I’m currently a math/business teacher in the pandemic, who also operates a business in the pandemic. I’ve got a lot of experience in financial analysis and would like to make the career shift to Data Scientist. I know a few but nobody who has done it a none traditional route (I’m older than the ones I know).
I’m having a little trouble understanding where to start as I am no spring chicken and learning all coding (SWE base) and then doing Data Science seems like it could take 1-2 years and I am supporting multiple children. Could I just do the following courses to kick start my career?
Scientific Computing w/ Python (and/or YouTube “Python for Data Science” - 12 hours+)
Data Analysis w/ Python Cert (and/or YouTube “Intro to DS course” - 6+ hours)
ML w/ Python Cert (not sure if needed)
As a teacher I’ve been impressed with the YouTube content - and feel it’s probably superior to bootcamps. I am highly motivated and capable of networking myself with industry individuals. If for some reason a bootcamp could add value - please LMK. Thanks!!!
Chat with you connections who are data scientists, ask what they would look for when hiring. Implement their suggestions if possible, ask about satisfactory augments to their suggestions when not possible (i.e. doing side projects instead of a 4 year degree). Start applying for jobs and get as much feedback as possible.
It depends. Do you have any background/foundational knowledge in programming? Those three sections come pretty late in the curriculum, so they are written with the assumption that you already know the fundamentals of programming (variables, functions, conditional logic, data structures, etc). If you are an absolute beginner, then I suggest starting with a basic programming course. Those freeCodeCamp sections are in Python, so I’d recommend learning Python (but it doesn’t really matter - the lessons assume that someone knows any language). If you search around on the forum you’ll find some conversations about good Python learning resources.
With a math education background, I would assume that learning the appropriate statistical methods isn’t too intimidating, but you might want to take time to blow the dust off of those skills.
You mention it taking 1-2 years to get the skills you need to change jobs, and that’s not an unreasonable expectation. One thing I try to remind people is that the traditional way to enter the field is to spend 4 years as a full-time student, including months or years of industry experience via internships or summer jobs. Building that degree of knowledge and experience in a fraction of the time requires a lot of work and efficiency. It’s something that people manage to do. It’s something that people manage to do while also supporting themselves. It is not, however, an easy or enjoyable experience.
I built a basic app so yes I can do basic programming but I’m rusty on some things. I planned on learning R & Python which I do not know. I think 1-2 years of time while working in the industry as an Data Anayst or BI Analyst would be fine - I just need to be working.
If you have some programming background, then go ahead and try the freeCodeCamp Python sections and see how it goes. A much more comprehensive Data Science curriculum is being built, but don’t hold your breath.
To clarify, I meant 1-2 years before you are qualified/able to get an industry job is probably a fair estimate.
The other path I suppose would be to go into Software Engineering and then transition as I gain experience. But my math and stats ed lends itself more towards data and I do have some industry connections. My professional (none education) experience is more on management / financial analyst side - FYI.
I’d skim over what R is, and does, but primarily focus on Python for data science.
I don’t hear much, if anything going on with R for data science. I’m not in the data science industry, but the only data science content I hear is for Python. So knowing what R is and how its used might give you an idea of why its not used anywhere near as much as a general language like Python, even for a realm like data science, which is what R is for.
I’d keep as many options open as possible. Its easier to get into some job and transition than to go full force into a specific job from the start.
Its hard enough to get a job in the industry, limiting your options at the start might not be the best option, especially since there is a large overlap between the 2 main “paths” your looking at.
Thanks - especially for note on R - wondering how much programming other than Python I should get into. And again wondering if I should go through all the programming (I understand variables, functions, conditionals and more but using for specific languages is a different matter). My limits are my 3 kids, and I just can’t take the time I could in my 20s.
IME experiencing, data science is harder to get into than web dev without a traditional degree. When I’ve worked with data scientists, I asked them about it and they said you basically need a masters or PhD for most jobs.
Maybe things have shifted over the last few years, but it might be hard
This is understandable, however it also doesn’t mean its impossible, only that it may take longer if you have less time to commit. If you have very limited time to commit, things might get near impossible, as learning takes time and effort.
“All the programming” isn’t so much a choice, but the job itself. There’s always more to learn, there isn’t really a time/spot where you can just stop learning and “know everything”.
Languages are just tools, its how you use them, what they are good/bad at, and why’d you’d use one over the other is where knowing different languages is helpful.
However, like having a large pile of tools, aren’t of much use if your aren’t sure use how to wield them. Same way building something out of wood could be done using primitive, simple tools could be done using fancier modern ones, doesn’t change the fact you need to know how to build whatever your building.
In that sense, knowing a tool, or language such as Python, and how to wield it to build all sorts of things is more important than trying to learn a bunch of tools and not be able to build anything. Its those underlying concepts are what you’d strive to learn, while using whatever tool you picked up (Python or R or the like).
UM and all these schools are basically running diploma mills for 40k that are just online Us. Its 20-45k for all of these programs - most run by coursera or the like. I don’t see how they will be much different than FreeCodeCamp.org other than a name brand. Also hearing that HR depts from big firms (MS) won’t even consider you unless you are from a top 3 school. It’s so incredibly dumb considering the entire industry was setup by people w/o diplomas working out of their garages. 45k ed for 100k+ salary is basically the trade you are making. Just not sure an industry person is going to take a UM coursera Masters seriously. I doubt they know what is happening. What do you think?
I can 100% confirm that this is false. Even if there were a consensus on what the “top 3” schools are, the majority of people being hired by these companies didn’t go to them. What there is a heavy bias towards is an accredited degree program because that means that certain defined, shared standards of education are met. I’m not claiming that formal education is the only (or always the best) way to prepare for a tech career, but I do think that it’s understandable why companies would prefer it for an entry-level hire.
Some people in the hiring process may be knowledgeable about some of the online learning platforms or bootcamps, but they know that not all of them have the same standards or represent the same amount of work. What an online program or bootcamp can show in general is how much time, effort, and dedication you’ve put into your studies. The primary benefit anyone will get from these programs is the education itself, but if the program is challenging and thorough then it can also be an asset on your resume.