Advice for pursuing a education/career in Data Science

So, this is a very broad question. I wasn’t sure if this is the kind of thing you wanted to be asked here, so other people could see it.

I’m interested in pursuing an education in computer science, more specifically data science, and eventually turning that into a career.

I currently work 40+ hours a week for an NGO. They’re fine with me going back to school, and have told me that they definitely see the benefit (for both of us) for me pursuing an education.

The problem I’m facing is that I am pretty much registering as a non-degree seeking student, and I have to wait until the last open registration date to sign up for classes. By this point, most of the spots are filled and the university will not do any overrides or make any exceptions. I understand this - degree-seeking students are obviously going to be the top priority.

So, I’m trying to knock out the prerequisite courses needed to apply to the Data Science Masters Program I’m eyeing. I was curious what you (you as in you all, and Zed) recommend? Another thing I wanted to ask is, is going to school a must to pursue a career in data science or programming in general? Is this preferable to an online program, and what are your thoughts on those? I’m fine with self-teaching - I just want to know I’m not taking all these steps in vain.

Thanks!

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Hmm, it sounds like you’re going about it the correct way. You’d do your independent study, and then apply to schools. I’d say though that you should check out some of the courses online that people rave about. I personally have also a few books on data science and machine learning that I’m going to go through.

I’d say the primary thing to do is get good at Python first. It’ll make any study of Data Science a lot easier. Also, what’s your math background already? Statistics?

I’ve only taken pre-cal trig and algebra, so I have a bit of catching up to do. Going to enroll in Cal 1 this fall. I plan on going over the stuff I’ve already learned, take a look at linear algebra, and then hopefully start learning Cal 1 before classes start so I can feel comfortable. I also have to take an intro to python course too, but at least I’ll 100% be prepared for that.

Any recommendations for classes or books on data science? I definitely plan on getting better at python before I try to tackle data science. Not too sure how good at Python I’ll be need to be - ideally I want to be well-rounded in the language regardless.

My recommendation is that you take an elementary statistics course at a community college before you commit to spending a lot of time on the math/statistics courses. The elem stat course can’t be used for a data science degree, but it only requires the algebra you have already have. An elementary stat course will give you a taste of what data analysis is about. Plus the tuition is cheaper than a 4-year college.
I took a marketing course in college and I learned that sales/marketing was not something I wanted to do as a career. I like creating and making things. The kind of work that I did as an engineer. I could have made a lot of money in sales but I doubt if I would have enjoyed the job.

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Any chance you could recommend a book I check out during the meantime?

I’m currently looking into the idea of juco courses. Unfortunately the school I’m going to attend won’t accept juco credits for transfer students.

A couple of widely used textbooks are by Bluman and another by Triola (Triola probably more so than Bluman’s). You can find old editions for very cheap prices. Don’t buy the newest edition (for self study). An example of a difference between editions might be a baseball statistics problem. That problem in the newer edition will use the name of the latest famous baseball player but the problem will be same as the old edition.
For completely free books, you could do a search on “open source statistics books”. But I can’t give an opinion about those because I quit teaching a couple of years ago. So I haven’t looked at them.
Again, I recommend taking only the Elementary Statistics class at a community college and nothing else. You should come out of that class wanting to know more. If not, don’t do this career change just for the money.

No need to worry, definitely not doing this for money.

And since enrolling in a class currently isn’t an option, I’ll check out the book(s) you recommended, and maybe see if there are any online courses. I’ll see if there are any community college courses being offered nearby in the upcoming semesters.

I know this is a bit dated, but for future readers, this might be of interest.
I also took a leap into computer science and data science after finishing my degree in business. I eventually ended up doing another master’s degree in computer science and I now work as a machine learning engineer.

From that experience, I can say: Going through formal education in CS is helpful but definitely not a must. The main advantage of going to school is the ability to directly interface with professors, and fellow students. There is so much open source educational material out there and amazing online courses that are on par with what you would get at most universities. In fact, most of the hard skills I use as a machine learning engineer like Python programming, advanced math, or cloud computing I learned through self-study.

For data science, the most important basic skills are Programming in Python (or perhaps R) and statistics. I’d highly recommend also studying linear algebra and calculus.
You can check out my blog for an overview of the math.
I also highly recommend checking out the various Data Science and statistics specializations on Coursera.
With online resources like Learn Code The Hard Way, Coursera, and books, you can acquire the knowledge of a full CS degree for a few hundred books and at any time that suits you.

A free service run by Zed A. Shaw for learncodethehardway.org.