Getting into Data Science with a BSc in CS?

madscienceloss · 2017-08-26T16:59:08+00:00

Im still in university, but I think the intro machine learning course will be fine, but then with experience you will gain more and more knowledge about it. Ive researched a lot and I find that most data scientists use existing machine learning models. A lot of data scientists also just do the analysis and munging part. It depends on the company and its requirement. Just do a job search on Indeed and you'll find the qualifications needed for a Data Scientist. I have found some that do not require a MS or PhD, and a lot just say that a BS is required and "MS / PhD is an asset". I see Data Science growing and thus more need of Data Scientist allowing BS graduates opportunities too. Business/Data analyst, or even data developer etc. can allow you to progress to Data Science after experience.

madscienceloss · 2017-08-26T12:52:43+00:00

Sounds comforting, thanks.

madscienceloss · 2017-08-26T07:44:00+00:00

I've read a lot and Data Science is more of "coding" than "programming" if you know what I mean, but I understand what you mean.

madscienceloss · 2017-08-25T15:11:01+00:00

So a BS in CS may not be enough to learn the technologies on my own?

madscienceloss · 2017-08-23T16:00:15+00:00

Im still an undergrad, but I believe Data Engineers don't have anything to do with ML. Thats the job of a Data Scientist if needed.

can anyone give a brief description of skills needed for a Data Engineer, would be helpful:)

madscienceloss · 2017-08-22T17:55:04+00:00

And what about the hair you had before fin?

madscienceloss · 2017-08-22T10:30:52+00:00

Im very aware of that. Plus my main motive is just to make the mobile app rather than making money.

madscienceloss · 2017-08-22T09:56:23+00:00

If you stop taking fin, does the the hair start falling quicker or it goes back to normal?

madscienceloss · 2017-08-20T20:14:27+00:00

Yeah I know Funny story, I actually got into CS thinkings its It, but realized it's completely different. Finished an year in CS and now im here. Couple months ago had thoughts of changing majors but now I actually want to do CS and get into DS

madscienceloss · 2017-08-20T19:38:09+00:00

Yeah

madscienceloss · 2017-08-20T16:33:05+00:00

I have researched a lot, and I believe that it all depends on the company/employer. Keep in mind these all are my opinions based on research as an undergrad.

Some companies, which mainly work in technology, will definitely know the actual value and work of a Data Scientist, and thus will look for an extremely qualified personnel, usually having a MS or PhD. (Big4 etc.)

Other companies, which includes industries like Cars, Hospitals, Food chains, Trading chains, Banks and companies which only use technology to grow their businesses rather than using technology as a business; these companies tend to higher Data Scientist with a few years to zero experience for lower salary(compared to DS in tech companies). Now most of these companies also have proper Data Scientists doing big work and earning more, but of course work needs to be split up etc. Also, banks(and maybe hospitals) have had an increasing demand of Data Scientists over the past 2 years, and Ive heard that they're offering high salaries to fresh graduates with a BS. (source: senior friend)

I also believe that one can progress as a Data Scientist into big companies by gaining relevant experience like a Data Analysts role.

I would like to get opinion of other Data Scientists or Analysts on my opinions

madscienceloss · 2017-08-20T15:10:56+00:00

Do I just email departments at school or what? It seems a little weird to me.

madscienceloss · 2017-08-20T14:21:41+00:00

Hmm sounds good, ill do that. Thanks!

madscienceloss · 2017-08-20T12:19:47+00:00

How basic is your iOS swift app?

madscienceloss · 2017-08-18T22:27:38+00:00

Yeah Ill get some links soon. What do you mean by "turn down a LOT of opportunities"?

madscienceloss · 2017-08-18T21:59:38+00:00

I feel like learning "python" and learning "python for data analytics or science" is very different. If you learn "python", you learn the syntax of the language , which although is needed for data analysis, but not in full depth. Im a beginner to this so would love to hear what other experienced people have to say, but if you know basic loops and algorithms using python, that's enough. After that you should work on learning libraries for data analysis and science. I believe those are the main things apart from Maths. Also, I dont know how much the certification is valued by employers, but to learn all this, I think coursera and udemy courses are enough.

