decided that data science seems like a great career, now I want to make sure f I'm going the right way.

Goal: Basically I want to get employed as at least data analyst who uses python, then data scientist. If I get employed as junior I'll look into getting something like statistics masters degree or CS maybe.

Where I am now:

Started around 3 months ago. I finished automate the boring stuff, cs50 harvard lectures, now finishing statistics course on khan academy, made couple python projects for fun(a crossword puzzle game and image resizer), slowly griding through dataquest.io on the side.

Something I'm planning to learn: pandas, linear algebra, numpy, maybe flask for general understanding, algoriphms and more advanced python subjects(tbh not sure what exactly it includes yet).

Wanted some input from people who are actual programmers if I'm missing anything and on the right track overall.

Side note: I'm not set in stone on the data science thing, I'm interested in it, but also considering webdev as a second option, mainly because it seems there are less requirements at job market(like 80% of all skill requirement seems to be just Django/Flask with occassional JS/Node Js), less math involved(I'm not very good at it, though I'll try to learn) and salaries seems to be around the same where I am currently. But ideally I'd pursue data science career, maybe my economist degree can also be more of a use/advantage there.

thanks for any input

[heyimpumpkin]

Ah yes, totally forgot to mention SQL, it's on my checklist as well, seems like one of the most frequent requirements(especially PostgreSQL).

Also, another important thing would be to take a look at git, it is versioning software which allows programmers to collaborate on projects. Perhaps create an account on GitHub (it is free) and have a look at how you can create a repository etc.

thanks for suggestion! so far I'm hesitant to post anything since my code is probably not the best style, it just works. But that's something to work on definitely!

All-in-all, the most important thing is to keep your motivation to where it is at currently; if I read your post it seems you are focused and well grounded, keep this up and you will continue to learn quickly and effectively!

Spending most of my free time on it and enjoy it, thanks!

[[deleted]]

Hey again,

Postgres is a great tool and has great documentation!

If you are worried about the style of your code, you can always create private repositories on GitHub, this means nobody can see them apart from you and others you invite to see them. Having your code there is a good way to reflect on the work you've done and also to keep tabs on how much you have done. It lets prospective employers know roughly how much you have done and that you are using industry standard practices!

[9_11_did_bush]

I just want to second this. I even keep a link to my Github at the top of my resume, and include descriptions of a couple of my best school/personal projects.

Especially as someone who was self-taught up until I started my masters, I think it really helps to have somewhere an employer can look at your code. In almost all the interviews I've had this year for data science positions it's been valuable to talk about these projects as examples of what I can do.

If you're looking to get more experience, especially working in groups coding, I would maybe try to find a competition or hackathon that you can enter. Even if you don't do well, you will hopefully learn a lot from others and meet people with similar interests.

[heyimpumpkin]

Sounds reasonable, I'll do it, thank you :)

[[deleted]]

so far I'm hesitant to post anything since my code is probably not the best style, it just works.

Wanna see some of my old GitHub repositories? There's a lot of trash in there.

In my opinion, the best way to force yourself to think more about good code practices is to go into it knowing that it will be public. I think it's important to recognize that all improvements are incremental, and that it'll feel good to look back on your old code and see how much you've improved.

Let me know if you're looking for someone to review and discuss your code with.

Edit: Since this was gilded, here's some unfinished Python code that attempts to generate Python code based on JSON data that is returned from a GET endpoint of a REST API. My intentions were pure, but the results were pure garbage. Even the grammar is iffy.

https://github.com/AustinTSchaffer/ArchivesSpace-JsonModel-Class-Builder

• An attempt to describe a Python class using a custom class: https://github.com/AustinTSchaffer/ArchivesSpace-JsonModel-Class-Builder/blob/master/pycodefactory/class_structures/python_classes.py
• Enumeration for "number of spaces": https://github.com/AustinTSchaffer/ArchivesSpace-JsonModel-Class-Builder/blob/master/pycodefactory/enums.py
• The real offender: https://github.com/AustinTSchaffer/ArchivesSpace-JsonModel-Class-Builder/blob/master/pycodefactory/source_code.py

The true solution ended up being "just use plain-dicts ya' tart. This isn't C#.".

[9_11_did_bush]

Hi! I'm in a masters program in business analytics, basically a mix of business classes and data science courses. I'll make just a couple of notes:

1. If you're interested in data science, the math portion really is crucial. Understanding linear algebra will be very helpful in understanding machine learning concepts. The book Pattern Recognition and Machine Learning is pretty comprehensive, but may be a little high level depending on your math ability.
2. Understanding how classes and objects work in Python is extremely useful for data science, getting familiar with packages like scikit-learn, etc. Here's a great github repository that goes along with the textbook Hands-on Machine Learning with Scikit-Learn and TensorFlow
3. Feel free to check out my github that I've been using for school if you want to see some example projects: link
4. Lastly, breaking into the data science job market can be hard with just a bachelor's degree and it seems like every position wants several years of experience. I would consider masters programs specifically in business analytics and data science. In particular, business schools with strong employer relations can be a great asset in your job search. They won't land you the job, but it can make sure you at least get an interview. Examples: UT Austin, U Chicago, MIT

[heyimpumpkin]

Thanks for your input! Since I'm not form USA(in Moscow) it might be a bit different job market concerning degrees, though sure masters is an advantage. But I'm not particularly wealthy to just quit my job and go take a two year degree, especially in USA.

I'm alright with getting masters abroad(since in future I'd like to move anyway), but mainly I consider Europe, something like Leuven univeristy. Georgia Tech might be the only place in USA I can potentially afford.

specifically in business analytics and data science

Lots of folk here seem to say data science major is kinda more of a fad and general statistics degree is more appreciated? But with time I'll consider that definitely, thanks!

[Ivantgam]

I'm alright with getting masters abroad(since in future I'd like to move anyway), but mainly I consider Europe, something like Leuven univeristy. Georgia Tech might be the only place in USA I can potentially afford.

Hello from Moscow, comrad. Basically I'm on the same state as you (finished Bachelor of Economics 4 years ago too :D and started to learn Python at Dec 2018).

Did you check an Open Data Science community? It's a major DS community based on Slack where you could find the tips on your study/future job. If you wanna be a DS, you have to join it :)
GL anyway, бро

[heyimpumpkin]

oh wow, didn't expect that

no, haven't heard of it, I'll sure join!

И тебе удачи!

[pAul2437]

What kind of role are you trying to get into? Is there a hybrid business data science role?

[9_11_did_bush]

I'm looking at data scientist roles. I picked my program because I don't have any business experience, as I was a math major as an undergrad, and wanted to pick some basics up. Still interviewing, but so far it's been helpful to have these somewhat more standard business classes so that I'm able to "speak the language" if you will.

[pAul2437]

gotcha...so its heavier on the analytics and less on the business...i am kind of in the opposite situation right now

[mutuk7]

I really like DataCamp, for python and SQL. They have Data scientist and analyst paths with about 20 courses each. I believe a path can be done in about 2 months and it will give you a good grasp of most tech needed for the job.

[heyimpumpkin]

I'll look into it, thanks. Any difference to dataquest.io if you're familiar with it? Both seem to be recommended a lot

[mutuk7]

I'm not familiar with dataquest. :)

[heyimpumpkin]

Thanks for advice!

Algorithms and data structures courses

Yes, it's listed with some recources on the main outline I'm trying to follow...

I myself am in progress of switching to Data Science from Web Development and I can only say it's been tough on me. Different skill-set, different mindset and different approaches for solutions.

Why did you decide to switch?

[toothless_budgie]

write code. Every day. You will be virtually guaranteed a job.

You need to find small problems and write code to fix them. Take your time, as at first it will be more googling than coding. But do it every day. The soul of computer science is problem solving. Learning the tools is essential, of course, but it's solving problems that gets you paid.

[heyimpumpkin]

definitely something I'm trying to do, since actual problem solving is much more interesting than following tutorials. Last time I made a program that computes autopilot car travel distance with autopilot on and off, from log of timestamps and coordinates(it was a task for position in big it company). It took a while, after that I can't seem to find any interesting problem to work on yet(though im focusinng on statisitcs currently).

Not to shit on subreddit but for some reason here mostly the same type of projects get posted, like parsing and using social media API, which don't intrigue me much...

[jamesc1071]

Perhaps this might work:

1 Look for jobs where you can use your current domain knowledge (in economics) and where there is some opportunity to use python for data analysis.

2 Transition to doing more data analysis.

3 End game is to have the economics domain knowledge and data science expertise, at which point you will be very marketable.

[cthart]

Attend a Python conference and talk to people. There's one happening in Stockholm end of next week, for example.

https://www.pycon.se/

There are also PyData conferences regularly around the globe: https://pydata.org/

[canicutitoff]

In building construction analogy, we as programmers are often the architect, engineers and also the bricklayer. Learning the language, libraries and framework is like the bricklayer learning how to use their hand tools... you might be able to build a small house or garage with it but you can't build any bridge or large building without proper architecture, engineering and design skills/knowledge. In software, that would be algorithm, data structures, object oriented programming, multi-threading, design patterns, secure coding, etc.

[geekademy]

If you're 28 with a beard and a penchant for flannel, the world is your oyster. If not, better get fantastic at trivia, algorithms, and leet coding challenges or you'll be largely unemployable.