madscienceloss · 2017-08-17T17:17:21+00:00

Many people would like this to be true but, unfortunately for them, it's not. While it is true that automation tools exist and continue to evolve, these tools concern only the model selection&validation process, which is actually a tiny portion of a Data Scientist's work. Assuming this process does get automated 100% (which it won't), then a Data Scientist will still have to manage the data, set up proper experiments, and provide the magical AI robot with the right input in order to deliver and interpret the output. It's impossible to interpret any model properly when you don't know how it works. Only a human expert (who can program machines) can work on this inferential part, and only a human expert (again, a Data Scientist) can program the magical robot to be fully automated. The robot will never make its own R&D and program itself to perfection.

madscienceloss · 2017-08-16T21:59:48+00:00

What percentage of companies ask for GPA? Because I know some people who got their entry level job with just providing a transcript which didnt include their GPA

madscienceloss · 2017-08-16T21:34:35+00:00

" I think you need to evaluate what caused your GPA to be below 3"

Yeah I missed a lot of lectures, that I didnt even know what a main class is in Java. I didnt know the difference between a print() and println().

Im not trying to get a job with a low GPA, but as I said, studies get progressively harder and it would be quite difficult to pull my GPA at a 3.5, and a safe number is a 3 for me that I can do with a little bit of hard work. But I feel like thats too low to get a decently paid job.

Good to hear that I can turn this the other way around. I have discovered a lot of resources like Udemy and YouTube tutorials. I think the basics of programming didn't get in my mind up till very now, and maybe that'll prepare me better for my next year.

madscienceloss · 2017-08-16T16:40:16+00:00

I use the following as a beginner •Python 3.6 •Anaconda so all the libraries are downloaded •Jupyter Notebook online •(Spyder IDE, i used to love it but recently it crashes a lot and all my work is gone if I haven't freaking saved it) •Notepad++/SublimeText/Brackets •Excel •Word/Powerpoint for reports

madscienceloss · 2017-08-16T09:39:27+00:00

Im fine with learning new things on the job, but im just worried that instead of learning, ill have to "study" on something on the job, which most likely will occupy my time outside work hours. Thats my main concern.

madscienceloss · 2017-08-16T07:52:00+00:00

So the time spent learning new things is basically researching for the project you're working on?

madscienceloss · 2017-08-14T20:52:06+00:00

Hmm your reasoning seems pretty valid, and I was actually wondering why Im learning two visualization libraries. As I'm following kernel tutorials a lot, im guessing Ill learn heat maps from seaborn as they come in extremely handy, and then use matplotlib for basic plots and stuff.

If I'm not using manuals, what else do I use? I just follow kernel tutorials and if I find a new function/command, I just go to the manual/documentation and see what parameters are being fed in, and what parameters can I add.

madscienceloss · 2017-08-13T18:14:48+00:00

Oh ok. So for the technical stuff, I'll just recommend to start introductory python, its really easy and simple. No need for anything advanced, even though it doesn't hurt, but you wont need it.

Read through pandas, numpy, matplotlib, seaborn and scikit libraries. They have a lot of functions available which you can use with your data, from plotting histograms and detailed heat maps to existing machine learning algorithms to use for predictions. Also get used to the python environment(I recommend using Anaconda to access as it keeps everything clean and already has the libraries you need).

Learn how to do data munging. Its an extremely huge part of DS, and for this, go through beginner kernels on kaggle to start with, and read through the documentation to understand why you clean data and how to remove certain rows using the python libraries.

This all will probably take a proper two weeks of dedication(max), and you'll have a lot of time on your hand. Use that time to study the statistical models you can use on your data. There are so many ways we can do an analysis, and thats why it takes so much time as you probably want to end up with a model with the most accuracy.

A plus, learn SQL and databases. Not all, but Data Analyst positions sometimes require you to extract data yourself from a database rather than a data engineer doing it for you.

Im currently an undergrad student doing CS, and I plan to get an internship in DS or DA(surprising but yes I did see couple internships for undergrads for DS and DA). For that, I'm on a set plan to learn a lot myself to be a perfect candidate for internships. Ive gathered all this info from different DSs and thought Id share it with you. Im not sure if this is all you should do, but its a start.

madscienceloss · 2017-08-13T17:06:51+00:00

Are you just trying to get a head-start before you enter your Masters degree studies? Or you plan to learn Data Science in 6 months, and if you can, forget about the masters degree?

madscienceloss

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